bayesPop: Probabilistic Population Projections

PubMed Central

Ševčíková, Hana; Raftery, Adrian E.

2016-01-01

We describe bayesPop, an R package for producing probabilistic population projections for all countries. This uses probabilistic projections of total fertility and life expectancy generated by Bayesian hierarchical models. It produces a sample from the joint posterior predictive distribution of future age- and sex-specific population counts, fertility rates and mortality rates, as well as future numbers of births and deaths. It provides graphical ways of summarizing this information, including trajectory plots and various kinds of probabilistic population pyramids. An expression language is introduced which allows the user to produce the predictive distribution of a wide variety of derived population quantities, such as the median age or the old age dependency ratio. The package produces aggregated projections for sets of countries, such as UN regions or trading blocs. The methodology has been used by the United Nations to produce their most recent official population projections for all countries, published in the World Population Prospects. PMID:28077933

Exact Analysis of Squared Cross-Validity Coefficient in Predictive Regression Models

ERIC Educational Resources Information Center

Shieh, Gwowen

2009-01-01

In regression analysis, the notion of population validity is of theoretical interest for describing the usefulness of the underlying regression model, whereas the presumably more important concept of population cross-validity represents the predictive effectiveness for the regression equation in future research. It appears that the inference…

Prediction of lung function response for populations exposed to a wide range of ozone conditions

EPA Science Inventory

Abstract Context: A human exposure-response (E-R) model that has previously been demonstrated to accurately predict population mean FEV1 response to ozone exposure has been proposed as the foundation for future risk assessments for ambient ozone. Objective: Fit the origi...

Identifying water price and population criteria for meeting future urban water demand targets

NASA Astrophysics Data System (ADS)

Ashoori, Negin; Dzombak, David A.; Small, Mitchell J.

2017-12-01

Predictive models for urban water demand can help identify the set of factors that must be satisfied in order to meet future targets for water demand. Some of the explanatory variables used in such models, such as service area population and changing temperature and rainfall rates, are outside the immediate control of water planners and managers. Others, such as water pricing and the intensity of voluntary water conservation efforts, are subject to decisions and programs implemented by the water utility. In order to understand this relationship, a multiple regression model fit to 44 years of monthly demand data (1970-2014) for Los Angeles, California was applied to predict possible future demand through 2050 under alternative scenarios for the explanatory variables: population, price, voluntary conservation efforts, and temperature and precipitation outcomes predicted by four global climate models with two CO2 emission scenarios. Future residential water demand in Los Angeles is projected to be largely driven by price and population rather than climate change and conservation. A median projection for the year 2050 indicates that residential water demand in Los Angeles will increase by approximately 36 percent, to a level of 620 million m3 per year. The Monte Carlo simulations of the fitted model for water demand were then used to find the set of conditions in the future for which water demand is predicted to be above or below the Los Angeles Department of Water and Power 2035 goal to reduce residential water demand by 25%. Results indicate that increases in price can not ensure that the 2035 water demand target can be met when population increases. Los Angeles must rely on furthering their conservation initiatives and increasing their use of stormwater capture, recycled water, and expanding their groundwater storage. The forecasting approach developed in this study can be utilized by other cities to understand the future of water demand in water-stressed areas. Improving water demand forecasts will help planners understand and optimize future investments in water supply infrastructure and related programs.

Population response to climate change: linear vs. non-linear modeling approaches.

PubMed

Ellis, Alicia M; Post, Eric

2004-03-31

Research on the ecological consequences of global climate change has elicited a growing interest in the use of time series analysis to investigate population dynamics in a changing climate. Here, we compare linear and non-linear models describing the contribution of climate to the density fluctuations of the population of wolves on Isle Royale, Michigan from 1959 to 1999. The non-linear self excitatory threshold autoregressive (SETAR) model revealed that, due to differences in the strength and nature of density dependence, relatively small and large populations may be differentially affected by future changes in climate. Both linear and non-linear models predict a decrease in the population of wolves with predicted changes in climate. Because specific predictions differed between linear and non-linear models, our study highlights the importance of using non-linear methods that allow the detection of non-linearity in the strength and nature of density dependence. Failure to adopt a non-linear approach to modelling population response to climate change, either exclusively or in addition to linear approaches, may compromise efforts to quantify ecological consequences of future warming.

Climate, CO2 and human population impacts on global wildfire emissions

NASA Astrophysics Data System (ADS)

Knorr, W.; Jiang, L.; Arneth, A.

2016-01-01

Wildfires are by far the largest contributor to global biomass burning and constitute a large global source of atmospheric traces gases and aerosols. Such emissions have a considerable impact on air quality and constitute a major health hazard. Biomass burning also influences the radiative balance of the atmosphere and is thus not only of societal, but also of significant scientific interest. There is a common perception that climate change will lead to an increase in emissions as hot and dry weather events that promote wildfire will become more common. However, even though a few studies have found that the inclusion of CO2 fertilisation of photosynthesis and changes in human population patterns will tend to somewhat lower predictions of future wildfire emissions, no such study has included full ensemble ranges of both climate predictions and population projections, including the effect of different degrees of urbanisation.

Here, we present a series of 124 simulations with the LPJ-GUESS-SIMFIRE global dynamic vegetation-wildfire model, including a semi-empirical formulation for the prediction of burned area based on fire weather, fuel continuity and human population density. The simulations use Climate Model Intercomparison Project 5 (CMIP5) climate predictions from eight Earth system models. These were combined with two Representative Concentration Pathways (RCPs) and five scenarios of future human population density based on the series of Shared Socioeconomic Pathways (SSPs) to assess the sensitivity of emissions to the effect of climate, CO2 and humans. In addition, two alternative parameterisations of the semi-empirical burned-area model were applied. Contrary to previous work, we find no clear future trend of global wildfire emissions for the moderate emissions and climate change scenario based on the RCP 4.5. Only historical population change introduces a decline by around 15 % since 1900. Future emissions could either increase for low population growth and fast urbanisation, or continue to decline for high population growth and slow urbanisation. Only for high future climate change (RCP8.5), wildfire emissions start to rise again after ca. 2020 but are unlikely to reach the levels of 1900 by the end of the 21st century. We find that climate warming will generally increase the risk of fire, but that this is only one of several equally important factors driving future levels of wildfire emissions, which include population change, CO2 fertilisation causing woody thickening, increased productivity and fuel load and faster litter turnover in a warmer climate.

Predicted extinction of unique genetic diversity in marine forests of Cystoseira spp.

PubMed

Buonomo, Roberto; Chefaoui, Rosa M; Lacida, Ricardo Bermejo; Engelen, Aschwin H; Serrão, Ester A; Airoldi, Laura

2018-07-01

Climate change is inducing shifts in species ranges across the globe. These can affect the genetic pools of species, including loss of genetic variability and evolutionary potential. In particular, geographically enclosed ecosystems, like the Mediterranean Sea, have a higher risk of suffering species loss and genetic erosion due to barriers to further range shifts and to dispersal. In this study, we address these questions for three habitat-forming seaweed species, Cystoseira tamariscifolia, C. amentacea and C. compressa, throughout their entire ranges in the Atlantic and Mediterranean regions. We aim to 1) describe their population genetic structure and diversity, 2) model the present and predict the future distribution and 3) assess the consequences of predicted future range shifts for their population genetic structure, according to two contrasting future climate change scenarios. A net loss of suitable areas was predicted in both climatic scenarios across the range of distribution of the three species. This loss was particularly severe for C. amentacea in the Mediterranean Sea (less 90% in the most extreme climatic scenario), suggesting that the species could become potentially at extinction risk. For all species, genetic data showed very differentiated populations, indicating low inter-population connectivity, and high and distinct genetic diversity in areas that were predicted to become lost, causing erosion of unique evolutionary lineages. Our results indicated that the Mediterranean Sea is the most threatened region, where future suitable Cystoseira habitats will become more limited. This is likely to have wider ecosystem impacts as there is a lack of species with the same ecological niche and functional role in the Mediterranean. The projected accelerated loss of already fragmented and disturbed populations and the long-term genetic effects highlight the urge for local scale management strategies that sustain the capacity of these habitat-forming species to persist despite climatic impacts while waiting for global emission reductions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Plasma Free Amino Acid Profiles Predict Four-Year Risk of Developing Diabetes, Metabolic Syndrome, Dyslipidemia, and Hypertension in Japanese Population

PubMed Central

Yamakado, Minoru; Nagao, Kenji; Imaizumi, Akira; Tani, Mizuki; Toda, Akiko; Tanaka, Takayuki; Jinzu, Hiroko; Miyano, Hiroshi; Yamamoto, Hiroshi; Daimon, Takashi; Horimoto, Katsuhisa; Ishizaka, Yuko

2015-01-01

Plasma free amino acid (PFAA) profile is highlighted in its association with visceral obesity and hyperinsulinemia, and future diabetes. Indeed PFAA profiling potentially can evaluate individuals’ future risks of developing lifestyle-related diseases, in addition to diabetes. However, few studies have been performed especially in Asian populations, about the optimal combination of PFAAs for evaluating health risks. We quantified PFAA levels in 3,701 Japanese subjects, and determined visceral fat area (VFA) and two-hour post-challenge insulin (Ins120 min) values in 865 and 1,160 subjects, respectively. Then, models between PFAA levels and the VFA or Ins120 min values were constructed by multiple linear regression analysis with variable selection. Finally, a cohort study of 2,984 subjects to examine capabilities of the obtained models for predicting four-year risk of developing new-onset lifestyle-related diseases was conducted. The correlation coefficients of the obtained PFAA models against VFA or Ins120 min were higher than single PFAA level. Our models work well for future risk prediction. Even after adjusting for commonly accepted multiple risk factors, these models can predict future development of diabetes, metabolic syndrome, and dyslipidemia. PFAA profiles confer independent and differing contributions to increasing the lifestyle-related disease risks in addition to the currently known factors in a general Japanese population. PMID:26156880

Future climate stimulates population out-breaks by relaxing constraints on reproduction.

PubMed

Heldt, Katherine A; Connell, Sean D; Anderson, Kathryn; Russell, Bayden D; Munguia, Pablo

2016-09-14

When conditions are stressful, reproduction and population growth are reduced, but when favourable, reproduction and population size can boom. Theory suggests climate change is an increasingly stressful environment, predicting extinctions or decreased abundances. However, if favourable conditions align, such as an increase in resources or release from competition and predation, future climate can fuel population growth. Tests of such population growth models and the mechanisms by which they are enabled are rare. We tested whether intergenerational increases in population size might be facilitated by adjustments in reproductive success to favourable environmental conditions in a large-scale mesocosm experiment. Herbivorous amphipod populations responded to future climate by increasing 20 fold, suggesting that future climate might relax environmental constraints on fecundity. We then assessed whether future climate reduces variation in mating success, boosting population fecundity and size. The proportion of gravid females doubled, and variance in phenotypic variation of male secondary sexual characters (i.e. gnathopods) was significantly reduced. While future climate can enhance individual growth and survival, it may also reduce constraints on mechanisms of reproduction such that enhanced intra-generational productivity and reproductive success transfers to subsequent generations. Where both intra and intergenerational production is enhanced, population sizes might boom.

Climate, CO2, and demographic impacts on global wildfire emissions

NASA Astrophysics Data System (ADS)

Knorr, W.; Jiang, L.; Arneth, A.

2015-09-01

Wildfires are by far the largest contributor to global biomass burning and constitute a large global source of atmospheric traces gases and aerosols. Such emissions have a considerable impact on air quality and constitute a major health hazard. Biomass burning also influences the radiative balance of the atmosphere and is thus not only of societal, but also of significant scientific interest. There is a common perception that climate change will lead to an increase in emissions as hot and dry weather events that promote wildfire will become more common. However, even though a few studies have found that the inclusion of CO2 fertilization of photosynthesis and changes in human population patterns will tend to somewhat lower predictions of future wildfire emissions, no such study has included full ensemble ranges of both climate predictions and population projections, including the effect of different degrees of urbanisation. Here, we present a series of 124 simulations with the LPJ-GUESS-SIMFIRE global dynamic vegetation - wildfire model, including a semi-empirical formulation for the prediction of burned area based on fire weather, fuel continuity and human population density. The simulations comprise Climate Model Intercomparison Project 5 (CMIP5) climate predictions from eight Earth system models using two Representative Concentration Pathways (RCPs) and five scenarios of future human population density based on the series of Shared Socioeconomic Pathways (SSPs), sensitivity tests for the effect of climate and CO2, as well as a sensitivity analysis using two alternative parameterisations of the semi-empirical burned-area model. Contrary to previous work, we find no clear future trend of global wildfire emissions for the moderate emissions and climate change scenario based on the RCP 4.5. Only historical population change introduces a decline by around 15 % since 1900. Future emissions could either increase for low population growth and fast urbanisation, or continue to decline for high population growth and slow urbanisation. Only for high future climate change (RCP8.5), wildfire emissions start to rise again after ca. 2020 but are unlikely to reach the levels of 1900 by the end of the 21st century. We find that climate warming will generally increase the risk of fire, but that this is only one of several equally important factors driving future levels of wildfire emissions, which include population change, CO2 fertilisation causing woody thickening, increased productivity and fuel load, and faster litter turnover in a warmer climate.

Clinical prediction and the idea of a population.

PubMed

Armstrong, David

2017-04-01

Using an analysis of the British Medical Journal over the past 170 years, this article describes how changes in the idea of a population have informed new technologies of medical prediction. These approaches have largely replaced older ideas of clinical prognosis based on understanding the natural histories of the underlying pathologies. The 19 th -century idea of a population, which provided a denominator for medical events such as births and deaths, was constrained in its predictive power by its method of enumerating individual bodies. During the 20 th century, populations were increasingly constructed through inferential techniques based on patient groups and samples seen to possess variable characteristics. The emergence of these new virtual populations created the conditions for the emergence of predictive algorithms that are used to foretell our medical futures.

The future of the New Zealand plastic surgery workforce.

PubMed

Adams, Brandon M; Klaassen, Michael F; Tan, Swee T

2013-04-05

The New Zealand (NZ) plastic and reconstructive surgery (PRS) workforce provides reconstructive plastic surgery (RPS) public services from six centres. There has been little analysis on whether the workforce is adequate to meet the needs of the NZ population currently or in the future. This study analysed the current workforce, its distribution and future requirements. PRS manpower data, workforce activities, population statistics, and population modelling were analysed to determine current needs and predict future needs for the PRS workforce. The NZ PRS workforce is compared with international benchmarks. Regional variation of the workforce was analysed with respect to the population's access to PRS services. Future supply of specialist plastic surgeons is analysed. NZ has a lower number of plastic surgeons per capita than comparable countries. The current NZ PRS workforce is mal-distributed. Areas of current and emerging future need are identified. The current workforce mal-distribution will worsen with future population growth and distribution. Up to 60% of the NZ population will be at risk of inadequate access to PRS services by 2027. Development of PRS services must be coordinated to ensure that equitable and sustainable services are available throughout NZ. Strategies for ensuring satisfactory future workforce are discussed.

A fuzzy mathematical model of West Java population with logistic growth model

NASA Astrophysics Data System (ADS)

Nurkholipah, N. S.; Amarti, Z.; Anggriani, N.; Supriatna, A. K.

2018-03-01

In this paper we develop a mathematics model of population growth in the West Java Province Indonesia. The model takes the form as a logistic differential equation. We parameterize the model using several triples of data, and choose the best triple which has the smallest Mean Absolute Percentage Error (MAPE). The resulting model is able to predict the historical data with a high accuracy and it also able to predict the future of population number. Predicting the future population is among the important factors that affect the consideration is preparing a good management for the population. Several experiment are done to look at the effect of impreciseness in the data. This is done by considering a fuzzy initial value to the crisp model assuming that the model propagates the fuzziness of the independent variable to the dependent variable. We assume here a triangle fuzzy number representing the impreciseness in the data. We found that the fuzziness may disappear in the long-term. Other scenarios also investigated, such as the effect of fuzzy parameters to the crisp initial value of the population. The solution of the model is obtained numerically using the fourth-order Runge-Kutta scheme.

Risk and the physics of clinical prediction.

PubMed

McEvoy, John W; Diamond, George A; Detrano, Robert C; Kaul, Sanjay; Blaha, Michael J; Blumenthal, Roger S; Jones, Steven R

2014-04-15

The current paradigm of primary prevention in cardiology uses traditional risk factors to estimate future cardiovascular risk. These risk estimates are based on prediction models derived from prospective cohort studies and are incorporated into guideline-based initiation algorithms for commonly used preventive pharmacologic treatments, such as aspirin and statins. However, risk estimates are more accurate for populations of similar patients than they are for any individual patient. It may be hazardous to presume that the point estimate of risk derived from a population model represents the most accurate estimate for a given patient. In this review, we exploit principles derived from physics as a metaphor for the distinction between predictions regarding populations versus patients. We identify the following: (1) predictions of risk are accurate at the level of populations but do not translate directly to patients, (2) perfect accuracy of individual risk estimation is unobtainable even with the addition of multiple novel risk factors, and (3) direct measurement of subclinical disease (screening) affords far greater certainty regarding the personalized treatment of patients, whereas risk estimates often remain uncertain for patients. In conclusion, shifting our focus from prediction of events to detection of disease could improve personalized decision-making and outcomes. We also discuss innovative future strategies for risk estimation and treatment allocation in preventive cardiology. Copyright © 2014 Elsevier Inc. All rights reserved.

Changes in Black-legged Tick Population in New England with Future Climate Change

NASA Astrophysics Data System (ADS)

Krishnan, S.; Huber, M.

2015-12-01

Lyme disease is one of the most frequently reported vector-borne diseases in the United States. In the Northeastern United States, vector transmission is maintained in a horizontal transmission cycle between the vector, the black-legged ticks, and the vertebrate reservoir hosts, which include white-tailed deer, rodents and other medium to large sized mammals. Predicting how vector populations change with future climate change is critical to understanding disease spread in the future, and for developing suitable regional adaptation strategies. For the United States, these predictions have mostly been made using regressions based on field and lab studies, or using spatial suitability studies. However, the relation between tick populations at various life-cycle stages and climate variables are complex, necessitating a mechanistic approach. In this study, we present a framework for driving a mechanistic tick population model with high-resolution regional climate modeling projections. The goal is to estimate changes in black-legged tick populations in New England for the 21st century. The tick population model used is based on the mechanistic approach of Ogden et al., (2005) developed for Canada. Dynamically downscaled climate projections at a 3-kms resolution using the Weather and Research Forecasting Model (WRF) are used to drive the tick population model.

Characterization of the 2012-044C Briz-M Upper Stage Breakup

NASA Technical Reports Server (NTRS)

Hamilton, Joseph A.; Matney, Mark

2013-01-01

The NASA breakup model prediction was close to the observed population for catalog objects. The NASA breakup model predicted a larger population than was observed for objects under 10 cm. The stare technique produces low observation counts, but is readily comparable to model predictions. Customized stare parameters (Az, El, Range) were effective to increase the opportunities for HAX to observe the debris cloud. Other techniques to increase observation count will be considered for future breakup events.

The Orbital Debris Problem and the Challenges for Environment Remediation

NASA Technical Reports Server (NTRS)

Liou, J.-C.

2013-01-01

Orbital debris scientists from major international space agencies, including JAXA and NASA, have worked together to predict the trend of the future environment. A summary presentation was given to the United Nations in February 2013. The orbital debris population in LEO will continue to increase. Catastrophic collisions will continue to occur every 5 to 9 years center dot To limit the growth of the future debris population and to better protect future spacecraft, active debris removal, should be considered.

Future riverine nitrogen export to US coastal regions: Prospects for improving water quality amid population growth.

EPA Science Inventory

Excess nitrogen (N) in the environment degrades ecosystems and adversely affects human health. Here we examine predictions of contemporary (2000) and future (2030) coastal N loading in the continental US by the Nutrient Export from WaterSheds (NEWS) model. Future scenarios were b...

Future Declines of Coronary Heart Disease Mortality in England and Wales Could Counter the Burden of Population Ageing

PubMed Central

Guzman Castillo, Maria; Gillespie, Duncan O. S.; Allen, Kirk; Bandosz, Piotr; Schmid, Volker; Capewell, Simon; O’Flaherty, Martin

2014-01-01

Background Coronary Heart Disease (CHD) remains a major cause of mortality in the United Kingdom. Yet predictions of future CHD mortality are potentially problematic due to population ageing and increase in obesity and diabetes. Here we explore future projections of CHD mortality in England & Wales under two contrasting future trend assumptions. Methods In scenario A, we used the conventional counterfactual scenario that the last-observed CHD mortality rates from 2011 would persist unchanged to 2030. The future number of deaths was calculated by applying those rates to the 2012–2030 population estimates. In scenario B, we assumed that the recent falling trend in CHD mortality rates would continue. Using Lee-Carter and Bayesian Age Period Cohort (BAPC) models, we projected the linear trends up to 2030. We validate our methods using past data to predict mortality from 2002–2011. Then, we computed the error between observed and projected values. Results In scenario A, assuming that 2011 mortality rates stayed constant by 2030, the number of CHD deaths would increase 62% or approximately 39,600 additional deaths. In scenario B, assuming recent declines continued, the BAPC model (the model with lowest error) suggests the number of deaths will decrease by 56%, representing approximately 36,200 fewer deaths by 2030. Conclusions The decline in CHD mortality has been reasonably continuous since 1979, and there is little reason to believe it will soon halt. The commonly used assumption that mortality will remain constant from 2011 therefore appears slightly dubious. By contrast, using the BAPC model and assuming continuing mortality falls offers a more plausible prediction of future trends. Thus, despite population ageing, the number of CHD deaths might halve again between 2011 and 2030. This has implications for how the potential benefits of future cardiovascular strategies might best be calculated and presented. PMID:24918442

Effects of temporal variation in temperature and density dependence on insect population dynamics

USDA-ARS?s Scientific Manuscript database

Understanding effects of environmental variation on insect populations is important in light of predictions about increasing future climatic variability. In order to understand the effects of changing environmental variation on population dynamics and life history evolution in insects one would need...

Effects of changing climate on aquatic habitat and connectivity for remnant populations of a wide-ranging frog species in an arid landscape.

PubMed

Pilliod, David S; Arkle, Robert S; Robertson, Jeanne M; Murphy, Melanie A; Funk, W Chris

2015-09-01

Amphibian species persisting in isolated streams and wetlands in desert environments can be susceptible to low connectivity, genetic isolation, and climate changes. We evaluated the past (1900-1930), recent (1981-2010), and future (2071-2100) climate suitability of the arid Great Basin (USA) for the Columbia spotted frog (Rana luteiventris) and assessed whether changes in surface water may affect connectivity for remaining populations. We developed a predictive model of current climate suitability and used it to predict the historic and future distribution of suitable climates. We then modeled changes in surface water availability at each time period. Finally, we quantified connectivity among existing populations on the basis of hydrology and correlated it with interpopulation genetic distance. We found that the area of the Great Basin with suitable climate conditions has declined by approximately 49% over the last century and will likely continue to decline under future climate scenarios. Climate conditions at currently occupied locations have been relatively stable over the last century, which may explain persistence at these sites. However, future climates at these currently occupied locations are predicted to become warmer throughout the year and drier during the frog's activity period (May - September). Fall and winter precipitation may increase, but as rain instead of snow. Earlier runoff and lower summer base flows may reduce connectivity between neighboring populations, which is already limited. Many of these changes could have negative effects on remaining populations over the next 50-80 years, but milder winters, longer growing seasons, and wetter falls might positively affect survival and dispersal. Collectively, however, seasonal shifts in temperature, precipitation, and stream flow patterns could reduce habitat suitability and connectivity for frogs and possibly other aquatic species inhabiting streams in this arid region.

Implications of demographics on future blood supply: a population-based cross-sectional study.

PubMed

Greinacher, Andreas; Fendrich, Konstanze; Brzenska, Ralf; Kiefel, Volker; Hoffmann, Wolfgang

2011-04-01

Data on blood recipients are sparse and unconnected to data on blood donors. The objective was to analyze the impact of the demographic change on future blood demand and supply in a German federal state. A population-based cross-sectional study was conducted. For all in-hospital transfused red blood cells (RBCs; n = 95,477), in the German federal state Mecklenburg-Pomerania in 2005, characteristics of the patient and the blood donor (118,406 blood donations) were obtained. Population data were used to predict blood demand and supply until 2020. By 2020 the population increase of those aged 65 years or more (+26.4%) in Mecklenburg-Pomerania will be paralleled by a decrease of the potential donor population (18-68 years; -16.1%). Assuming stable rates per age group until 2020, the demand for in-hospital blood transfusions will increase by approximately 25% (24,000 RBC units) while blood donations will decrease by approximately 27% (32,000 RBC units). The resulting, predicted shortfall is 47% of demand for in-hospital patients (56,000 RBC units). Validation using historical data (1997-2007) showed that the model predicted the RBC demand with a deviation of only 1.2%. Demographic changes are particularly pronounced in former East Germany, but by 2030 most European countries will face a similar situation. The decrease of younger age groups requires an increase of blood donation rates and interdisciplinary approaches to reduce the need for transfusion to maintain sufficient blood supply. Demography is a major determinant of future transfusion demand. All efforts should be made by Western societies to systematically obtain data on blood donors and recipients to develop strategies to meet future blood demand. © 2010 American Association of Blood Banks.

Collective motion of predictive swarms

PubMed Central

Vural, Dervis Can

2017-01-01

Theoretical models of populations and swarms typically start with the assumption that the motion of agents is governed by the local stimuli. However, an intelligent agent, with some understanding of the laws that govern its habitat, can anticipate the future, and make predictions to gather resources more efficiently. Here we study a specific model of this kind, where agents aim to maximize their consumption of a diffusing resource, by attempting to predict the future of a resource field and the actions of other agents. Once the agents make a prediction, they are attracted to move towards regions that have, and will have, denser resources. We find that the further the agents attempt to see into the future, the more their attempts at prediction fail, and the less resources they consume. We also study the case where predictive agents compete against non-predictive agents and find the predictors perform better than the non-predictors only when their relative numbers are very small. We conclude that predictivity pays off either when the predictors do not see too far into the future or the number of predictors is small. PMID:29065136

Collective motion of predictive swarms.

PubMed

Rupprecht, Nathaniel; Vural, Dervis Can

2017-01-01

Theoretical models of populations and swarms typically start with the assumption that the motion of agents is governed by the local stimuli. However, an intelligent agent, with some understanding of the laws that govern its habitat, can anticipate the future, and make predictions to gather resources more efficiently. Here we study a specific model of this kind, where agents aim to maximize their consumption of a diffusing resource, by attempting to predict the future of a resource field and the actions of other agents. Once the agents make a prediction, they are attracted to move towards regions that have, and will have, denser resources. We find that the further the agents attempt to see into the future, the more their attempts at prediction fail, and the less resources they consume. We also study the case where predictive agents compete against non-predictive agents and find the predictors perform better than the non-predictors only when their relative numbers are very small. We conclude that predictivity pays off either when the predictors do not see too far into the future or the number of predictors is small.

Modelling obesity trends in Australia: unravelling the past and predicting the future.

PubMed

Hayes, A J; Lung, T W C; Bauman, A; Howard, K

2017-01-01

Modelling is increasingly being used to predict the epidemiology of obesity progression and its consequences. The aims of this study were: (a) to present and validate a model for prediction of obesity among Australian adults and (b) to use the model to project the prevalence of obesity and severe obesity by 2025. Individual level simulation combined with survey estimation techniques to model changing population body mass index (BMI) distribution over time. The model input population was derived from a nationally representative survey in 1995, representing over 12 million adults. Simulations were run for 30 years. The model was validated retrospectively and then used to predict obesity and severe obesity by 2025 among different aged cohorts and at a whole population level. The changing BMI distribution over time was well predicted by the model and projected prevalence of weight status groups agreed with population level data in 2008, 2012 and 2014.The model predicts more growth in obesity among younger than older adult cohorts. Projections at a whole population level, were that healthy weight will decline, overweight will remain steady, but obesity and severe obesity prevalence will continue to increase beyond 2016. Adult obesity prevalence was projected to increase from 19% in 1995 to 35% by 2025. Severe obesity (BMI>35), which was only around 5% in 1995, was projected to be 13% by 2025, two to three times the 1995 levels. The projected rise in obesity severe obesity will have more substantial cost and healthcare system implications than in previous decades. Having a robust epidemiological model is key to predicting these long-term costs and health outcomes into the future.

Future riverine nitrogen export to US coastal regions: Prospects for improving water quality considering population growth

EPA Science Inventory

Excess nitrogen (N) in the environment degrades ecosystems and adversely affects human health. Here we examine predictions of contemporary (2000) and future (2030) coastal N loading in the continental US by the Nutrient Export from WaterSheds (NEWS) model. Future output is from s...

Linear regression analysis of Hospital Episode Statistics predicts a large increase in demand for elective hand surgery in England.

PubMed

Bebbington, Emily; Furniss, Dominic

2015-02-01

We integrated two factors, demographic population shifts and changes in prevalence of disease, to predict future trends in demand for hand surgery in England, to facilitate workforce planning. We analysed Hospital Episode Statistics data for Dupuytren's disease, carpal tunnel syndrome, cubital tunnel syndrome, and trigger finger from 1998 to 2011. Using linear regression, we estimated trends in both diagnosis and surgery until 2030. We integrated this regression with age specific population data from the Office for National Statistics in order to estimate how this will contribute to a change in workload over time. There has been a significant increase in both absolute numbers of diagnoses and surgery for all four conditions. Combined with future population data, we calculate that the total operative burden for these four conditions will increase from 87,582 in 2011 to 170,166 (95% confidence interval 144,517-195,353) in 2030. The prevalence of these diseases in the ageing population, and increasing prevalence of predisposing factors such as obesity and diabetes, may account for the predicted increase in workload. The most cost effective treatments must be sought, which requires high quality clinical trials. Our methodology can be applied to other sub-specialties to help anticipate the need for future service provision. Copyright © 2014 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Predicting body temperature and activity of adult Polyommatus icarus using neural network models under current and projected climate scenarios.

PubMed

Howe, P D; Bryant, S R; Shreeve, T G

2007-10-01

We use field observations in two geographic regions within the British Isles and regression and neural network models to examine the relationship between microhabitat use, thoracic temperatures and activity in a widespread lycaenid butterfly, Polyommatus icarus. We also make predictions for future activity under climate change scenarios. Individuals from a univoltine northern population initiated flight with significantly lower thoracic temperatures than individuals from a bivoltine southern population. Activity is dependent on body temperature and neural network models of body temperature are better at predicting body temperature than generalized linear models. Neural network models of activity with a sole input of predicted body temperature (using weather and microclimate variables) are good predictors of observed activity and were better predictors than generalized linear models. By modelling activity under climate change scenarios for 2080 we predict differences in activity in relation to both regional differences of climate change and differing body temperature requirements for activity in different populations. Under average conditions for low-emission scenarios there will be little change in the activity of individuals from central-southern Britain and a reduction in northwest Scotland from 2003 activity levels. Under high-emission scenarios, flight-dependent activity in northwest Scotland will increase the greatest, despite smaller predicted increases in temperature and decreases in cloud cover. We suggest that neural network models are an effective way of predicting future activity in changing climates for microhabitat-specialist butterflies and that regional differences in the thermoregulatory response of populations will have profound effects on how they respond to climate change.

Mapping, Bayesian Geostatistical Analysis and Spatial Prediction of Lymphatic Filariasis Prevalence in Africa

PubMed Central

Slater, Hannah; Michael, Edwin

2013-01-01

There is increasing interest to control or eradicate the major neglected tropical diseases. Accurate modelling of the geographic distributions of parasitic infections will be crucial to this endeavour. We used 664 community level infection prevalence data collated from the published literature in conjunction with eight environmental variables, altitude and population density, and a multivariate Bayesian generalized linear spatial model that allows explicit accounting for spatial autocorrelation and incorporation of uncertainty in input data and model parameters, to construct the first spatially-explicit map describing LF prevalence distribution in Africa. We also ran the best-fit model against predictions made by the HADCM3 and CCCMA climate models for 2050 to predict the likely distributions of LF under future climate and population changes. We show that LF prevalence is strongly influenced by spatial autocorrelation between locations but is only weakly associated with environmental covariates. Infection prevalence, however, is found to be related to variations in population density. All associations with key environmental/demographic variables appear to be complex and non-linear. LF prevalence is predicted to be highly heterogenous across Africa, with high prevalences (>20%) estimated to occur primarily along coastal West and East Africa, and lowest prevalences predicted for the central part of the continent. Error maps, however, indicate a need for further surveys to overcome problems with data scarcity in the latter and other regions. Analysis of future changes in prevalence indicates that population growth rather than climate change per se will represent the dominant factor in the predicted increase/decrease and spread of LF on the continent. We indicate that these results could play an important role in aiding the development of strategies that are best able to achieve the goals of parasite elimination locally and globally in a manner that may also account for the effects of future climate change on parasitic infection. PMID:23951194

The impact of demographic change on the estimated future burden of infectious diseases: examples from hepatitis B and seasonal influenza in the Netherlands

PubMed Central

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

Detecting pulsars in the Galactic Centre

NASA Astrophysics Data System (ADS)

Rajwade, K. M.; Lorimer, D. R.; Anderson, L. D.

2017-10-01

Although high-sensitivity surveys have revealed a number of highly dispersed pulsars in the inner Galaxy, none have so far been found in the Galactic Centre (GC) region, which we define to be within a projected distance of 1 pc from Sgr A*. This null result is surprising given that several independent lines of evidence predict a sizable population of neutron stars in the region. Here, we present a detailed analysis of both the canonical and millisecond pulsar populations in the GC and consider free-free absorption and multipath scattering to be the two main sources of flux density mitigation. We demonstrate that the sensitivity limits of previous surveys are not sufficient to detect GC pulsar population, and investigate the optimum observing frequency for future surveys. Depending on the degree of scattering and free-free absorption in the GC, current surveys constrain the size of the potentially observable population (I.e. those beaming towards us) to be up to 52 canonical pulsars and 10 000 millisecond pulsars. We find that the optimum frequency for future surveys is in the range of 9-13 GHz. We also predict that future deeper surveys with the Square Kilometre array will probe a significant portion of the existing radio pulsar population in the GC.

Branched-chain and aromatic amino acid profiles and diabetes risk in Chinese populations.

PubMed

Chen, Tianlu; Ni, Yan; Ma, Xiaojing; Bao, Yuqian; Liu, Jiajian; Huang, Fengjie; Hu, Cheng; Xie, Guoxiang; Zhao, Aihua; Jia, Weiping; Jia, Wei

2016-02-05

Recent studies revealed strong evidence that branched-chain and aromatic amino acids (BCAAs and AAAs) are closely associated with the risk of developing type 2 diabetes in several Western countries. The aim of this study was to evaluate the potential role of BCAAs and AAAs in predicting the diabetes development in Chinese populations. The serum levels of valine, leucine, isoleucine, tyrosine, and phenylalanine were measured in a longitudinal and a cross sectional studies with a total of 429 Chinese participants at different stages of diabetes development, using an ultra-performance liquid chromatography triple quadruple mass spectrometry platform. The alterations of the five AAs in Chinese populations are well in accordance with previous reports. Early elevation of the five AAs and their combined score was closely associated with future development of diabetes, suggesting an important role of these metabolites as early markers of diabetes. On the other hand, the five AAs were not as good as existing clinical markers in differentiating diabetic patients from their healthy counterparts. Our findings verified the close correlation of BCAAs and AAAs with insulin resistance and future development of diabetes in Chinese populations and highlighted the predictive value of these markers for future development of diabetes.

Branched-chain and aromatic amino acid profiles and diabetes risk in Chinese populations

PubMed Central

Chen, Tianlu; Ni, Yan; Ma, Xiaojing; Bao, Yuqian; Liu, Jiajian; Huang, Fengjie; Hu, Cheng; Xie, Guoxiang; Zhao, Aihua; Jia, Weiping; Jia, Wei

2016-01-01

Recent studies revealed strong evidence that branched-chain and aromatic amino acids (BCAAs and AAAs) are closely associated with the risk of developing type 2 diabetes in several Western countries. The aim of this study was to evaluate the potential role of BCAAs and AAAs in predicting the diabetes development in Chinese populations. The serum levels of valine, leucine, isoleucine, tyrosine, and phenylalanine were measured in a longitudinal and a cross sectional studies with a total of 429 Chinese participants at different stages of diabetes development, using an ultra-performance liquid chromatography triple quadruple mass spectrometry platform. The alterations of the five AAs in Chinese populations are well in accordance with previous reports. Early elevation of the five AAs and their combined score was closely associated with future development of diabetes, suggesting an important role of these metabolites as early markers of diabetes. On the other hand, the five AAs were not as good as existing clinical markers in differentiating diabetic patients from their healthy counterparts. Our findings verified the close correlation of BCAAs and AAAs with insulin resistance and future development of diabetes in Chinese populations and highlighted the predictive value of these markers for future development of diabetes. PMID:26846565

Dispersal and population state of an endangered island lizard following a conservation translocation.

PubMed

Angeli, Nicole F; Lundgren, Ian F; Pollock, Clayton G; Hillis-Starr, Zandy M; Fitzgerald, Lee A

2018-03-01

Population size is widely used as a unit of ecological analysis, yet to estimate population size requires accounting for observed and latent heterogeneity influencing dispersion of individuals across landscapes. In newly established populations, such as when animals are translocated for conservation, dispersal and availability of resources influence patterns of abundance. We developed a process to estimate population size using N-mixture models and spatial models for newly established and dispersing populations. We used our approach to estimate the population size of critically endangered St. Croix ground lizards (Ameiva polops) five years after translocation of 57 individuals to Buck Island, an offshore island of St. Croix, United States Virgin Islands. Estimates of population size incorporated abiotic variables, dispersal limits, and operative environmental temperature available to the lizards to account for low species detection. Operative environmental temperature and distance from the translocation site were always important in fitting the N-mixture model indicating effects of dispersal and species biology on estimates of population size. We found that the population is increasing its range across the island by 5-10% every six months. We spatially interpolated site-specific abundance from the N-mixture model to the entire island, and we estimated 1,473 (95% CI, 940-1,802) St. Croix ground lizards on Buck Island in 2013 corresponding to survey results. This represents a 26-fold increase since the translocation. We predicted the future dispersal of the lizards to all habitats on Buck Island, with the potential for the population to increase by another five times in the future. Incorporating biologically relevant covariates as explicit parameters in population models can improve predictions of population size and the future spread of species introduced to new localities. © 2018 by the Ecological Society of America.

Early warnings of the potential for malaria transmission in Rural Africa using the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS)

NASA Astrophysics Data System (ADS)

Yamana, T. K.; Eltahir, E. A.

2010-12-01

Early warnings of malaria transmission allow health officials to better prepare for future epidemics. Monitoring rainfall is recognized as an important part of malaria early warning systems, as outlined by the Roll Back Malaria Initiative. The Hydrology, Entomology and Malaria Simulator (HYDREMATS) is a mechanistic model that relates rainfall to malaria transmission, and could be used to provide early warnings of malaria epidemics. HYDREMATS is used to make predictions of mosquito populations and vectorial capacity for 2005, 2006, and 2007 in Banizoumbou village in western Niger. HYDREMATS is forced by observed rainfall, followed by a rainfall prediction based on the seasonal mean rainfall for a period two or four weeks into the future. Predictions made using this method provided reasonable estimates of mosquito populations and vectorial capacity, two to four weeks in advance. The predictions were significantly improved compared to those made when HYDREMATS was forced with seasonal mean rainfall alone.

A changing climate: impacts on human exposures to O3 using ...

EPA Pesticide Factsheets

Predicting the impacts of changing climate on human exposure to air pollution requires future scenarios that account for changes in ambient pollutant concentrations, population sizes and distributions, and housing stocks. An integrated methodology to model changes in human exposures due to these impacts was developed by linking climate, air quality, land-use, and human exposure models. This methodology was then applied to characterize changes in predicted human exposures to O3 under multiple future scenarios. Regional climate projections for the U.S. were developed by downscaling global circulation model (GCM) scenarios for three of the Intergovernmental Panel on Climate Change’s (IPCC’s) Representative Concentration Pathways (RCPs) using the Weather Research and Forecasting (WRF) model. The regional climate results were in turn used to generate air quality (concentration) projections using the Community Multiscale Air Quality (CMAQ) model. For each of the climate change scenarios, future U.S. census-tract level population distributions from the Integrated Climate and Land Use Scenarios (ICLUS) model for four future scenarios based on the IPCC’s Special Report on Emissions Scenarios (SRES) storylines were used. These climate, air quality, and population projections were used as inputs to EPA’s Air Pollutants Exposure (APEX) model for 12 U.S. cities. Probability density functions show changes in the population distribution of 8 h maximum daily O3 exposur

Spatio-temporal environmental variation mediates geographical differences in phenotypic responses to ocean acidification

PubMed Central

Villanueva, Paola A.; Lopez, Jorge; Torres, Rodrigo; Navarro, Jorge M.; Bacigalupe, Leonardo D.

2017-01-01

Phenotypic plasticity is expected to play a major adaptive role in the response of species to ocean acidification (OA), by providing broader tolerances to changes in pCO2 conditions. However, tolerances and sensitivities to future OA may differ among populations within a species because of their particular environmental context and genetic backgrounds. Here, using the climatic variability hypothesis (CVH), we explored this conceptual framework in populations of the sea urchin Loxechinus albus across natural fluctuating pCO2/pH environments. Although elevated pCO2 affected the morphology, physiology, development and survival of sea urchin larvae, the magnitude of these effects differed among populations. These differences were consistent with the predictions of the CVH showing greater tolerance to OA in populations experiencing greater local variation in seawater pCO2/pH. Considering geographical differences in plasticity, tolerances and sensitivities to increased pCO2 will provide more accurate predictions for species responses to future OA. PMID:28179409

Spatio-temporal environmental variation mediates geographical differences in phenotypic responses to ocean acidification.

PubMed

Gaitán-Espitia, Juan Diego; Villanueva, Paola A; Lopez, Jorge; Torres, Rodrigo; Navarro, Jorge M; Bacigalupe, Leonardo D

2017-02-01

Phenotypic plasticity is expected to play a major adaptive role in the response of species to ocean acidification (OA), by providing broader tolerances to changes in p CO 2 conditions. However, tolerances and sensitivities to future OA may differ among populations within a species because of their particular environmental context and genetic backgrounds. Here, using the climatic variability hypothesis (CVH), we explored this conceptual framework in populations of the sea urchin Loxechinus albus across natural fluctuating p CO 2 /pH environments. Although elevated p CO 2 affected the morphology, physiology, development and survival of sea urchin larvae, the magnitude of these effects differed among populations. These differences were consistent with the predictions of the CVH showing greater tolerance to OA in populations experiencing greater local variation in seawater p CO 2 /pH. Considering geographical differences in plasticity, tolerances and sensitivities to increased p CO 2 will provide more accurate predictions for species responses to future OA. © 2017 The Author(s).

Mitigating Future Avian Malaria Threats to Hawaiian Forest Birds from Climate Change.

PubMed

Liao, Wei; Atkinson, Carter T; LaPointe, Dennis A; Samuel, Michael D

2017-01-01

Avian malaria, transmitted by Culex quinquefasciatus mosquitoes in the Hawaiian Islands, has been a primary contributor to population range limitations, declines, and extinctions for many endemic Hawaiian honeycreepers. Avian malaria is strongly influenced by climate; therefore, predicted future changes are expected to expand transmission into higher elevations and intensify and lengthen existing transmission periods at lower elevations, leading to further population declines and potential extinction of highly susceptible honeycreepers in mid- and high-elevation forests. Based on future climate changes and resulting malaria risk, we evaluated the viability of alternative conservation strategies to preserve endemic Hawaiian birds at mid and high elevations through the 21st century. We linked an epidemiological model with three alternative climatic projections from the Coupled Model Intercomparison Project to predict future malaria risk and bird population dynamics for the coming century. Based on climate change predictions, proposed strategies included mosquito population suppression using modified males, release of genetically modified refractory mosquitoes, competition from other introduced mosquitoes that are not competent vectors, evolved malaria-tolerance in native honeycreepers, feral pig control to reduce mosquito larval habitats, and predator control to improve bird demographics. Transmission rates of malaria are predicted to be higher than currently observed and are likely to have larger impacts in high-elevation forests where current low rates of transmission create a refuge for highly-susceptible birds. As a result, several current and proposed conservation strategies will be insufficient to maintain existing forest bird populations. We concluded that mitigating malaria transmission at high elevations should be a primary conservation goal. Conservation strategies that maintain highly susceptible species like Iiwi (Drepanis coccinea) will likely benefit other threatened and endangered Hawai'i species, especially in high-elevation forests. Our results showed that mosquito control strategies offer potential long-term benefits to high elevation Hawaiian honeycreepers. However, combined strategies will likely be needed to preserve endemic birds at mid elevations. Given the delay required to research, develop, evaluate, and improve several of these currently untested conservation strategies we suggest that planning should begin expeditiously.

Mitigating future avian malaria threats to Hawaiian forest birds from climate change

USGS Publications Warehouse

Liao, Wei; Atkinson, Carter T.; LaPointe, Dennis; Samuel, Michael D.

2017-01-01

Avian malaria, transmitted by Culex quinquefasciatus mosquitoes in the Hawaiian Islands, has been a primary contributor to population range limitations, declines, and extinctions for many endemic Hawaiian honeycreepers. Avian malaria is strongly influenced by climate; therefore, predicted future changes are expected to expand transmission into higher elevations and intensify and lengthen existing transmission periods at lower elevations, leading to further population declines and potential extinction of highly susceptible honeycreepers in mid- and high-elevation forests. Based on future climate changes and resulting malaria risk, we evaluated the viability of alternative conservation strategies to preserve endemic Hawaiian birds at mid and high elevations through the 21st century. We linked an epidemiological model with three alternative climatic projections from the Coupled Model Intercomparison Project to predict future malaria risk and bird population dynamics for the coming century. Based on climate change predictions, proposed strategies included mosquito population suppression using modified males, release of genetically modified refractory mosquitoes, competition from other introduced mosquitoes that are not competent vectors, evolved malaria-tolerance in native honeycreepers, feral pig control to reduce mosquito larval habitats, and predator control to improve bird demographics. Transmission rates of malaria are predicted to be higher than currently observed and are likely to have larger impacts in high-elevation forests where current low rates of transmission create a refuge for highly-susceptible birds. As a result, several current and proposed conservation strategies will be insufficient to maintain existing forest bird populations. We concluded that mitigating malaria transmission at high elevations should be a primary conservation goal. Conservation strategies that maintain highly susceptible species like Iiwi (Drepanis coccinea) will likely benefit other threatened and endangered Hawai’i species, especially in high-elevation forests. Our results showed that mosquito control strategies offer potential long-term benefits to high elevation Hawaiian honeycreepers. However, combined strategies will likely be needed to preserve endemic birds at mid elevations. Given the delay required to research, develop, evaluate, and improve several of these currently untested conservation strategies we suggest that planning should begin expeditiously.

Presidential Address National Academy of Neuropsychology Conference Boston 2017.

PubMed

Meyers, John E

2018-05-05

This presidential address attempts to predict the future directions of neuropsychology. Predicting the future is always a difficult thing. By examining population trends such as aging and demographics, a clearer picture becomes visible. The population is getting older and more ethnically diverse. Also, examination of the spending trends in health care indicates that neuropsychology needs to be able to adapt to working with larger population-based patient care as well as individual patient care. Shifts in the demographics of neuropsychology, in that the profession previously was 70% male dominate and now is >70% female dominant are also discussed. Trends in NAN's speaker and leader demographics are examined as well as the need to stay current in the trends and latest neuropsychological research lest we become dinosaurs in the next 5-10 years. Recommendations for new neuropsychologists and post-doctoral fellows are also presented.

Understanding past, contemporary, and future dynamics of plants, populations, and communities using Sonoran Desert winter annuals.

PubMed

Huxman, Travis E; Kimball, Sarah; Angert, Amy L; Gremer, Jennifer R; Barron-Gafford, Greg A; Venable, D Lawrence

2013-07-01

Global change requires plant ecologists to predict future states of biological diversity to aid the management of natural communities, thus introducing a number of significant challenges. One major challenge is considering how the many interacting features of biological systems, including ecophysiological processes, plant life histories, and species interactions, relate to performance in the face of a changing environment. We have employed a functional trait approach to understand the individual, population, and community dynamics of a model system of Sonoran Desert winter annual plants. We have used a comprehensive approach that connects physiological ecology and comparative biology to population and community dynamics, while emphasizing both ecological and evolutionary processes. This approach has led to a fairly robust understanding of past and contemporary dynamics in response to changes in climate. In this community, there is striking variation in physiological and demographic responses to both precipitation and temperature that is described by a trade-off between water-use efficiency (WUE) and relative growth rate (RGR). This community-wide trade-off predicts both the demographic and life history variation that contribute to species coexistence. Our framework has provided a mechanistic explanation to the recent warming, drying, and climate variability that has driven a surprising shift in these communities: cold-adapted species with more buffered population dynamics have increased in relative abundance. These types of comprehensive approaches that acknowledge the hierarchical nature of biology may be especially useful in aiding prediction. The emerging, novel and nonstationary climate constrains our use of simplistic statistical representations of past plant behavior in predicting the future, without understanding the mechanistic basis of change.

Effects of climate change on polar bears.

PubMed

Wiig, Øystein; Aars, Jon; Born, Erik W

2008-01-01

In this article, we review the effects on polar bears of global warming that have already been observed, and try to evaluate what may happen to the polar bears in the future. Many researchers have predicted a wide range of impacts of climate change on polar bear demography and conditions. A predicted major reduction in sea ice habitat will reduce the availability of ice associated seals, the main prey of polar bears, and a loss and fragmentation of polar bear habitat will ultimately lead to large future reductions in most subpopulations. It is likely that polar bears will be lost from many areas where they are common today and also that the total population will change into a few more distinctly isolated populations.

78 FR 65248 - Endangered and Threatened Wildlife and Plants; Threatened Status for the Distinct Population...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-31

... effects of climate change on wolverines in the future. Our assessment of climate change impacts on wolverines used wolverines' snow dependence and suitable wolverine habitat and climate change models to predict future impacts of climate change on wolverine habitat suitability. Some of the commenters...

PREDICTING REGIONAL ALLERGY HOTSPOTS IN FUTURE CLIMATE SCENARIOS – PUTTING THE WHERE & WHEN ON WHEEZING

EPA Science Inventory

This research addresses both the effects and mechanisms by which current and future climate conditions affect the risk factors related to allergic airway disease in humans. Our intensive sampling of pollen production, output, and potency in ecologically distinct ragweed popul...

Effects of changing climate on aquatic habitat and connectivity for remnant populations of a wide-ranging frog species in an arid landscape

USGS Publications Warehouse

Pilliod, David S.; Arkle, Robert S.; Robertson, Jeanne M; Murphy, Melanie; Funk, W. Chris

2015-01-01

Amphibian species persisting in isolated streams and wetlands in desert environments can be susceptible to low connectivity, genetic isolation, and climate changes. We evaluated the past (1900–1930), recent (1981–2010), and future (2071–2100) climate suitability of the arid Great Basin (USA) for the Columbia spotted frog (Rana luteiventris) and assessed whether changes in surface water may affect connectivity for remaining populations. We developed a predictive model of current climate suitability and used it to predict the historic and future distribution of suitable climates. We then modeled changes in surface water availability at each time period. Finally, we quantified connectivity among existing populations on the basis of hydrology and correlated it with interpopulation genetic distance. We found that the area of the Great Basin with suitable climate conditions has declined by approximately 49% over the last century and will likely continue to decline under future climate scenarios. Climate conditions at currently occupied locations have been relatively stable over the last century, which may explain persistence at these sites. However, future climates at these currently occupied locations are predicted to become warmer throughout the year and drier during the frog's activity period (May – September). Fall and winter precipitation may increase, but as rain instead of snow. Earlier runoff and lower summer base flows may reduce connectivity between neighboring populations, which is already limited. Many of these changes could have negative effects on remaining populations over the next 50–80 years, but milder winters, longer growing seasons, and wetter falls might positively affect survival and dispersal. Collectively, however, seasonal shifts in temperature, precipitation, and stream flow patterns could reduce habitat suitability and connectivity for frogs and possibly other aquatic species inhabiting streams in this arid region.

Arthroplasty Utilization in the United States is Predicted by Age-Specific Population Groups.

PubMed

Bashinskaya, Bronislava; Zimmerman, Ryan M; Walcott, Brian P; Antoci, Valentin

2012-01-01

Osteoarthritis is a common indication for hip and knee arthroplasty. An accurate assessment of current trends in healthcare utilization as they relate to arthroplasty may predict the needs of a growing elderly population in the United States. First, incidence data was queried from the United States Nationwide Inpatient Sample from 1993 to 2009. Patients undergoing total knee and hip arthroplasty were identified. Then, the United States Census Bureau was queried for population data from the same study period as well as to provide future projections. Arthroplasty followed linear regression models with the population group >64 years in both hip and knee groups. Projections for procedure incidence in the year 2050 based on these models were calculated to be 1,859,553 cases (hip) and 4,174,554 cases (knee). The need for hip and knee arthroplasty is expected to grow significantly in the upcoming years, given population growth predictions.

A multi-model framework for simulating wildlife population response to land-use and climate change

USGS Publications Warehouse

McRae, B.H.; Schumaker, N.H.; McKane, R.B.; Busing, R.T.; Solomon, A.M.; Burdick, C.A.

2008-01-01

Reliable assessments of how human activities will affect wildlife populations are essential for making scientifically defensible resource management decisions. A principle challenge of predicting effects of proposed management, development, or conservation actions is the need to incorporate multiple biotic and abiotic factors, including land-use and climate change, that interact to affect wildlife habitat and populations through time. Here we demonstrate how models of land-use, climate change, and other dynamic factors can be integrated into a coherent framework for predicting wildlife population trends. Our framework starts with land-use and climate change models developed for a region of interest. Vegetation changes through time under alternative future scenarios are predicted using an individual-based plant community model. These predictions are combined with spatially explicit animal habitat models to map changes in the distribution and quality of wildlife habitat expected under the various scenarios. Animal population responses to habitat changes and other factors are then projected using a flexible, individual-based animal population model. As an example application, we simulated animal population trends under three future land-use scenarios and four climate change scenarios in the Cascade Range of western Oregon. We chose two birds with contrasting habitat preferences for our simulations: winter wrens (Troglodytes troglodytes), which are most abundant in mature conifer forests, and song sparrows (Melospiza melodia), which prefer more open, shrubby habitats. We used climate and land-use predictions from previously published studies, as well as previously published predictions of vegetation responses using FORCLIM, an individual-based forest dynamics simulator. Vegetation predictions were integrated with other factors in PATCH, a spatially explicit, individual-based animal population simulator. Through incorporating effects of landscape history and limited dispersal, our framework predicted population changes that typically exceeded those expected based on changes in mean habitat suitability alone. Although land-use had greater impacts on habitat quality than did climate change in our simulations, we found that small changes in vital rates resulting from climate change or other stressors can have large consequences for population trajectories. The ability to integrate bottom-up demographic processes like these with top-down constraints imposed by climate and land-use in a dynamic modeling environment is a key advantage of our approach. The resulting framework should allow researchers to synthesize existing empirical evidence, and to explore complex interactions that are difficult or impossible to capture through piecemeal modeling approaches. ?? 2008 Elsevier B.V.

Modelling climate change effects on Atlantic salmon: Implications for mitigation in regulated rivers.

PubMed

Sundt-Hansen, L E; Hedger, R D; Ugedal, O; Diserud, O H; Finstad, A G; Sauterleute, J F; Tøfte, L; Alfredsen, K; Forseth, T

2018-08-01

Climate change is expected to alter future temperature and discharge regimes of rivers. These regimes have a strong influence on the life history of most aquatic river species, and are key variables controlling the growth and survival of Atlantic salmon. This study explores how the future abundance of Atlantic salmon may be influenced by climate-induced changes in water temperature and discharge in a regulated river, and investigates how negative impacts in the future can be mitigated by applying different regulated discharge regimes during critical periods for salmon survival. A spatially explicit individual-based model was used to predict juvenile Atlantic salmon population abundance in a regulated river under a range of future water temperature and discharge scenarios (derived from climate data predicted by the Hadley Centre's Global Climate Model (GCM) HadAm3H and the Max Plank Institute's GCM ECHAM4), which were then compared with populations predicted under control scenarios representing past conditions. Parr abundance decreased in all future scenarios compared to the control scenarios due to reduced wetted areas (with the effect depending on climate scenario, GCM, and GCM spatial domain). To examine the potential for mitigation of climate change-induced reductions in wetted area, simulations were run with specific minimum discharge regimes. An increase in abundance of both parr and smolt occurred with an increase in the limit of minimum permitted discharge for three of the four GCM/GCM spatial domains examined. This study shows that, in regulated rivers with upstream storage capacity, negative effects of climate change on Atlantic salmon populations can potentially be mitigated by release of water from reservoirs during critical periods for juvenile salmon. Copyright © 2018. Published by Elsevier B.V.

The Relationship of Baseline Prostate Specific Antigen and Risk of Future Prostate Cancer and Its Variance by Race.

PubMed

Verges, Daniel P; Dani, Hasan; Sterling, William A; Weedon, Jeremy; Atallah, William; Mehta, Komal; Schreiber, David; Weiss, Jeffrey P; Karanikolas, Nicholas T

2017-01-01

Several studies suggest that a baseline prostate specific antigen (PSA) measured in young men predicts future risk of prostate cancer. Considering recent recommendations against PSA screening, high-risk populations (e.g. black men, men with a high baseline PSA) may be particularly vulnerable in the coming years. Thus, we investigated the relationship between baseline PSA and future prostate cancer in a black majority-minority urban population. A retrospective analysis was performed of the prostate biopsy database (n = 994) at the Brooklyn Veterans Affairs Hospital. These men were referred to urology clinic for elevated PSA and biopsied between 2007 and 2014. Multivariate logistic regression was used to predict positive prostate biopsy from log-transformed baseline PSA, race (black, white, or other), and several other variables. The majority of men identified as black (50.2%). Median age at time of baseline PSA and biopsy was 58.6 and 64.8, respectively. Median baseline PSA was similar among black men and white men (2.70 vs 2.91 for black men vs white men, p = 0.232). Even so, black men were more likely than white men to be diagnosed with prostate cancer (OR 1.62, p < 0.0001). Black men less than age 70 were at particularly greater risk than their white counterparts. Baseline PSA was not a statistically significant predictor of future prostate cancer (p = 0.101). Black men were more likely to be diagnosed with prostate cancer than were white men, despite comparable baseline PSA. In our pre-screened population at the urology clinic, a retrospective examination of baseline PSA did not predict future prostate cancer. Copyright © 2016 National Medical Association. Published by Elsevier Inc. All rights reserved.

Factors Predicting Post-High School Employment for Young Adults with Visual Impairments

ERIC Educational Resources Information Center

McDonnall, Michele Capella

2010-01-01

Although low levels of employment among transition-age youth with visual impairments (VI) have long been a concern, empirical research in this area is very limited. The purpose of this study was to identify factors that predict future employment for this population and to compare these factors to the factors that predict employment for the general…

Contrasting effects of climate change on rabbit populations through reproduction.

PubMed

Tablado, Zulima; Revilla, Eloy

2012-01-01

Climate change is affecting many physical and biological processes worldwide. Anticipating its effects at the level of populations and species is imperative, especially for organisms of conservation or management concern. Previous studies have focused on estimating future species distributions and extinction probabilities directly from current climatic conditions within their geographical ranges. However, relationships between climate and population parameters may be so complex that to make these high-level predictions we need first to understand the underlying biological processes driving population size, as well as their individual response to climatic alterations. Therefore, the objective of this study is to investigate the influence that climate change may have on species population dynamics through altering breeding season. We used a mechanistic model based on drivers of rabbit reproductive physiology together with demographic simulations to show how future climate-driven changes in breeding season result in contrasting rabbit population trends across Europe. In the Iberian Peninsula, where rabbits are a native species of high ecological and economic value, breeding seasons will shorten and become more variable leading to population declines, higher extinction risk, and lower resilience to perturbations. Whereas towards north-eastern countries, rabbit numbers are expected to increase through longer and more stable reproductive periods, which augment the probability of new rabbit invasions in those areas. Our study reveals the type of mechanisms through which climate will cause alterations at the species level and emphasizes the need to focus on them in order to better foresee large-scale complex population trends. This is especially important in species like the European rabbit whose future responses may aggravate even further its dual keystone/pest problematic. Moreover, this approach allows us to predict not only distribution shifts but also future population status and growth, and to identify the demographic parameters on which to focus to mitigate global change effects.

Contrasting Effects of Climate Change on Rabbit Populations through Reproduction

PubMed Central

Tablado, Zulima; Revilla, Eloy

2012-01-01

Background Climate change is affecting many physical and biological processes worldwide. Anticipating its effects at the level of populations and species is imperative, especially for organisms of conservation or management concern. Previous studies have focused on estimating future species distributions and extinction probabilities directly from current climatic conditions within their geographical ranges. However, relationships between climate and population parameters may be so complex that to make these high-level predictions we need first to understand the underlying biological processes driving population size, as well as their individual response to climatic alterations. Therefore, the objective of this study is to investigate the influence that climate change may have on species population dynamics through altering breeding season. Methodology/Principal Findings We used a mechanistic model based on drivers of rabbit reproductive physiology together with demographic simulations to show how future climate-driven changes in breeding season result in contrasting rabbit population trends across Europe. In the Iberian Peninsula, where rabbits are a native species of high ecological and economic value, breeding seasons will shorten and become more variable leading to population declines, higher extinction risk, and lower resilience to perturbations. Whereas towards north-eastern countries, rabbit numbers are expected to increase through longer and more stable reproductive periods, which augment the probability of new rabbit invasions in those areas. Conclusions/Significance Our study reveals the type of mechanisms through which climate will cause alterations at the species level and emphasizes the need to focus on them in order to better foresee large-scale complex population trends. This is especially important in species like the European rabbit whose future responses may aggravate even further its dual keystone/pest problematic. Moreover, this approach allows us to predict not only distribution shifts but also future population status and growth, and to identify the demographic parameters on which to focus to mitigate global change effects. PMID:23152836

Population connectivity and genetic diversity of American marten (Martes americana) in the United States northern Rocky Mountains in a climate change context

Treesearch

Tzeidle N. Wasserman; Samuel A. Cushman; Jeremy S. Littell; Andrew J. Shirk; Erin L. Landguth

2013-01-01

Climate change is likely to alter population connectivity, particularly for species associated with higher elevation environments. The goal of this study is to predict the potential effects of future climate change on population connectivity and genetic diversity of American marten populations across a 30.2 million hectare region of the in the US northern Rocky...

Integration of population genetic structure and plant response to climate change: sustaining genetic resources through evaluation of projected threats

Treesearch

Bryce A. Richardson; Marcus V. Warwell; Mee-Sook Kim; Ned B. Klopfenstein; Geral I. McDonald

2010-01-01

To assess threats or predict responses to disturbances, or both, it is essential to recognize and characterize the population structures of forest species in relation to changing environments. Appropriate management of these genetic resources in the future will require (1) understanding the existing genetic diversity/variation and population structure of forest trees...

The Cornucopian Fallacies: The Myth of Perpetual Growth.

ERIC Educational Resources Information Center

Grant, Lindsey

1983-01-01

Julian Simon and Herman Kahn argue that population growth is good, not bad; they ignore or dismiss critical environmental issues. Fallacies in their arguments about predicting the future from the past, climate change, population growth, air quality, resource expansion, the finite earth, and technological growth are examined. (SR)

The uncertainty of future water supply adequacy in megacities: Effects of population growth and climate change

NASA Astrophysics Data System (ADS)

Alarcon, T.; Garcia, M. E.; Small, D. L.; Portney, K.; Islam, S.

2013-12-01

Providing water to the expanding population of megacities, which have over 10 million people, with a stressed and aging water infrastructure creates unprecedented challenges. These challenges are exacerbated by dwindling supply and competing demands, altered precipitation and runoff patterns in a changing climate, fragmented water utility business models, and changing consumer behavior. While there is an extensive literature on the effects of climate change on water resources, the uncertainty of climate change predictions continues to be high. This hinders the value of these predictions for municipal water supply planning. The ability of water utilities to meet future water needs will largely depend on their capacity to make decisions under uncertainty. Water stressors, like changes in demographics, climate, and socioeconomic patterns, have varying degrees of uncertainty. Identifying which stressors will have a greater impact on water resources, may reduce the level of future uncertainty for planning and managing water utilities. Within this context, we analyze historical and projected changes of population and climate to quantify the relative impacts of these two stressors on water resources. We focus on megacities that rely primarily on surface water resources to evaluate (a) population growth pattern from 1950-2010 and projected population for 2010-2060; (b) climate change impact on projected climate change scenarios for 2010-2060; and (c) water access for 1950-2010; projected needs for 2010-2060.

Projecting pest population dynamics under global warming: the combined effect of inter- and intra-annual variations.

PubMed

Zidon, Royi; Tsueda, Hirotsugu; Morin, Efrat; Morin, Shai

2016-06-01

The typical short generation length of insects makes their population dynamics highly sensitive not only to mean annual temperatures but also to their intra-annual variations. To consider the combined effect of both thermal factors under global warming, we propose a modeling framework that links general circulation models (GCMs) with a stochastic weather generator and population dynamics models to predict species population responses to inter- and intra-annual temperature changes. This framework was utilized to explore future changes in populations of Bemisia tabaci, an invasive insect pest-species that affects multiple agricultural systems in the Mediterranean region. We considered three locations representing different pest status and climatic conditions: Montpellier (France), Seville (Spain), and Beit-Jamal (Israel). We produced ensembles of local daily temperature realizations representing current and future (mid-21st century) climatic conditions under two emission scenarios for the three locations. Our simulations predicted a significant increase in the average number of annual generations and in population size, and a significant lengthening of the growing season in all three locations. A negative effect was found only in Seville for the summer season, where future temperatures lead to a reduction in population size. High variability in population size was observed between years with similar annual mean temperatures, suggesting a strong effect of intra-annual temperature variation. Critical periods were from late spring to late summer in Montpellier and from late winter to early summer in Seville and Beit-Jamal. Although our analysis suggested that earlier seasonal activity does not necessarily lead to increased populations load unless an additional generation is produced, it is highly likely that the insect will become a significant pest of open-fields at Mediterranean latitudes above 40° during the next 50 years. Our simulations also implied that current predictions based on mean temperature anomalies are relatively conservative and it is better to apply stochastic tools to resolve complex responses to climate change while taking natural variability into account. In summary, we propose a modeling framework capable of determining distinct intra-annual temperature patterns leading to large or small population sizes, for pest risk assessment and management planning of both natural and agricultural ecosystems.

Predicting the geographical distribution of two invasive termite species from occurrence data.

PubMed

Tonini, Francesco; Divino, Fabio; Lasinio, Giovanna Jona; Hochmair, Hartwig H; Scheffrahn, Rudolf H

2014-10-01

Predicting the potential habitat of species under both current and future climate change scenarios is crucial for monitoring invasive species and understanding a species' response to different environmental conditions. Frequently, the only data available on a species is the location of its occurrence (presence-only data). Using occurrence records only, two models were used to predict the geographical distribution of two destructive invasive termite species, Coptotermes gestroi (Wasmann) and Coptotermes formosanus Shiraki. The first model uses a Bayesian linear logistic regression approach adjusted for presence-only data while the second one is the widely used maximum entropy approach (Maxent). Results show that the predicted distributions of both C. gestroi and C. formosanus are strongly linked to urban development. The impact of future scenarios such as climate warming and population growth on the biotic distribution of both termite species was also assessed. Future climate warming seems to affect their projected probability of presence to a lesser extent than population growth. The Bayesian logistic approach outperformed Maxent consistently in all models according to evaluation criteria such as model sensitivity and ecological realism. The importance of further studies for an explicit treatment of residual spatial autocorrelation and a more comprehensive comparison between both statistical approaches is suggested.

Projected shifts in fish species dominance in Wisconsin lakes under climate change.

PubMed

Hansen, Gretchen J A; Read, Jordan S; Hansen, Jonathan F; Winslow, Luke A

2017-04-01

Temperate lakes may contain both coolwater fish species such as walleye (Sander vitreus) and warmwater fish species such as largemouth bass (Micropterus salmoides). Recent declining walleye and increasing largemouth bass populations have raised questions regarding the future trajectories and management actions for these species. We developed a thermodynamic model of water temperatures driven by downscaled climate data and lake-specific characteristics to estimate daily water temperature profiles for 2148 lakes in Wisconsin, US, under contemporary (1989-2014) and future (2040-2064 and 2065-2089) conditions. We correlated contemporary walleye recruitment and largemouth bass relative abundance to modeled water temperature, lake morphometry, and lake productivity, and projected lake-specific changes in each species under future climate conditions. Walleye recruitment success was negatively related and largemouth bass abundance was positively related to water temperature degree days. Both species exhibited a threshold response at the same degree day value, albeit in opposite directions. Degree days were predicted to increase in the future, although the magnitude of increase varied among lakes, time periods, and global circulation models (GCMs). Under future conditions, we predicted a loss of walleye recruitment in 33-75% of lakes where recruitment is currently supported and a 27-60% increase in the number of lakes suitable for high largemouth bass abundance. The percentage of lakes capable of supporting abundant largemouth bass but failed walleye recruitment was predicted to increase from 58% in contemporary conditions to 86% by mid-century and to 91% of lakes by late century, based on median projections across GCMs. Conversely, the percentage of lakes with successful walleye recruitment and low largemouth bass abundance was predicted to decline from 9% of lakes in contemporary conditions to only 1% of lakes in both future periods. Importantly, we identify up to 85 resilient lakes predicted to continue to support natural walleye recruitment. Management resources could target preserving these resilient walleye populations. © 2016 The Authors. Global Change Biology published by John Wiley & Sons Ltd.

Projected shifts in fish species dominance in Wisconsin lakes under climate change

USGS Publications Warehouse

Hansen, Gretchen JA; Read, Jordan S.; Hansen, Jonathan F.; Winslow, Luke

2016-01-01

Temperate lakes may contain both coolwater fish species such as walleye (Sander vitreus) and warmwater fish species such as largemouth bass (Micropterus salmoides). Recent declining walleye and increasing largemouth bass populations have raised questions regarding the future trajectories and management actions for these species. We developed a thermodynamic model of water temperatures driven by downscaled climate data and lake-specific characteristics to estimate daily water temperature profiles for 2148 lakes in Wisconsin, US, under contemporary (1989–2014) and future (2040–2064 and 2065–2089) conditions. We correlated contemporary walleye recruitment and largemouth bass relative abundance to modeled water temperature, lake morphometry, and lake productivity, and projected lake-specific changes in each species under future climate conditions. Walleye recruitment success was negatively related and largemouth bass abundance was positively related to water temperature degree days. Both species exhibited a threshold response at the same degree day value, albeit in opposite directions. Degree days were predicted to increase in the future, although the magnitude of increase varied among lakes, time periods, and global circulation models (GCMs). Under future conditions, we predicted a loss of walleye recruitment in 33–75% of lakes where recruitment is currently supported and a 27–60% increase in the number of lakes suitable for high largemouth bass abundance. The percentage of lakes capable of supporting abundant largemouth bass but failed walleye recruitment was predicted to increase from 58% in contemporary conditions to 86% by mid-century and to 91% of lakes by late century, based on median projections across GCMs. Conversely, the percentage of lakes with successful walleye recruitment and low largemouth bass abundance was predicted to decline from 9% of lakes in contemporary conditions to only 1% of lakes in both future periods. Importantly, we identify up to 85 resilient lakes predicted to continue to support natural walleye recruitment. Management resources could target preserving these resilient walleye populations.

Ultrasonographic measurements of subclinical carotid atherosclerosis in prediction of ischemic stroke.

PubMed

Mathiesen, E B; Johnsen, S H

2009-01-01

Carotid intima-media thickness (IMT) and plaque measurements are widely used to quantify atherosclerosis and assess the risk of future stroke, and are used as surrogate endpoints for clinical disease. In recent years, it has become clear that carotid IMT and plaque reflect biologically and genetically different aspects of the atherosclerotic process, and are differentially related to risk factors and cardiovascular disease. Plaques are focal manifestations of atherosclerosis while increased IMT represents mainly hypertensive medial hypertrophy. Several prospective studies have showed that IMT and plaque measurements, such as total plaque area and plaque number, are predictive of future stroke. Plaque echogenicity predicts future stroke independent of plaque size. The contribution of IMT and plaque measurements in individual stroke risk prediction in the general population seems to be limited, but may be useful as a tool for individual stratification of high-risk patients.

AEDT: A new concept for ecological dynamics in the ever-changing world.

PubMed

Chesson, Peter

2017-05-01

The important concept of equilibrium has always been controversial in ecology, but a new, more general concept, an asymptotic environmentally determined trajectory (AEDT), overcomes many concerns with equilibrium by realistically incorporating long-term climate change while retaining much of the predictive power of a stable equilibrium. A population or ecological community is predicted to approach its AEDT, which is a function of time reflecting environmental history and biology. The AEDT invokes familiar questions and predictions but in a more realistic context in which consideration of past environments and a future changing profoundly due to human influence becomes possible. Strong applications are also predicted in population genetics, evolution, earth sciences, and economics.

Concepts and tools for predictive modeling of microbial dynamics.

PubMed

Bernaerts, Kristel; Dens, Els; Vereecken, Karen; Geeraerd, Annemie H; Standaert, Arnout R; Devlieghere, Frank; Debevere, Johan; Van Impe, Jan F

2004-09-01

Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models.

Prediction of mortality rates using a model with stochastic parameters

NASA Astrophysics Data System (ADS)

Tan, Chon Sern; Pooi, Ah Hin

2016-10-01

Prediction of future mortality rates is crucial to insurance companies because they face longevity risks while providing retirement benefits to a population whose life expectancy is increasing. In the past literature, a time series model based on multivariate power-normal distribution has been applied on mortality data from the United States for the years 1933 till 2000 to forecast the future mortality rates for the years 2001 till 2010. In this paper, a more dynamic approach based on the multivariate time series will be proposed where the model uses stochastic parameters that vary with time. The resulting prediction intervals obtained using the model with stochastic parameters perform better because apart from having good ability in covering the observed future mortality rates, they also tend to have distinctly shorter interval lengths.

77 FR 73045 - Draft Environmental Impact Statement and Draft Pima County Multi-Species Habitat Conservation...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-07

... County, Arizona, has had one of the fastest growing human populations of any county in the United States... opportunities. Urban growth has resulted in significant development, which is expected to continue in the foreseeable future. A significant proportion of the predicted future development is anticipated to occur in...

The accuracy of matrix population model projections for coniferous trees in the Sierra Nevada, California

USGS Publications Warehouse

van Mantgem, P.J.; Stephenson, N.L.

2005-01-01

1 We assess the use of simple, size-based matrix population models for projecting population trends for six coniferous tree species in the Sierra Nevada, California. We used demographic data from 16 673 trees in 15 permanent plots to create 17 separate time-invariant, density-independent population projection models, and determined differences between trends projected from initial surveys with a 5-year interval and observed data during two subsequent 5-year time steps. 2 We detected departures from the assumptions of the matrix modelling approach in terms of strong growth autocorrelations. We also found evidence of observation errors for measurements of tree growth and, to a more limited degree, recruitment. Loglinear analysis provided evidence of significant temporal variation in demographic rates for only two of the 17 populations. 3 Total population sizes were strongly predicted by model projections, although population dynamics were dominated by carryover from the previous 5-year time step (i.e. there were few cases of recruitment or death). Fractional changes to overall population sizes were less well predicted. Compared with a null model and a simple demographic model lacking size structure, matrix model projections were better able to predict total population sizes, although the differences were not statistically significant. Matrix model projections were also able to predict short-term rates of survival, growth and recruitment. Mortality frequencies were not well predicted. 4 Our results suggest that simple size-structured models can accurately project future short-term changes for some tree populations. However, not all populations were well predicted and these simple models would probably become more inaccurate over longer projection intervals. The predictive ability of these models would also be limited by disturbance or other events that destabilize demographic rates. ?? 2005 British Ecological Society.

Measuring populations to improve vaccination coverage

NASA Astrophysics Data System (ADS)

Bharti, Nita; Djibo, Ali; Tatem, Andrew J.; Grenfell, Bryan T.; Ferrari, Matthew J.

2016-10-01

In low-income settings, vaccination campaigns supplement routine immunization but often fail to achieve coverage goals due to uncertainty about target population size and distribution. Accurate, updated estimates of target populations are rare but critical; short-term fluctuations can greatly impact population size and susceptibility. We use satellite imagery to quantify population fluctuations and the coverage achieved by a measles outbreak response vaccination campaign in urban Niger and compare campaign estimates to measurements from a post-campaign survey. Vaccine coverage was overestimated because the campaign underestimated resident numbers and seasonal migration further increased the target population. We combine satellite-derived measurements of fluctuations in population distribution with high-resolution measles case reports to develop a dynamic model that illustrates the potential improvement in vaccination campaign coverage if planners account for predictable population fluctuations. Satellite imagery can improve retrospective estimates of vaccination campaign impact and future campaign planning by synchronizing interventions with predictable population fluxes.

Measuring populations to improve vaccination coverage

PubMed Central

Bharti, Nita; Djibo, Ali; Tatem, Andrew J.; Grenfell, Bryan T.; Ferrari, Matthew J.

2016-01-01

In low-income settings, vaccination campaigns supplement routine immunization but often fail to achieve coverage goals due to uncertainty about target population size and distribution. Accurate, updated estimates of target populations are rare but critical; short-term fluctuations can greatly impact population size and susceptibility. We use satellite imagery to quantify population fluctuations and the coverage achieved by a measles outbreak response vaccination campaign in urban Niger and compare campaign estimates to measurements from a post-campaign survey. Vaccine coverage was overestimated because the campaign underestimated resident numbers and seasonal migration further increased the target population. We combine satellite-derived measurements of fluctuations in population distribution with high-resolution measles case reports to develop a dynamic model that illustrates the potential improvement in vaccination campaign coverage if planners account for predictable population fluctuations. Satellite imagery can improve retrospective estimates of vaccination campaign impact and future campaign planning by synchronizing interventions with predictable population fluxes. PMID:27703191

Ability of matrix models to explain the past and predict the future of plant populations.

USGS Publications Warehouse

McEachern, Kathryn; Crone, Elizabeth E.; Ellis, Martha M.; Morris, William F.; Stanley, Amanda; Bell, Timothy; Bierzychudek, Paulette; Ehrlen, Johan; Kaye, Thomas N.; Knight, Tiffany M.; Lesica, Peter; Oostermeijer, Gerard; Quintana-Ascencio, Pedro F.; Ticktin, Tamara; Valverde, Teresa; Williams, Jennifer I.; Doak, Daniel F.; Ganesan, Rengaian; Thorpe, Andrea S.; Menges, Eric S.

2013-01-01

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage-based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts' 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data-collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk-averse decisions than to expect precise forecasts from models.

Ability of matrix models to explain the past and predict the future of plant populations.

PubMed

Crone, Elizabeth E; Ellis, Martha M; Morris, William F; Stanley, Amanda; Bell, Timothy; Bierzychudek, Paulette; Ehrlén, Johan; Kaye, Thomas N; Knight, Tiffany M; Lesica, Peter; Oostermeijer, Gerard; Quintana-Ascencio, Pedro F; Ticktin, Tamara; Valverde, Teresa; Williams, Jennifer L; Doak, Daniel F; Ganesan, Rengaian; McEachern, Kathyrn; Thorpe, Andrea S; Menges, Eric S

2013-10-01

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage-based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts' 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data-collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk-averse decisions than to expect precise forecasts from models. © 2013 Society for Conservation Biology.

Forecasting Trends in Disability in a Super-Aging Society: Adapting the Future Elderly Model to Japan.

PubMed

Chen, Brian K; Jalal, Hawre; Hashimoto, Hideki; Suen, Sze-Chuan; Eggleston, Karen; Hurley, Michael; Schoemaker, Lena; Bhattacharya, Jay

2016-12-01

Japan has experienced pronounced population aging, and now has the highest proportion of elderly adults in the world. Yet few projections of Japan's future demography go beyond estimating population by age and sex to forecast the complex evolution of the health and functioning of the future elderly. This study estimates a new state-transition microsimulation model - the Japanese Future Elderly Model (FEM) - for Japan. We use the model to forecast disability and health for Japan's future elderly. Our simulation suggests that by 2040, over 27 percent of Japan's elderly will exhibit 3 or more limitations in IADLs and social functioning; almost one in 4 will experience difficulties with 3 or more ADLs; and approximately one in 5 will suffer limitations in cognitive or intellectual functioning. Since the majority of the increase in disability arises from the aging of the Japanese population, prevention efforts that reduce age-specific morbidity can help reduce the burden of disability but may have only a limited impact on reducing the overall prevalence of disability among Japanese elderly. While both age and morbidity contribute to a predicted increase in disability burden among elderly Japanese in the future, our simulation results suggest that the impact of population aging exceeds the effect of age-specific morbidity on increasing disability in Japan's future.

Statistical model selection for better prediction and discovering science mechanisms that affect reliability

DOE PAGES

Anderson-Cook, Christine M.; Morzinski, Jerome; Blecker, Kenneth D.

2015-08-19

Understanding the impact of production, environmental exposure and age characteristics on the reliability of a population is frequently based on underlying science and empirical assessment. When there is incomplete science to prescribe which inputs should be included in a model of reliability to predict future trends, statistical model/variable selection techniques can be leveraged on a stockpile or population of units to improve reliability predictions as well as suggest new mechanisms affecting reliability to explore. We describe a five-step process for exploring relationships between available summaries of age, usage and environmental exposure and reliability. The process involves first identifying potential candidatemore » inputs, then second organizing data for the analysis. Third, a variety of models with different combinations of the inputs are estimated, and fourth, flexible metrics are used to compare them. As a result, plots of the predicted relationships are examined to distill leading model contenders into a prioritized list for subject matter experts to understand and compare. The complexity of the model, quality of prediction and cost of future data collection are all factors to be considered by the subject matter experts when selecting a final model.« less

Quantifying the health impacts of air pollution under a changing climate-a review of approaches and methodology.

PubMed

Sujaritpong, Sarunya; Dear, Keith; Cope, Martin; Walsh, Sean; Kjellstrom, Tord

2014-03-01

Climate change has been predicted to affect future air quality, with inevitable consequences for health. Quantifying the health effects of air pollution under a changing climate is crucial to provide evidence for actions to safeguard future populations. In this paper, we review published methods for quantifying health impacts to identify optimal approaches and ways in which existing challenges facing this line of research can be addressed. Most studies have employed a simplified methodology, while only a few have reported sensitivity analyses to assess sources of uncertainty. The limited investigations that do exist suggest that examining the health risk estimates should particularly take into account the uncertainty associated with future air pollution emissions scenarios, concentration-response functions, and future population growth and age structures. Knowledge gaps identified for future research include future health impacts from extreme air pollution events, interactions between temperature and air pollution effects on public health under a changing climate, and how population adaptation and behavioural changes in a warmer climate may modify exposure to air pollution and health consequences.

Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis.

PubMed

Agarwal, Vibhu; Zhang, Liangliang; Zhu, Josh; Fang, Shiyuan; Cheng, Tim; Hong, Chloe; Shah, Nigam H

2016-09-21

By recent estimates, the steady rise in health care costs has deprived more than 45 million Americans of health care services and has encouraged health care providers to better understand the key drivers of health care utilization from a population health management perspective. Prior studies suggest the feasibility of mining population-level patterns of health care resource utilization from observational analysis of Internet search logs; however, the utility of the endeavor to the various stakeholders in a health ecosystem remains unclear. The aim was to carry out a closed-loop evaluation of the utility of health care use predictions using the conversion rates of advertisements that were displayed to the predicted future utilizers as a surrogate. The statistical models to predict the probability of user's future visit to a medical facility were built using effective predictors of health care resource utilization, extracted from a deidentified dataset of geotagged mobile Internet search logs representing searches made by users of the Baidu search engine between March 2015 and May 2015. We inferred presence within the geofence of a medical facility from location and duration information from users' search logs and putatively assigned medical facility visit labels to qualifying search logs. We constructed a matrix of general, semantic, and location-based features from search logs of users that had 42 or more search days preceding a medical facility visit as well as from search logs of users that had no medical visits and trained statistical learners for predicting future medical visits. We then carried out a closed-loop evaluation of the utility of health care use predictions using the show conversion rates of advertisements displayed to the predicted future utilizers. In the context of behaviorally targeted advertising, wherein health care providers are interested in minimizing their cost per conversion, the association between show conversion rate and predicted utilization score, served as a surrogate measure of the model's utility. We obtained the highest area under the curve (0.796) in medical visit prediction with our random forests model and daywise features. Ablating feature categories one at a time showed that the model performance worsened the most when location features were dropped. An online evaluation in which advertisements were served to users who had a high predicted probability of a future medical visit showed a 3.96% increase in the show conversion rate. Results from our experiments done in a research setting suggest that it is possible to accurately predict future patient visits from geotagged mobile search logs. Results from the offline and online experiments on the utility of health utilization predictions suggest that such prediction can have utility for health care providers.

Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis

PubMed Central

Zhang, Liangliang; Zhu, Josh; Fang, Shiyuan; Cheng, Tim; Hong, Chloe; Shah, Nigam H

2016-01-01

Background By recent estimates, the steady rise in health care costs has deprived more than 45 million Americans of health care services and has encouraged health care providers to better understand the key drivers of health care utilization from a population health management perspective. Prior studies suggest the feasibility of mining population-level patterns of health care resource utilization from observational analysis of Internet search logs; however, the utility of the endeavor to the various stakeholders in a health ecosystem remains unclear. Objective The aim was to carry out a closed-loop evaluation of the utility of health care use predictions using the conversion rates of advertisements that were displayed to the predicted future utilizers as a surrogate. The statistical models to predict the probability of user’s future visit to a medical facility were built using effective predictors of health care resource utilization, extracted from a deidentified dataset of geotagged mobile Internet search logs representing searches made by users of the Baidu search engine between March 2015 and May 2015. Methods We inferred presence within the geofence of a medical facility from location and duration information from users’ search logs and putatively assigned medical facility visit labels to qualifying search logs. We constructed a matrix of general, semantic, and location-based features from search logs of users that had 42 or more search days preceding a medical facility visit as well as from search logs of users that had no medical visits and trained statistical learners for predicting future medical visits. We then carried out a closed-loop evaluation of the utility of health care use predictions using the show conversion rates of advertisements displayed to the predicted future utilizers. In the context of behaviorally targeted advertising, wherein health care providers are interested in minimizing their cost per conversion, the association between show conversion rate and predicted utilization score, served as a surrogate measure of the model’s utility. Results We obtained the highest area under the curve (0.796) in medical visit prediction with our random forests model and daywise features. Ablating feature categories one at a time showed that the model performance worsened the most when location features were dropped. An online evaluation in which advertisements were served to users who had a high predicted probability of a future medical visit showed a 3.96% increase in the show conversion rate. Conclusions Results from our experiments done in a research setting suggest that it is possible to accurately predict future patient visits from geotagged mobile search logs. Results from the offline and online experiments on the utility of health utilization predictions suggest that such prediction can have utility for health care providers. PMID:27655225

The evolutionary time machine: forecasting how populations can adapt to changing environments using dormant propagules

PubMed Central

Orsini, Luisa; Schwenk, Klaus; De Meester, Luc; Colbourne, John K.; Pfrender, Michael E.; Weider, Lawrence J.

2013-01-01

Evolutionary changes are determined by a complex assortment of ecological, demographic and adaptive histories. Predicting how evolution will shape the genetic structures of populations coping with current (and future) environmental challenges has principally relied on investigations through space, in lieu of time, because long-term phenotypic and molecular data are scarce. Yet, dormant propagules in sediments, soils and permafrost are convenient natural archives of population-histories from which to trace adaptive trajectories along extended time periods. DNA sequence data obtained from these natural archives, combined with pioneering methods for analyzing both ecological and population genomic time-series data, are likely to provide predictive models to forecast evolutionary responses of natural populations to environmental changes resulting from natural and anthropogenic stressors, including climate change. PMID:23395434

Paths more traveled: Predicting future recreation pressures on America’s national forests and grasslands - a Forests on the Edge report

Treesearch

Donald B. K. English; Pam Froemke; Kathleen Hawkos

2014-01-01

Populations near many national forests and grasslands are rising and are outpacing growth elsewhere in the United States. We used National Visitor Use Monitoring (NVUM) data and U.S. census data to examine growth in population and locally based recreation visits within 50 and 100 miles of National Forest System (NFS) boundaries. From 1990 to 2010, the population living...

Influence of internal variability on population exposure to hydroclimatic changes

NASA Astrophysics Data System (ADS)

Mankin, Justin S.; Viviroli, Daniel; Mekonnen, Mesfin M.; Hoekstra, Arjen Y.; Horton, Radley M.; E Smerdon, Jason; Diffenbaugh, Noah S.

2017-04-01

Future freshwater supply, human water demand, and people’s exposure to water stress are subject to multiple sources of uncertainty, including unknown future pathways of fossil fuel and water consumption, and ‘irreducible’ uncertainty arising from internal climate system variability. Such internal variability can conceal forced hydroclimatic changes on multi-decadal timescales and near-continental spatial-scales. Using three projections of population growth, a large ensemble from a single Earth system model, and assuming stationary per capita water consumption, we quantify the likelihoods of future population exposure to increased hydroclimatic deficits, which we define as the average duration and magnitude by which evapotranspiration exceeds precipitation in a basin. We calculate that by 2060, ∽31%-35% of the global population will be exposed to >50% probability of hydroclimatic deficit increases that exceed existing hydrological storage, with up to 9% of people exposed to >90% probability. However, internal variability, which is an irreducible uncertainty in climate model predictions that is under-sampled in water resource projections, creates substantial uncertainty in predicted exposure: ∽86%-91% of people will reside where irreducible uncertainty spans the potential for both increases and decreases in sub-annual water deficits. In one population scenario, changes in exposure to large hydroclimate deficits vary from -3% to +6% of global population, a range arising entirely from internal variability. The uncertainty in risk arising from irreducible uncertainty in the precise pattern of hydroclimatic change, which is typically conflated with other uncertainties in projections, is critical for climate risk management that seeks to optimize adaptations that are robust to the full set of potential real-world outcomes.

The Impact of Climate Change on Indigenous Arabica Coffee (Coffea arabica): Predicting Future Trends and Identifying Priorities

PubMed Central

Gole, Tadesse Woldemariam; Baena, Susana

2012-01-01

Precise modelling of the influence of climate change on Arabica coffee is limited; there are no data available for indigenous populations of this species. In this study we model the present and future predicted distribution of indigenous Arabica, and identify priorities in order to facilitate appropriate decision making for conservation, monitoring and future research. Using distribution data we perform bioclimatic modelling and examine future distribution with the HadCM3 climate model for three emission scenarios (A1B, A2A, B2A) over three time intervals (2020, 2050, 2080). The models show a profoundly negative influence on indigenous Arabica. In a locality analysis the most favourable outcome is a c. 65% reduction in the number of pre-existing bioclimatically suitable localities, and at worst an almost 100% reduction, by 2080. In an area analysis the most favourable outcome is a 38% reduction in suitable bioclimatic space, and the least favourable a c. 90% reduction, by 2080. Based on known occurrences and ecological tolerances of Arabica, bioclimatic unsuitability would place populations in peril, leading to severe stress and a high risk of extinction. This study establishes a fundamental baseline for assessing the consequences of climate change on wild populations of Arabica coffee. Specifically, it: (1) identifies and categorizes localities and areas that are predicted to be under threat from climate change now and in the short- to medium-term (2020–2050), representing assessment priorities for ex situ conservation; (2) identifies ‘core localities’ that could have the potential to withstand climate change until at least 2080, and therefore serve as long-term in situ storehouses for coffee genetic resources; (3) provides the location and characterization of target locations (populations) for on-the-ground monitoring of climate change influence. Arabica coffee is confimed as a climate sensitivite species, supporting data and inference that existing plantations will be neagtively impacted by climate change. PMID:23144840

Atlantic Bluefin Tuna: A Novel Multistock Spatial Model for Assessing Population Biomass

PubMed Central

Taylor, Nathan G.; McAllister, Murdoch K.; Lawson, Gareth L.; Carruthers, Tom; Block, Barbara A.

2011-01-01

Atlantic bluefin tuna (Thunnus thynnus) is considered to be overfished, but the status of its populations has been debated, partly because of uncertainties regarding the effects of mixing on fishing grounds. A better understanding of spatial structure and mixing may help fisheries managers to successfully rebuild populations to sustainable levels while maximizing catches. We formulate a new seasonally and spatially explicit fisheries model that is fitted to conventional and electronic tag data, historic catch-at-age reconstructions, and otolith microchemistry stock-composition data to improve the capacity to assess past, current, and future population sizes of Atlantic bluefin tuna. We apply the model to estimate spatial and temporal mixing of the eastern (Mediterranean) and western (Gulf of Mexico) populations, and to reconstruct abundances from 1950 to 2008. We show that western and eastern populations have been reduced to 17% and 33%, respectively, of 1950 spawning stock biomass levels. Overfishing to below the biomass that produces maximum sustainable yield occurred in the 1960s and the late 1990s for western and eastern populations, respectively. The model predicts that mixing depends on season, ontogeny, and location, and is highest in the western Atlantic. Assuming that future catches are zero, western and eastern populations are predicted to recover to levels at maximum sustainable yield by 2025 and 2015, respectively. However, the western population will not recover with catches of 1750 and 12,900 tonnes (the “rebuilding quotas”) in the western and eastern Atlantic, respectively, with or without closures in the Gulf of Mexico. If future catches are double the rebuilding quotas, then rebuilding of both populations will be compromised. If fishing were to continue in the eastern Atlantic at the unregulated levels of 2007, both stocks would continue to decline. Since populations mix on North Atlantic foraging grounds, successful rebuilding policies will benefit from trans-Atlantic cooperation. PMID:22174745

Predicted shortage of vascular surgeons in the United Kingdom: A matter for debate?

PubMed

Harkin, D W; Beard, J D; Shearman, C P; Wyatt, M G

2016-10-01

Vascular surgery became a new independent surgical specialty in the United Kingdom (UK) in 2013. In this matter for debate we discuss the question, is there a "shortage of vascular surgeons in the United Kingdom?" We used data derived from the "Vascular Surgery United Kingdom Workforce Survey 2014", NHS Employers Electronic Staff Records (ESR), and the National Vascular Registry (NVR) surgeon-level public report to estimate current and predict future workforce requirements. We estimate there are approximately 458 Consultant Vascular Surgeons for the current UK population of 63 million, or 1 per 137,000 population. In several UK Regions there are a large number of relatively small teams (3 or less) of vascular surgeons working in separate NHS Trusts in close geographical proximity. In developed countries, both the number and complexity of vascular surgery procedures (open and endovascular) per capita population is increasing, and concerns have been raised that demand cannot be met without a significant expansion in numbers of vascular surgeons. Additional workforce demand arises from the impact of population growth and changes in surgical work-patterns with respect to gender, working-life-balance and 7-day services. We predict a future shortage of Consultant Vascular Surgeons in the UK and recommend an increase in training numbers and an expansion in the UK Consultant Vascular Surgeon workforce to accommodate population growth, facilitate changes in work-patterns and to create safe sustainable services. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Weather-Related Hazards and Population Change: A Study of Hurricanes and Tropical Storms in the United States, 1980–2012

PubMed Central

FUSSELL, ELIZABETH; CURRAN, SARA R.; DUNBAR, MATTHEW D.; BABB, MICHAEL A.; THOMPSON, LUANNE; MEIJER-IRONS, JACQUELINE

2017-01-01

Environmental determinists predict that people move away from places experiencing frequent weather hazards, yet some of these areas have rapidly growing populations. This analysis examines the relationship between weather events and population change in all U.S. counties that experienced hurricanes and tropical storms between 1980 and 2012. Our database allows for more generalizable conclusions by accounting for heterogeneity in current and past hurricane events and losses and past population trends. We find that hurricanes and tropical storms affect future population growth only in counties with growing, high-density populations, which are only 2 percent of all counties. In those counties, current year hurricane events and related losses suppress future population growth, although cumulative hurricane-related losses actually elevate population growth. Low-density counties and counties with stable or declining populations experience no effect of these weather events. Our analysis provides a methodologically informed explanation for contradictory findings in prior studies. PMID:29326480

Weather-Related Hazards and Population Change: A Study of Hurricanes and Tropical Storms in the United States, 1980-2012.

PubMed

Fussell, Elizabeth; Curran, Sara R; Dunbar, Matthew D; Babb, Michael A; Thompson, Luanne; Meijer-Irons, Jacqueline

2017-01-01

Environmental determinists predict that people move away from places experiencing frequent weather hazards, yet some of these areas have rapidly growing populations. This analysis examines the relationship between weather events and population change in all U.S. counties that experienced hurricanes and tropical storms between 1980 and 2012. Our database allows for more generalizable conclusions by accounting for heterogeneity in current and past hurricane events and losses and past population trends. We find that hurricanes and tropical storms affect future population growth only in counties with growing, high-density populations, which are only 2 percent of all counties. In those counties, current year hurricane events and related losses suppress future population growth, although cumulative hurricane-related losses actually elevate population growth. Low-density counties and counties with stable or declining populations experience no effect of these weather events. Our analysis provides a methodologically informed explanation for contradictory findings in prior studies.

The shadow of the future.

PubMed

Caldwell, J C

1984-01-01

This article focuses on the need for care in evaluating current demographic conditions in Australia and planning for the future. After noting that Australia is basically a nation of immigrants, the author reviews the country's demographic history. Comparisons with other countries and explanations for major changes are included. It is suggested that long-term fertility has probably stabilized just below replacement level. The changing composition of the immigrant population is also analyzed. The author accepts official 1983 population projections in which declines in the rate of population growth are predicted through the year 2021, although the actual population is expected to increase. In the last section, effects of this population growth on the environment are considered. It is concluded that there are no economic or environmental factors precluding continued immigration at the rate of 75,000-100,000 people per year.

Impacts of Climate Change on the Global Invasion Potential of the African Clawed Frog Xenopus laevis

PubMed Central

Ihlow, Flora; Courant, Julien; Secondi, Jean; Herrel, Anthony; Rebelo, Rui; Measey, G. John; Lillo, Francesco; De Villiers, F. André; Vogt, Solveig; De Busschere, Charlotte; Backeljau, Thierry; Rödder, Dennis

2016-01-01

By altering or eliminating delicate ecological relationships, non-indigenous species are considered a major threat to biodiversity, as well as a driver of environmental change. Global climate change affects ecosystems and ecological communities, leading to changes in the phenology, geographic ranges, or population abundance of several species. Thus, predicting the impacts of global climate change on the current and future distribution of invasive species is an important subject in macroecological studies. The African clawed frog (Xenopus laevis), native to South Africa, possesses a strong invasion potential and populations have become established in numerous countries across four continents. The global invasion potential of X. laevis was assessed using correlative species distribution models (SDMs). SDMs were computed based on a comprehensive set of occurrence records covering South Africa, North America, South America and Europe and a set of nine environmental predictors. Models were built using both a maximum entropy model and an ensemble approach integrating eight algorithms. The future occurrence probabilities for X. laevis were subsequently computed using bioclimatic variables for 2070 following four different IPCC scenarios. Despite minor differences between the statistical approaches, both SDMs predict the future potential distribution of X. laevis, on a global scale, to decrease across all climate change scenarios. On a continental scale, both SDMs predict decreasing potential distributions in the species’ native range in South Africa, as well as in the invaded areas in North and South America, and in Australia where the species has not been introduced. In contrast, both SDMs predict the potential range size to expand in Europe. Our results suggest that all probability classes will be equally affected by climate change. New regional conditions may promote new invasions or the spread of established invasive populations, especially in France and Great Britain. PMID:27248830

Impacts of Climate Change on the Global Invasion Potential of the African Clawed Frog Xenopus laevis.

PubMed

Ihlow, Flora; Courant, Julien; Secondi, Jean; Herrel, Anthony; Rebelo, Rui; Measey, G John; Lillo, Francesco; De Villiers, F André; Vogt, Solveig; De Busschere, Charlotte; Backeljau, Thierry; Rödder, Dennis

2016-01-01

By altering or eliminating delicate ecological relationships, non-indigenous species are considered a major threat to biodiversity, as well as a driver of environmental change. Global climate change affects ecosystems and ecological communities, leading to changes in the phenology, geographic ranges, or population abundance of several species. Thus, predicting the impacts of global climate change on the current and future distribution of invasive species is an important subject in macroecological studies. The African clawed frog (Xenopus laevis), native to South Africa, possesses a strong invasion potential and populations have become established in numerous countries across four continents. The global invasion potential of X. laevis was assessed using correlative species distribution models (SDMs). SDMs were computed based on a comprehensive set of occurrence records covering South Africa, North America, South America and Europe and a set of nine environmental predictors. Models were built using both a maximum entropy model and an ensemble approach integrating eight algorithms. The future occurrence probabilities for X. laevis were subsequently computed using bioclimatic variables for 2070 following four different IPCC scenarios. Despite minor differences between the statistical approaches, both SDMs predict the future potential distribution of X. laevis, on a global scale, to decrease across all climate change scenarios. On a continental scale, both SDMs predict decreasing potential distributions in the species' native range in South Africa, as well as in the invaded areas in North and South America, and in Australia where the species has not been introduced. In contrast, both SDMs predict the potential range size to expand in Europe. Our results suggest that all probability classes will be equally affected by climate change. New regional conditions may promote new invasions or the spread of established invasive populations, especially in France and Great Britain.

Comparing models of Red Knot population dynamics

USGS Publications Warehouse

McGowan, Conor P.

2015-01-01

Predictive population modeling contributes to our basic scientific understanding of population dynamics, but can also inform management decisions by evaluating alternative actions in virtual environments. Quantitative models mathematically reflect scientific hypotheses about how a system functions. In Delaware Bay, mid-Atlantic Coast, USA, to more effectively manage horseshoe crab (Limulus polyphemus) harvests and protect Red Knot (Calidris canutus rufa) populations, models are used to compare harvest actions and predict the impacts on crab and knot populations. Management has been chiefly driven by the core hypothesis that horseshoe crab egg abundance governs the survival and reproduction of migrating Red Knots that stopover in the Bay during spring migration. However, recently, hypotheses proposing that knot dynamics are governed by cyclical lemming dynamics garnered some support in data analyses. In this paper, I present alternative models of Red Knot population dynamics to reflect alternative hypotheses. Using 2 models with different lemming population cycle lengths and 2 models with different horseshoe crab effects, I project the knot population into the future under environmental stochasticity and parametric uncertainty with each model. I then compare each model's predictions to 10 yr of population monitoring from Delaware Bay. Using Bayes' theorem and model weight updating, models can accrue weight or support for one or another hypothesis of population dynamics. With 4 models of Red Knot population dynamics and only 10 yr of data, no hypothesis clearly predicted population count data better than another. The collapsed lemming cycle model performed best, accruing ~35% of the model weight, followed closely by the horseshoe crab egg abundance model, which accrued ~30% of the weight. The models that predicted no decline or stable populations (i.e. the 4-yr lemming cycle model and the weak horseshoe crab effect model) were the most weakly supported.

[Considering housing arrangements in elderly life: factors influencing plans concerning future housing arrangements and preferences in a representative sample of 45+ year olds].

PubMed

Spangenberg, L; Glaesmer, H; Brähler, E; Kersting, A; Strauß, B

2013-04-01

Providing care and support for the elderly is a future challenge. Using regression analysis, a representative population-based sample (n = 1,445) was examined with respect to whether they had considered future housing and which variables influenced their thoughts and preferences. The majority of the sample reported thinking about housing in old age and preferred to stay at home in old age. Thoughts about future housing and housing preferences were predicted by different factors in the age groups analyzed. Thinking about future housing was positively associated with increasing age and depression. Other relevant predictors were gender, living with a partner, images of old age (especially negative ones), and anticipated subjective health. These variables also predicted housing preferences. Thoughts about future living arrangements are widespread, and their importance increases with age. The wishes reported do contrast to a certain extent with reality. Planning future care as well as developing consultation guidelines should address these issues while considering the reported influences.

Forecasting Trends in Disability in a Super-Aging Society: Adapting the Future Elderly Model to Japan

PubMed Central

Chen, Brian K.; Jalal, Hawre; Hashimoto, Hideki; Suen, Sze-chuan; Eggleston, Karen; Hurley, Michael; Schoemaker, Lena; Bhattacharya, Jay

2016-01-01

Japan has experienced pronounced population aging, and now has the highest proportion of elderly adults in the world. Yet few projections of Japan’s future demography go beyond estimating population by age and sex to forecast the complex evolution of the health and functioning of the future elderly. This study estimates a new state-transition microsimulation model – the Japanese Future Elderly Model (FEM) – for Japan. We use the model to forecast disability and health for Japan’s future elderly. Our simulation suggests that by 2040, over 27 percent of Japan’s elderly will exhibit 3 or more limitations in IADLs and social functioning; almost one in 4 will experience difficulties with 3 or more ADLs; and approximately one in 5 will suffer limitations in cognitive or intellectual functioning. Since the majority of the increase in disability arises from the aging of the Japanese population, prevention efforts that reduce age-specific morbidity can help reduce the burden of disability but may have only a limited impact on reducing the overall prevalence of disability among Japanese elderly. While both age and morbidity contribute to a predicted increase in disability burden among elderly Japanese in the future, our simulation results suggest that the impact of population aging exceeds the effect of age-specific morbidity on increasing disability in Japan’s future. PMID:28580275

Using demography and movement behavior to predict range expansion of the southern sea otter.

USGS Publications Warehouse

Tinker, M.T.; Doak, D.F.; Estes, J.A.

2008-01-01

In addition to forecasting population growth, basic demographic data combined with movement data provide a means for predicting rates of range expansion. Quantitative models of range expansion have rarely been applied to large vertebrates, although such tools could be useful for restoration and management of many threatened but recovering populations. Using the southern sea otter (Enhydra lutris nereis) as a case study, we utilized integro-difference equations in combination with a stage-structured projection matrix that incorporated spatial variation in dispersal and demography to make forecasts of population recovery and range recolonization. In addition to these basic predictions, we emphasize how to make these modeling predictions useful in a management context through the inclusion of parameter uncertainty and sensitivity analysis. Our models resulted in hind-cast (1989–2003) predictions of net population growth and range expansion that closely matched observed patterns. We next made projections of future range expansion and population growth, incorporating uncertainty in all model parameters, and explored the sensitivity of model predictions to variation in spatially explicit survival and dispersal rates. The predicted rate of southward range expansion (median = 5.2 km/yr) was sensitive to both dispersal and survival rates; elasticity analysis indicated that changes in adult survival would have the greatest potential effect on the rate of range expansion, while perturbation analysis showed that variation in subadult dispersal contributed most to variance in model predictions. Variation in survival and dispersal of females at the south end of the range contributed most of the variance in predicted southward range expansion. Our approach provides guidance for the acquisition of further data and a means of forecasting the consequence of specific management actions. Similar methods could aid in the management of other recovering populations.

Impacts of Climate Change on Native Landcover: Seeking Future Climatic Refuges

PubMed Central

Mangabeira Albernaz, Ana Luisa

2016-01-01

Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified landcover map, from which 25% of the map’s coverage was randomly selected to fuel distribution models. We selected the best geographical distribution models among twelve techniques, validating the predicted distribution for current climate with the landcover map and used the best technique to predict the future distribution. All landcover categories showed changes in area and displacement of the latitudinal/longitudinal centroid. Closed vegetation was the only landcover type predicted to expand its distributional range. The range contractions predicted for other categories were intense, even suggesting extirpation of the sparse vegetation category. The landcover refuges under future climate change represent a small proportion of the South American area and they are disproportionately represented and unevenly distributed, predominantly occupying five of 26 South American countries. The predicted changes, regardless of their direction and intensity, can put biodiversity at risk because they are expected to occur in the near future in terms of the temporal scales of ecological and evolutionary processes. Recognition of the threat of climate change allows more efficient conservation actions. PMID:27618445

Impacts of Climate Change on Native Landcover: Seeking Future Climatic Refuges.

PubMed

Zanin, Marina; Mangabeira Albernaz, Ana Luisa

2016-01-01

Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified landcover map, from which 25% of the map's coverage was randomly selected to fuel distribution models. We selected the best geographical distribution models among twelve techniques, validating the predicted distribution for current climate with the landcover map and used the best technique to predict the future distribution. All landcover categories showed changes in area and displacement of the latitudinal/longitudinal centroid. Closed vegetation was the only landcover type predicted to expand its distributional range. The range contractions predicted for other categories were intense, even suggesting extirpation of the sparse vegetation category. The landcover refuges under future climate change represent a small proportion of the South American area and they are disproportionately represented and unevenly distributed, predominantly occupying five of 26 South American countries. The predicted changes, regardless of their direction and intensity, can put biodiversity at risk because they are expected to occur in the near future in terms of the temporal scales of ecological and evolutionary processes. Recognition of the threat of climate change allows more efficient conservation actions.

Projecting the future of an alpine ungulate under climate change scenarios.

PubMed

White, Kevin S; Gregovich, David P; Levi, Taal

2018-03-01

Climate change represents a primary threat to species persistence and biodiversity at a global scale. Cold adapted alpine species are especially sensitive to climate change and can offer key "early warning signs" about deleterious effects of predicted change. Among mountain ungulates, survival, a key determinant of demographic performance, may be influenced by future climate in complex, and possibly opposing ways. Demographic data collected from 447 mountain goats in 10 coastal Alaska, USA, populations over a 37-year time span indicated that survival is highest during low snowfall winters and cool summers. However, general circulation models (GCMs) predict future increase in summer temperature and decline in winter snowfall. To disentangle how these opposing climate-driven effects influence mountain goat populations, we developed an age-structured population model to project mountain goat population trajectories for 10 different GCM/emissions scenarios relevant for coastal Alaska. Projected increases in summer temperature had stronger negative effects on population trajectories than the positive demographic effects of reduced winter snowfall. In 5 of the 10 GCM/representative concentration pathway (RCP) scenarios, the net effect of projected climate change was extinction over a 70-year time window (2015-2085); smaller initial populations were more likely to go extinct faster than larger populations. Using a resource selection modeling approach, we determined that distributional shifts to higher elevation (i.e., "thermoneutral") summer range was unlikely to be a viable behavioral adaptation strategy; due to the conical shape of mountains, summer range was expected to decline by 17%-86% for 7 of the 10 GCM/RCP scenarios. Projected declines of mountain goat populations are driven by climate-linked bottom-up mechanisms and may have wide ranging implications for alpine ecosystems. These analyses elucidate how projected climate change can negatively alter population dynamics of a sentinel alpine species and provide insight into how demographic modeling can be used to assess risk to species persistence. © 2017 John Wiley & Sons Ltd.

Range-wide patterns of greater sage-grouse persistence

USGS Publications Warehouse

Aldridge, Cameron L.; Nielsen, Scott E.; Beyer, Hawthorne L.; Boyce, Mark S.; Connelly, John W.; Knick, Steven T.; Schroeder, Michael A.

2008-01-01

Aim: Greater sage-grouse (Centrocercus urophasianus), a shrub-steppe obligate species of western North America, currently occupies only half its historical range. Here we examine how broad-scale, long-term trends in landscape condition have affected range contraction. Location: Sagebrush biome of the western USA. Methods: Logistic regression was used to assess persistence and extirpation of greater sage-grouse range based on landscape conditions measured by human population (density and population change), vegetation (percentage of sagebrush habitat), roads (density of and distance to roads), agriculture (cropland, farmland and cattle density), climate (number of severe and extreme droughts) and range periphery. Model predictions were used to identify areas where future extirpations can be expected, while also explaining possible causes of past extirpations. Results: Greater sage-grouse persistence and extirpation were significantly related to sagebrush habitat, cultivated cropland, human population density in 1950, prevalence of severe droughts and historical range periphery. Extirpation of sage-grouse was most likely in areas having at least four persons per square kilometre in 1950, 25% cultivated cropland in 2002 or the presence of three or more severe droughts per decade. In contrast, persistence of sage-grouse was expected when at least 30 km from historical range edge and in habitats containing at least 25% sagebrush cover within 30 km. Extirpation was most often explained (35%) by the combined effects of peripherality (within 30 km of range edge) and lack of sagebrush cover (less than 25% within 30 km). Based on patterns of prior extirpation and model predictions, we predict that 29% of remaining range may be at risk. Main Conclusions: Spatial patterns in greater sage-grouse range contraction can be explained by widely available landscape variables that describe patterns of remaining sagebrush habitat and loss due to cultivation, climatic trends, human population growth and peripherality of populations. However, future range loss may relate less to historical mechanisms and more to recent changes in land use and habitat condition, including energy developments and invasions by non-native species such as cheatgrass (Bromus tectorum) and West Nile virus. In conjunction with local measures of population performance, landscape-scale predictions of future range loss may be useful for prioritizing management and protection. Our results suggest that initial conservation efforts should focus on maintaining large expanses of sagebrush habitat, enhancing quality of existing habitats, and increasing habitat connectivity.

Biotic and abiotic factors predicting the global distribution and population density of an invasive large mammal

PubMed Central

Lewis, Jesse S.; Farnsworth, Matthew L.; Burdett, Chris L.; Theobald, David M.; Gray, Miranda; Miller, Ryan S.

2017-01-01

Biotic and abiotic factors are increasingly acknowledged to synergistically shape broad-scale species distributions. However, the relative importance of biotic and abiotic factors in predicting species distributions is unclear. In particular, biotic factors, such as predation and vegetation, including those resulting from anthropogenic land-use change, are underrepresented in species distribution modeling, but could improve model predictions. Using generalized linear models and model selection techniques, we used 129 estimates of population density of wild pigs (Sus scrofa) from 5 continents to evaluate the relative importance, magnitude, and direction of biotic and abiotic factors in predicting population density of an invasive large mammal with a global distribution. Incorporating diverse biotic factors, including agriculture, vegetation cover, and large carnivore richness, into species distribution modeling substantially improved model fit and predictions. Abiotic factors, including precipitation and potential evapotranspiration, were also important predictors. The predictive map of population density revealed wide-ranging potential for an invasive large mammal to expand its distribution globally. This information can be used to proactively create conservation/management plans to control future invasions. Our study demonstrates that the ongoing paradigm shift, which recognizes that both biotic and abiotic factors shape species distributions across broad scales, can be advanced by incorporating diverse biotic factors. PMID:28276519

Hubbert's Peak: A Physicist's View

NASA Astrophysics Data System (ADS)

McDonald, Richard

2011-11-01

Oil and its by-products, as used in manufacturing, agriculture, and transportation, are the lifeblood of today's 7 billion-person population and our 65T world economy. Despite this importance, estimates of future oil production seem dominated by wishful thinking rather than quantitative analysis. Better studies are needed. In 1956, Dr. M.King Hubbert proposed a theory of resource production and applied it successfully to predict peak U.S. oil production in 1970. Thus, the peak of oil production is referred to as ``Hubbert's Peak.'' Prof. Al Bartlett extended this work in publications and lectures on population and oil. Both Hubbert and Bartlett place peak world oil production at a similar time, essentially now. This paper extends this line of work to include analyses of individual countries, inclusion of multiple Gaussian peaks, and analysis of reserves data. While this is not strictly a predictive theory, we will demonstrate a ``closed'' story connecting production, oil-in-place, and reserves. This gives us the ``most likely'' estimate of future oil availability. Finally, we will comment on synthetic oil and the possibility of carbon-neutral synthetic oil for a sustainable future.

Factors leading to different viability predictions for a grizzly bear data set

USGS Publications Warehouse

Mills, L.S.; Hayes, S.G.; Wisdom, M.J.; Citta, J.; Mattson, D.J.; Murphy, K.

1996-01-01

Population viability analysis programs are being used increasingly in research and management applications, but there has not been a systematic study of the congruence of different program predictions based on a single data set. We performed such an analysis using four population viability analysis computer programs: GAPPS, INMAT, RAMAS/AGE, and VORTEX. The standardized demographic rates used in all programs were generalized from hypothetical increasing and decreasing grizzly bear (Ursus arctos horribilis) populations. Idiosyncracies of input format for each program led to minor differences in intrinsic growth rates that translated into striking differences in estimates of extinction rates and expected population size. In contrast, the addition of demographic stochasticity, environmental stochasticity, and inbreeding costs caused only a small divergence in viability predictions. But, the addition of density dependence caused large deviations between the programs despite our best attempts to use the same density-dependent functions. Population viability programs differ in how density dependence is incorporated, and the necessary functions are difficult to parameterize accurately. Thus, we recommend that unless data clearly suggest a particular density-dependent model, predictions based on population viability analysis should include at least one scenario without density dependence. Further, we describe output metrics that may differ between programs; development of future software could benefit from standardized input and output formats across different programs.

Interacting stressors and the potential for adaptation in a changing world: responses of populations and individuals

PubMed Central

French, Susannah S.; Brodie, Edmund D.

2017-01-01

To accurately predict the impact of environmental change, it is necessary to assay effects of key interacting stressors on vulnerable organisms, and the potential resiliency of their populations. Yet, for the most part, these critical data are missing. We examined the effects of two common abiotic stressors predicted to interact with climate change, salinity and temperature, on the embryonic survival and development of a model freshwater vertebrate, the rough-skinned newt (Taricha granulosa) from different populations. We found that salinity and temperature significantly interacted to affect newt embryonic survival and development, with the negative effects of salinity most pronounced at temperature extremes. We also found significant variation among, and especially within, populations, with different females varying in the performance of their eggs at different salinity–temperature combinations, possibly providing the raw material for future natural selection. Our results highlight the complex nature of predicting responses to climate change in space and time, and provide critical data towards that aim. PMID:28680662

Losing your edge: climate change and the conservation value of range-edge populations.

PubMed

Rehm, Evan M; Olivas, Paulo; Stroud, James; Feeley, Kenneth J

2015-10-01

Populations occurring at species' range edges can be locally adapted to unique environmental conditions. From a species' perspective, range-edge environments generally have higher severity and frequency of extreme climatic events relative to the range core. Under future climates, extreme climatic events are predicted to become increasingly important in defining species' distributions. Therefore, range-edge genotypes that are better adapted to extreme climates relative to core populations may be essential to species' persistence during periods of rapid climate change. We use relatively simple conceptual models to highlight the importance of locally adapted range-edge populations (leading and trailing edges) for determining the ability of species to persist under future climates. Using trees as an example, we show how locally adapted populations at species' range edges may expand under future climate change and become more common relative to range-core populations. We also highlight how large-scale habitat destruction occurring in some geographic areas where many species range edge converge, such as biome boundaries and ecotones (e.g., the arc of deforestation along the rainforest-cerrado ecotone in the southern Amazonia), can have major implications for global biodiversity. As climate changes, range-edge populations will play key roles in helping species to maintain or expand their geographic distributions. The loss of these locally adapted range-edge populations through anthropogenic disturbance is therefore hypothesized to reduce the ability of species to persist in the face of rapid future climate change.

Change in avian abundance predicted from regional forest inventory data

USGS Publications Warehouse

Twedt, Daniel J.; Tirpak, John M.; Jones-Farrand, D. Todd; Thompson, Frank R.; Uihlein, William B.; Fitzgerald, Jane A.

2010-01-01

An inability to predict population response to future habitat projections is a shortcoming in bird conservation planning. We sought to predict avian response to projections of future forest conditions that were developed from nationwide forest surveys within the Forest Inventory and Analysis (FIA) program. To accomplish this, we evaluated the historical relationship between silvicolous bird populations and FIA-derived forest conditions within 25 ecoregions that comprise the southeastern United States. We aggregated forest area by forest ownership, forest type, and tree size-class categories in county-based ecoregions for 5 time periods spanning 1963-2008. We assessed the relationship of forest data with contemporaneous indices of abundance for 24 silvicolous bird species that were obtained from Breeding Bird Surveys. Relationships between bird abundance and forest inventory data for 18 species were deemed sufficient as predictive models. We used these empirically derived relationships between regional forest conditions and bird populations to predict relative changes in abundance of these species within ecoregions that are anticipated to coincide with projected changes in forest variables through 2040. Predicted abundances of these 18 species are expected to remain relatively stable in over a quarter (27%) of the ecoregions. However, change in forest area and redistribution of forest types will likely result in changed abundance of some species within many ecosystems. For example, abundances of 11 species, including pine warbler (Dendroica pinus), brown-headed nuthatch (Sitta pusilla), and chuckwills- widow (Caprimulgus carolinensis), are projected to increase within more ecoregions than ecoregions where they will decrease. For 6 other species, such as blue-winged warbler (Vermivora pinus), Carolina wren (Thryothorus ludovicianus), and indigo bunting (Passerina cyanea), we projected abundances will decrease within more ecoregions than ecoregions where they will increase.

Effects of climate change and variability on population dynamics in a long-lived shorebird.

PubMed

van de Pol, Martijn; Vindenes, Yngvild; Saether, Bernt-Erik; Engen, Steinar; Ens, Bruno J; Oosterbeek, Kees; Tinbergen, Joost M

2010-04-01

Climate change affects both the mean and variability of climatic variables, but their relative impact on the dynamics of populations is still largely unexplored. Based on a long-term study of the demography of a declining Eurasian Oystercatcher (Haematopus ostralegus) population, we quantify the effect of changes in mean and variance of winter temperature on different vital rates across the life cycle. Subsequently, we quantify, using stochastic stage-structured models, how changes in the mean and variance of this environmental variable affect important characteristics of the future population dynamics, such as the time to extinction. Local mean winter temperature is predicted to strongly increase, and we show that this is likely to increase the population's persistence time via its positive effects on adult survival that outweigh the negative effects that higher temperatures have on fecundity. Interannual variation in winter temperature is predicted to decrease, which is also likely to increase persistence time via its positive effects on adult survival that outweigh the negative effects that lower temperature variability has on fecundity. Overall, a 0.1 degrees C change in mean temperature is predicted to alter median time to extinction by 1.5 times as many years as would a 0.1 degrees C change in the standard deviation in temperature, suggesting that the dynamics of oystercatchers are more sensitive to changes in the mean than in the interannual variability of this climatic variable. Moreover, as climate models predict larger changes in the mean than in the standard deviation of local winter temperature, the effects of future climatic variability on this population's time to extinction are expected to be overwhelmed by the effects of changes in climatic means. We discuss the mechanisms by which climatic variability can either increase or decrease population viability and how this might depend both on species' life histories and on the vital rates affected. This study illustrates that, for making reliable inferences about population consequences in species in which life history changes with age or stage, it is crucial to investigate the impact of climate change on vital rates across the entire life cycle. Disturbingly, such data are unavailable for most species of conservation concern.

Life-history theory and climate change: resolving population and parental investment paradoxes.

PubMed

Caudell, Mark; Quinlan, Robert

2016-11-01

Population growth in the next half-century is on pace to raise global carbon emissions by half. Carbon emissions are associated with fertility as a by-product of somatic and parental investment, which is predicted to involve time orientation/preference as a mediating psychological mechanism. Here, we draw upon life-history theory (LHT) to investigate associations between future orientation and fertility, and their impacts on carbon emissions. We argue ' K -strategy' life history (LH) in high-income countries has resulted in parental investment behaviours involving future orientation that, paradoxically, promote unsustainable carbon emissions, thereby lowering the Earth's K or carrying capacity. Increasing the rate of approach towards this capacity are ' r -strategy' LHs in low-income countries that promote population growth. We explore interactions between future orientation and development that might slow the rate of approach towards global K . Examination of 67 000 individuals across 75 countries suggests that future orientation interacts with the relationship between environmental risk and fertility and with development related parental investment, particularly investment in higher education, to slow population growth and mitigate per capita carbon emissions. Results emphasize that LHT will be an important tool in understanding the demographic and consumption patterns that drive anthropogenic climate change.

U.S. population policy.

PubMed

Piotrow, P T

1993-06-01

Some of the history and special features of the US population assistance program administered by USAID are recounted. Future predictions are also made for funding and new directions for the US population assistance program and environmental issues. The topics addressed were part of a talk given in 1992 at a meeting of the Council on Population Education held in Tokyo. Credit is given to Japan for its contribution to family planning (FP) efforts by setting an example of reducing population size within a decade and providing financial support internationally. Japan's example so impressed General William H. Draper, Jr. that he worked for the establishment of the USAID and the UN Population Fund, and funding for the International Planned Parenthood Federation. He encouraged Japanese officials to provide support for international population and (FP) programs. Currently, the US provides $350 million in population assistance. Encouragement was given for Japan to increase its international commitment of $80 million and to contribute to the Johns Hopkins University William H. Draper, Jr., fellowship fund for graduate students from developing countries to study modern health communication. The special features of the US population assistance program were identified as follows: 1) high funding levels, 2) availability of FP services, 3) adequate contraceptive supplies, 4) availability of professional population staff, and 5) an emphasis on data and evaluation. The single most important element of the USAID program is the reliance on private, nongovernmental organizations (NGOs), which can establish flexible, independent, innovative and cost- effective programs. Predictions for the future were that the US Congress would expand overseas population assistance. Domestic policy will have priority, and the future will depend on who occupies the key policy positions at the State Department and USAID. THere will be more emphasis on free political elections, on humanitarian issues, and on environmental issues. New directions will be to increase funding, reduce restrictions on population assistance, increase support for NGOs, expand FP communication programs, improve the quality of FP services, increase distribution of condoms, and increase coordination among donors. The enter educate approach to promoting FP is described.

Measurement of Physical Activity and Energy Expenditure in Wheelchair Users: Methods, Considerations and Future Directions.

PubMed

Nightingale, Tom E; Rouse, Peter C; Thompson, Dylan; Bilzon, James L J

2017-12-01

Accurately measuring physical activity and energy expenditure in persons with chronic physical disabilities who use wheelchairs is a considerable and ongoing challenge. Quantifying various free-living lifestyle behaviours in this group is at present restricted by our understanding of appropriate measurement tools and analytical techniques. This review provides a detailed evaluation of the currently available measurement tools used to predict physical activity and energy expenditure in persons who use wheelchairs. It also outlines numerous considerations specific to this population and suggests suitable future directions for the field. Of the existing three self-report methods utilised in this population, the 3-day Physical Activity Recall Assessment for People with Spinal Cord Injury (PARA-SCI) telephone interview demonstrates the best reliability and validity. However, the complexity of interview administration and potential for recall bias are notable limitations. Objective measurement tools, which overcome such considerations, have been validated using controlled laboratory protocols. These have consistently demonstrated the arm or wrist as the most suitable anatomical location to wear accelerometers. Yet, more complex data analysis methodologies may be necessary to further improve energy expenditure prediction for more intricate movements or behaviours. Multi-sensor devices that incorporate physiological signals and acceleration have recently been adapted for persons who use wheelchairs. Population specific algorithms offer considerable improvements in energy expenditure prediction accuracy. This review highlights the progress in the field and aims to encourage the wider scientific community to develop innovative solutions to accurately quantify physical activity in this population.

Predicting debris

NASA Technical Reports Server (NTRS)

Kessler, Donald J.

1988-01-01

The probable amount, sizes, and relative velocities of debris are discussed, giving examples of the damage caused by debris, and focusing on the use of mathematical models to forecast the debris environment and solar activity now and in the future. Most debris are within 2,000 km of the earth's surface. The average velocity of spacecraft-debris collisions varies from 9 km/sec at 30 degrees of inclination to 13 km/sec near polar orbits. Mathematical models predict a 5 percent per year increase in the large-fragment population, producing a small-fragment population increase of 10 percent per year until the year 2060, the time of critical density. A 10 percent increase in the large population would cause the critical density to be reached around 2025.

Habitat availability and gene flow influence diverging local population trajectories under scenarios of climate change: a place-based approach.

PubMed

Schwalm, Donelle; Epps, Clinton W; Rodhouse, Thomas J; Monahan, William B; Castillo, Jessica A; Ray, Chris; Jeffress, Mackenzie R

2016-04-01

Ecological niche theory holds that species distributions are shaped by a large and complex suite of interacting factors. Species distribution models (SDMs) are increasingly used to describe species' niches and predict the effects of future environmental change, including climate change. Currently, SDMs often fail to capture the complexity of species' niches, resulting in predictions that are generally limited to climate-occupancy interactions. Here, we explore the potential impact of climate change on the American pika using a replicated place-based approach that incorporates climate, gene flow, habitat configuration, and microhabitat complexity into SDMs. Using contemporary presence-absence data from occupancy surveys, genetic data to infer connectivity between habitat patches, and 21 environmental niche variables, we built separate SDMs for pika populations inhabiting eight US National Park Service units representing the habitat and climatic breadth of the species across the western United States. We then predicted occurrence probability under current (1981-2010) and three future time periods (out to 2100). Occurrence probabilities and the relative importance of predictor variables varied widely among study areas, revealing important local-scale differences in the realized niche of the American pika. This variation resulted in diverse and - in some cases - highly divergent future potential occupancy patterns for pikas, ranging from complete extirpation in some study areas to stable occupancy patterns in others. Habitat composition and connectivity, which are rarely incorporated in SDM projections, were influential in predicting pika occupancy in all study areas and frequently outranked climate variables. Our findings illustrate the importance of a place-based approach to species distribution modeling that includes fine-scale factors when assessing current and future climate impacts on species' distributions, especially when predictions are intended to manage and conserve species of concern within individual protected areas. © 2015 John Wiley & Sons Ltd.

Past and ongoing shifts in Joshua tree distribution support future modeled range contraction

USGS Publications Warehouse

Cole, Kenneth L.; Ironside, Kirsten; Eischeid, Jon K.; Garfin, Gregg; Duffy, Phil; Toney, Chris

2011-01-01

The future distribution of the Joshua tree (Yucca brevifolia) is projected by combining a geostatistical analysis of 20th-century climates over its current range, future modeled climates, and paleoecological data showing its response to a past similar climate change. As climate rapidly warmed ;11 700 years ago, the range of Joshua tree contracted, leaving only the populations near what had been its northernmost limit. Its ability to spread northward into new suitable habitats after this time may have been inhibited by the somewhat earlier extinction of megafaunal dispersers, especially the Shasta ground sloth. We applied a model of climate suitability for Joshua tree, developed from its 20th-century range and climates, to future climates modeled through a set of six individual general circulation models (GCM) and one suite of 22 models for the late 21st century. All distribution data, observed climate data, and future GCM results were scaled to spatial grids of ;1 km and ;4 km in order to facilitate application within this topographically complex region. All of the models project the future elimination of Joshua tree throughout most of the southern portions of its current range. Although estimates of future monthly precipitation differ between the models, these changes are outweighed by large increases in temperature common to all the models. Only a few populations within the current range are predicted to be sustainable. Several models project significant potential future expansion into new areas beyond the current range, but the species' Historical and current rates of dispersal would seem to prevent natural expansion into these new areas. Several areas are predicted to be potential sites for relocation/ assisted migration. This project demonstrates how information from paleoecology and modern ecology can be integrated in order to understand ongoing processes and future distributions.

Recent and projected future climatic suitability of North America for the Asian tiger mosquito Aedes albopictus.

PubMed

Ogden, Nicholas H; Milka, Radojević; Caminade, Cyril; Gachon, Philippe

2014-12-02

Since the 1980s, populations of the Asian tiger mosquito Aedes albopictus have become established in south-eastern, eastern and central United States, extending to approximately 40°N. Ae. albopictus is a vector of a wide range of human pathogens including dengue and chikungunya viruses, which are currently emerging in the Caribbean and Central America and posing a threat to North America. The risk of Ae. albopictus expanding its geographic range in North America under current and future climate was assessed using three climatic indicators of Ae. albopictus survival: overwintering conditions (OW), OW combined with annual air temperature (OWAT), and a linear index of precipitation and air temperature suitability expressed through a sigmoidal function (SIG). The capacity of these indicators to predict Ae. albopictus occurrence was evaluated using surveillance data from the United States. Projected future climatic suitability for Ae. albopictus was obtained using output of nine Regional Climate Model experiments (RCMs). OW and OWAT showed >90% specificity and sensitivity in predicting observed Ae. albopictus occurrence and also predicted moderate to high risk of Ae. albopictus invasion in Pacific coastal areas of the Unites States and Canada under current climate. SIG also well predicted observed Ae. albopictus occurrence (ROC area under the curve was 0.92) but predicted wider current climatic suitability in the north-central and north-eastern United States and south-eastern Canada. RCM output projected modest (circa 500 km) future northward range expansion of Ae. albopictus by the 2050s when using OW and OWAT indicators, but greater (600-1000 km) range expansion, particularly in eastern and central Canada, when using the SIG indicator. Variation in future possible distributions of Ae. albopictus was greater amongst the climatic indicators used than amongst the RCM experiments. Current Ae. albopictus distributions were well predicted by simple climatic indicators and northward range expansion was predicted for the future with climate change. However, current and future predicted geographic distributions of Ae. albopictus varied amongst the climatic indicators used. Further field studies are needed to assess which climatic indicator is the most accurate in predicting regions suitable for Ae. albopictus survival in North America.

Longitudinal histories as predictors of future diagnoses of domestic abuse: modelling study

PubMed Central

Kohane, Isaac S; Mandl, Kenneth D

2009-01-01

Objective To determine whether longitudinal data in patients’ historical records, commonly available in electronic health record systems, can be used to predict a patient’s future risk of receiving a diagnosis of domestic abuse. Design Bayesian models, known as intelligent histories, used to predict a patient’s risk of receiving a future diagnosis of abuse, based on the patient’s diagnostic history. Retrospective evaluation of the model’s predictions using an independent testing set. Setting A state-wide claims database covering six years of inpatient admissions to hospital, admissions for observation, and encounters in emergency departments. Population All patients aged over 18 who had at least four years between their earliest and latest visits recorded in the database (561 216 patients). Main outcome measures Timeliness of detection, sensitivity, specificity, positive predictive values, and area under the ROC curve. Results 1.04% (5829) of the patients met the narrow case definition for abuse, while 3.44% (19 303) met the broader case definition for abuse. The model achieved sensitive, specific (area under the ROC curve of 0.88), and early (10-30 months in advance, on average) prediction of patients’ future risk of receiving a diagnosis of abuse. Analysis of model parameters showed important differences between sexes in the risks associated with certain diagnoses. Conclusions Commonly available longitudinal diagnostic data can be useful for predicting a patient’s future risk of receiving a diagnosis of abuse. This modelling approach could serve as the basis for an early warning system to help doctors identify high risk patients for further screening. PMID:19789406

Effects of Climate Change and Fisheries Bycatch on Shy Albatross (Thalassarche cauta) in Southern Australia

PubMed Central

2015-01-01

The impacts of climate change on marine species are often compounded by other stressors that make direct attribution and prediction difficult. Shy albatrosses (Thalassarche cauta) breeding on Albatross Island, Tasmania, show an unusually restricted foraging range, allowing easier discrimination between the influence of non-climate stressors (fisheries bycatch) and environmental variation. Local environmental conditions (rainfall, air temperature, and sea-surface height, an indicator of upwelling) during the vulnerable chick-rearing stage, have been correlated with breeding success of shy albatrosses. We use an age-, stage- and sex-structured population model to explore potential relationships between local environmental factors and albatross breeding success while accounting for fisheries bycatch by trawl and longline fisheries. The model uses time-series of observed breeding population counts, breeding success, adult and juvenile survival rates and a bycatch mortality observation for trawl fishing to estimate fisheries catchability, environmental influence, natural mortality rate, density dependence, and productivity. Observed at-sea distributions for adult and juvenile birds were coupled with reported fishing effort to estimate vulnerability to incidental bycatch. The inclusion of rainfall, temperature and sea-surface height as explanatory variables for annual chick mortality rate was statistically significant. Global climate models predict little change in future local average rainfall, however, increases are forecast in both temperatures and upwelling, which are predicted to have detrimental and beneficial effects, respectively, on breeding success. The model shows that mitigation of at least 50% of present bycatch is required to offset losses due to future temperature changes, even if upwelling increases substantially. Our results highlight the benefits of using an integrated modeling approach, which uses available demographic as well as environmental data within a single estimation framework, to provide future predictions. Such predictions inform the development of management options in the face of climate change. PMID:26057739

Effects of Climate Change and Fisheries Bycatch on Shy Albatross (Thalassarche cauta) in Southern Australia.

PubMed

Thomson, Robin B; Alderman, Rachael L; Tuck, Geoffrey N; Hobday, Alistair J

2015-01-01

The impacts of climate change on marine species are often compounded by other stressors that make direct attribution and prediction difficult. Shy albatrosses (Thalassarche cauta) breeding on Albatross Island, Tasmania, show an unusually restricted foraging range, allowing easier discrimination between the influence of non-climate stressors (fisheries bycatch) and environmental variation. Local environmental conditions (rainfall, air temperature, and sea-surface height, an indicator of upwelling) during the vulnerable chick-rearing stage, have been correlated with breeding success of shy albatrosses. We use an age-, stage- and sex-structured population model to explore potential relationships between local environmental factors and albatross breeding success while accounting for fisheries bycatch by trawl and longline fisheries. The model uses time-series of observed breeding population counts, breeding success, adult and juvenile survival rates and a bycatch mortality observation for trawl fishing to estimate fisheries catchability, environmental influence, natural mortality rate, density dependence, and productivity. Observed at-sea distributions for adult and juvenile birds were coupled with reported fishing effort to estimate vulnerability to incidental bycatch. The inclusion of rainfall, temperature and sea-surface height as explanatory variables for annual chick mortality rate was statistically significant. Global climate models predict little change in future local average rainfall, however, increases are forecast in both temperatures and upwelling, which are predicted to have detrimental and beneficial effects, respectively, on breeding success. The model shows that mitigation of at least 50% of present bycatch is required to offset losses due to future temperature changes, even if upwelling increases substantially. Our results highlight the benefits of using an integrated modeling approach, which uses available demographic as well as environmental data within a single estimation framework, to provide future predictions. Such predictions inform the development of management options in the face of climate change.

Eurabia: Strategic Implications for the United States

DTIC Science & Technology

2010-03-01

display a currently valid OMB control number. 1. REPORT DATE 30 MAR 2010 2. REPORT TYPE 3. DATES COVERED 4. TITLE AND SUBTITLE Eurabia: Strategic...projecting current trends into the future seldom holds true in the face of demographic realities, i.e. nature gets a vote so to speak. These social welfare...portion of the population. Nevertheless, current predictions have it rising dramatically over the coming decades. Most demographers predict that by

Current demographics suggest future energy supplies will be inadequate to slow human population growth.

PubMed

DeLong, John P; Burger, Oskar; Hamilton, Marcus J

2010-10-05

Influential demographic projections suggest that the global human population will stabilize at about 9-10 billion people by mid-century. These projections rest on two fundamental assumptions. The first is that the energy needed to fuel development and the associated decline in fertility will keep pace with energy demand far into the future. The second is that the demographic transition is irreversible such that once countries start down the path to lower fertility they cannot reverse to higher fertility. Both of these assumptions are problematic and may have an effect on population projections. Here we examine these assumptions explicitly. Specifically, given the theoretical and empirical relation between energy-use and population growth rates, we ask how the availability of energy is likely to affect population growth through 2050. Using a cross-country data set, we show that human population growth rates are negatively related to per-capita energy consumption, with zero growth occurring at ∼13 kW, suggesting that the global human population will stop growing only if individuals have access to this amount of power. Further, we find that current projected future energy supply rates are far below the supply needed to fuel a global demographic transition to zero growth, suggesting that the predicted leveling-off of the global population by mid-century is unlikely to occur, in the absence of a transition to an alternative energy source. Direct consideration of the energetic constraints underlying the demographic transition results in a qualitatively different population projection than produced when the energetic constraints are ignored. We suggest that energetic constraints be incorporated into future population projections.

Isohaline position as a habitat indicator for estuarine populations

USGS Publications Warehouse

Jassby, Alan D.; Kimmerer, W.J.; Monismith, Stephen G.; Armor, C.; Cloern, James E.; Powell, T.M.; Vedlinski, Timothy J.

1995-01-01

The striped bass survival data were also used to illustrate a related important point: incorporating additionalexplanatory variables may decrease the prediction error for a population or process, but it can increase theuncertainty in parameter estimates and management strategies based on these estimates. Even in cases wherethe uncertainty is currently too large to guide management decisions, an uncertainty analysis can identify themost practical direction for future data acquisition.

Clinical application of the Melbourne risk prediction tool in a high-risk upper abdominal surgical population: an observational cohort study.

PubMed

Parry, S; Denehy, L; Berney, S; Browning, L

2014-03-01

(1) To determine the ability of the Melbourne risk prediction tool to predict a pulmonary complication as defined by the Melbourne Group Scale in a medically defined high-risk upper abdominal surgery population during the postoperative period; (2) to identify the incidence of postoperative pulmonary complications; and (3) to examine the risk factors for postoperative pulmonary complications in this high-risk population. Observational cohort study. Tertiary Australian referral centre. 50 individuals who underwent medically defined high-risk upper abdominal surgery. Presence of postoperative pulmonary complications was screened daily for seven days using the Melbourne Group Scale (Version 2). Postoperative pulmonary risk prediction was calculated according to the Melbourne risk prediction tool. (1) Melbourne risk prediction tool; and (2) the incidence of postoperative pulmonary complications. Sixty-six percent (33/50) underwent hepatobiliary or upper gastrointestinal surgery. Mean (SD) anaesthetic duration was 377.8 (165.5) minutes. The risk prediction tool classified 84% (42/50) as high risk. Overall postoperative pulmonary complication incidence was 42% (21/50). The tool was 91% sensitive and 21% specific with a 50% chance of correct classification. This is the first study to externally validate the Melbourne risk prediction tool in an independent medically defined high-risk population. There was a higher incidence of pulmonary complications postoperatively observed compared to that previously reported. Results demonstrated poor validity of the tool in a population already defined medically as high risk and when applied postoperatively. This observational study has identified several important points to consider in future trials. Copyright © 2013 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

Climate change can alter predator-prey dynamics and population viability of prey.

PubMed

Bastille-Rousseau, Guillaume; Schaefer, James A; Peers, Michael J L; Ellington, E Hance; Mumma, Matthew A; Rayl, Nathaniel D; Mahoney, Shane P; Murray, Dennis L

2018-01-01

For many organisms, climate change can directly drive population declines, but it is less clear how such variation may influence populations indirectly through modified biotic interactions. For instance, how will climate change alter complex, multi-species relationships that are modulated by climatic variation and that underlie ecosystem-level processes? Caribou (Rangifer tarandus), a keystone species in Newfoundland, Canada, provides a useful model for unravelling potential and complex long-term implications of climate change on biotic interactions and population change. We measured cause-specific caribou calf predation (1990-2013) in Newfoundland relative to seasonal weather patterns. We show that black bear (Ursus americanus) predation is facilitated by time-lagged higher summer growing degree days, whereas coyote (Canis latrans) predation increases with current precipitation and winter temperature. Based on future climate forecasts for the region, we illustrate that, through time, coyote predation on caribou calves could become increasingly important, whereas the influence of black bear would remain unchanged. From these predictions, demographic projections for caribou suggest long-term population limitation specifically through indirect effects of climate change on calf predation rates by coyotes. While our work assumes limited impact of climate change on other processes, it illustrates the range of impact that climate change can have on predator-prey interactions. We conclude that future efforts to predict potential effects of climate change on populations and ecosystems should include assessment of both direct and indirect effects, including climate-predator interactions.

The past, present, and future of cancer incidence in the United States: 1975 through 2020.

PubMed

Weir, Hannah K; Thompson, Trevor D; Soman, Ashwini; Møller, Bjørn; Leadbetter, Steven

2015-06-01

The overall age-standardized cancer incidence rate continues to decline whereas the number of cases diagnosed each year increases. Predicting cancer incidence can help to anticipate future resource needs, evaluate primary prevention strategies, and inform research. Surveillance, Epidemiology, and End Results data were used to estimate the number of cancers (all sites) resulting from changes in population risk, age, and size. The authors projected to 2020 nationwide age-standardized incidence rates and cases (including the top 23 cancers). Since 1975, incident cases increased among white individuals, primarily caused by an aging white population, and among black individuals, primarily caused by an increasing black population. Between 2010 and 2020, it is expected that overall incidence rates (proxy for risk) will decrease slightly among black men and stabilize in other groups. By 2020, the authors predict annual cancer cases (all races, all sites) to increase among men by 24.1% (-3.2% risk and 27.3% age/growth) to >1 million cases, and by 20.6% among women (1.2% risk and 19.4% age/growth) to >900,000 cases. The largest increases are expected for melanoma (white individuals); cancers of the prostate, kidney, liver, and urinary bladder in males; and the lung, breast, uterus, and thyroid in females. Overall, the authors predict cancer incidence rates/risk to stabilize for the majority of the population; however, they expect the number of cancer cases to increase by >20%. A greater emphasis on primary prevention and early detection is needed to counter the effect of an aging and growing population on the burden of cancer. © 2015 American Cancer Society.

The Past, Present, and Future of Cancer Incidence in the United States: 1975 Through 2020

PubMed Central

Weir, Hannah K.; Thompson, Trevor D.; Soman, Ashwini; Møller, Bjørn; Leadbetter, Steven

2015-01-01

BACKGROUND The overall age-standardized cancer incidence rate continues to decline whereas the number of cases diagnosed each year increases. Predicting cancer incidence can help to anticipate future resource needs, evaluate primary prevention strategies, and inform research. METHODS Surveillance, Epidemiology, and End Results data were used to estimate the number of cancers (all sites) resulting from changes in population risk, age, and size. The authors projected to 2020 nationwide age-standardized incidence rates and cases (including the top 23 cancers). RESULTS Since 1975, incident cases increased among white individuals, primarily caused by an aging white population, and among black individuals, primarily caused by an increasing black population. Between 2010 and 2020, it is expected that overall incidence rates (proxy for risk) will decrease slightly among black men and stabilize in other groups. By 2020, the authors predict annual cancer cases (all races, all sites) to increase among men by 24.1% (−3.2% risk and 27.3% age/growth) to >1 million cases, and by 20.6% among women (1.2% risk and 19.4% age/growth) to >900,000 cases. The largest increases are expected for melanoma (white individuals); cancers of the prostate, kidney, liver, and urinary bladder in males; and the lung, breast, uterus, and thyroid in females. CONCLUSIONS Overall, the authors predict cancer incidence rates/risk to stabilize for the majority of the population; however, they expect the number of cancer cases to increase by >20%. A greater emphasis on primary prevention and early detection is needed to counter the effect of an aging and growing population on the burden of cancer. PMID:25649671

Shifting species interactions in terrestrial dryland ecosystems under altered water availability and climate change

USGS Publications Warehouse

McCluney, Kevin E.; Belnap, Jayne; Collins, Scott L.; González, Angélica L.; Hagen, Elizabeth M.; Holland, J. Nathaniel; Kotler, Burt P.; Maestre, Fernando T.; Smith, Stanley D.; Wolf, Blair O.

2012-01-01

Species interactions play key roles in linking the responses of populations, communities, and ecosystems to environmental change. For instance, species interactions are an important determinant of the complexity of changes in trophic biomass with variation in resources. Water resources are a major driver of terrestrial ecology and climate change is expected to greatly alter the distribution of this critical resource. While previous studies have documented strong effects of global environmental change on species interactions in general, responses can vary from region to region. Dryland ecosystems occupy more than one-third of the Earth's land mass, are greatly affected by changes in water availability, and are predicted to be hotspots of climate change. Thus, it is imperative to understand the effects of environmental change on these globally significant ecosystems. Here, we review studies of the responses of population-level plant-plant, plant-herbivore, and predator-prey interactions to changes in water availability in dryland environments in order to develop new hypotheses and predictions to guide future research. To help explain patterns of interaction outcomes, we developed a conceptual model that views interaction outcomes as shifting between (1) competition and facilitation (plant-plant), (2) herbivory, neutralism, or mutualism (plant-herbivore), or (3) neutralism and predation (predator-prey), as water availability crosses physiological, behavioural, or population-density thresholds. We link our conceptual model to hypothetical scenarios of current and future water availability to make testable predictions about the influence of changes in water availability on species interactions. We also examine potential implications of our conceptual model for the relative importance of top-down effects and the linearity of patterns of change in trophic biomass with changes in water availability. Finally, we highlight key research needs and some possible broader impacts of our findings. Overall, we hope to stimulate and guide future research that links changes in water availability to patterns of species interactions and the dynamics of populations and communities in dryland ecosystems.

Projections of Water Stress Based on an Ensemble of Socioeconomic Growth and Climate Change Scenarios: A Case Study in Asia.

PubMed

Fant, Charles; Schlosser, C Adam; Gao, Xiang; Strzepek, Kenneth; Reilly, John

2016-01-01

The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios--internally consistent across economics, emissions, climate, and population--to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify the primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region's population will live in water-stressed regions in the near future. Tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers.

Current & future vulnerability of sarasota county Florida to hurricane storm surge & sea level rise

USGS Publications Warehouse

Frazier, T.; Wood, N.; Yarnal, B.

2008-01-01

Coastal communities in portions of the United States are vulnerable to storm-surge inundation from hurricanes and this vulnerability will likely increase, given predicted rises in sea level from climate change and growing coastal development. In this paper, we provide an overview of research to determine current and future societal vulnerability to hurricane storm-surge inundation and to help public officials and planners integrate these scenarios into their long-range land use plans. Our case study is Sarasota County, Florida, where planners face the challenge of balancing increasing population growth and development with the desire to lower vulnerability to storm surge. Initial results indicate that a large proportion of Sarasota County's residential and employee populations are in areas prone to storm-surge inundation from a Category 5 hurricane. This hazard zone increases when accounting for potential sea-level-rise scenarios, thereby putting additional populations at risk. Subsequent project phases involve the development of future land use and vulnerability scenarios in collaboration with local officials. Copyright ASCE 2008.

HSV-2 serology can be predictive of HIV epidemic potential and hidden sexual-risk behavior in the Middle East and North Africa

PubMed Central

Abu-Raddad, Laith J.; Schiffer, Joshua T.; Ashley, Rhoda; Mumtaz, Ghina; Alsallaq, Ramzi A.; Akala, Francisca Ayodeji; Semini, Iris; Riedner, Gabriele; Wilson, David

2013-01-01

Background HIV prevalence is low in the Middle East and North Africa (MENA) region, though the risk or potential for further spread in the future is not well understood. Behavioral surveys are limited in this region and when available have serious limitations in assessing the risk of HIV acquisition. We demonstrate the potential use of herpes simplex virus-2 (HSV-2) seroprevalence as a marker for HIV risk within MENA. Methods We designed a mathematical model to assess whether HSV-2 prevalence can be predictive of future HIV spread. We also conducted a systematic literature review of HSV-2 seroprevalence studies within MENA. Results We found that HSV-2 prevalence data are rather limited in this region. Prevalence is typically low among the general population but high in established core groups prone to sexually transmitted infections such as men who have sex with men and female sex workers. Our model predicts that if HSV-2 prevalence is low and stable, then the risk of future HIV epidemics is low. However, expanding or high HSV-2 prevalence (greater than about 20%), implies a risk for a considerable HIV epidemic. Based on available HSV-2 prevalence data, it is not likely that the general population in MENA is experiencing or will experience such a considerable HIV epidemic. Nevertheless, the risk for concentrated HIV epidemics among several high-risk core groups is high. Conclusions HSV-2 prevalence surveys provide a useful mechanism for identifying and corroborating populations at risk for HIV within MENA. HSV-2 serology offers an effective tool for probing hidden risk behaviors in a region where quality behavioral data are limited. PMID:21352788

New evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs

PubMed Central

Beckman, Robert A.; Chen, Cong

2013-01-01

Predictive biomarkers are important to the future of oncology; they can be used to identify patient populations who will benefit from therapy, increase the value of cancer medicines, and decrease the size and cost of clinical trials while increasing their chance of success. But predictive biomarkers do not always work. When unsuccessful, they add cost, complexity, and time to drug development. This perspective describes phases 2 and 3 development methods that efficiently and adaptively check the ability of a biomarker to predict clinical outcomes. In the end, the biomarker is emphasized to the extent that it can actually predict. PMID:23489587

Prediction, dynamics, and visualization of antigenic phenotypes of seasonal influenza viruses

PubMed Central

Neher, Richard A.; Bedford, Trevor; Daniels, Rodney S.; Shraiman, Boris I.

2016-01-01

Human seasonal influenza viruses evolve rapidly, enabling the virus population to evade immunity and reinfect previously infected individuals. Antigenic properties are largely determined by the surface glycoprotein hemagglutinin (HA), and amino acid substitutions at exposed epitope sites in HA mediate loss of recognition by antibodies. Here, we show that antigenic differences measured through serological assay data are well described by a sum of antigenic changes along the path connecting viruses in a phylogenetic tree. This mapping onto the tree allows prediction of antigenicity from HA sequence data alone. The mapping can further be used to make predictions about the makeup of the future A(H3N2) seasonal influenza virus population, and we compare predictions between models with serological and sequence data. To make timely model output readily available, we developed a web browser-based application that visualizes antigenic data on a continuously updated phylogeny. PMID:26951657

Land-cover changes predict steep declines for the Sumatran orangutan (Pongo abelii)

PubMed Central

Wich, Serge A.; Singleton, Ian; Nowak, Matthew G.; Utami Atmoko, Sri Suci; Nisam, Gonda; Arif, Sugesti Mhd.; Putra, Rudi H.; Ardi, Rio; Fredriksson, Gabriella; Usher, Graham; Gaveau, David L. A.; Kühl, Hjalmar S.

2016-01-01

Positive news about Sumatran orangutans is rare. The species is critically endangered because of forest loss and poaching, and therefore, determining the impact of future land-use change on this species is important. To date, the total Sumatran orangutan population has been estimated at 6600 individuals. On the basis of new transect surveys, we estimate a population of 14,613 in 2015. This higher estimate is due to three factors. First, orangutans were found at higher elevations, elevations previously considered outside of their range and, consequently, not surveyed previously. Second, orangutans were found more widely distributed in logged forests. Third, orangutans were found in areas west of the Toba Lake that were not previously surveyed. This increase in numbers is therefore due to a more wide-ranging survey effort and is not indicative of an increase in the orangutan population in Sumatra. There are evidently more Sumatran orangutans remaining in the wild than we thought, but the species remains under serious threat. Current scenarios for future forest loss predict that as many as 4500 individuals could vanish by 2030. Despite the positive finding that the population is double the size previously estimated, our results indicate that future deforestation will continue to be the cause of rapid declines in orangutan numbers. Hence, we urge that all developmental planning involving forest loss be accompanied by appropriate environmental impact assessments conforming with the current national and provincial legislations, and, through these, implement specific measures to reduce or, better, avoid negative impacts on forests where orangutans occur. PMID:26973868

Land-cover changes predict steep declines for the Sumatran orangutan (Pongo abelii).

PubMed

Wich, Serge A; Singleton, Ian; Nowak, Matthew G; Utami Atmoko, Sri Suci; Nisam, Gonda; Arif, Sugesti Mhd; Putra, Rudi H; Ardi, Rio; Fredriksson, Gabriella; Usher, Graham; Gaveau, David L A; Kühl, Hjalmar S

2016-03-01

Positive news about Sumatran orangutans is rare. The species is critically endangered because of forest loss and poaching, and therefore, determining the impact of future land-use change on this species is important. To date, the total Sumatran orangutan population has been estimated at 6600 individuals. On the basis of new transect surveys, we estimate a population of 14,613 in 2015. This higher estimate is due to three factors. First, orangutans were found at higher elevations, elevations previously considered outside of their range and, consequently, not surveyed previously. Second, orangutans were found more widely distributed in logged forests. Third, orangutans were found in areas west of the Toba Lake that were not previously surveyed. This increase in numbers is therefore due to a more wide-ranging survey effort and is not indicative of an increase in the orangutan population in Sumatra. There are evidently more Sumatran orangutans remaining in the wild than we thought, but the species remains under serious threat. Current scenarios for future forest loss predict that as many as 4500 individuals could vanish by 2030. Despite the positive finding that the population is double the size previously estimated, our results indicate that future deforestation will continue to be the cause of rapid declines in orangutan numbers. Hence, we urge that all developmental planning involving forest loss be accompanied by appropriate environmental impact assessments conforming with the current national and provincial legislations, and, through these, implement specific measures to reduce or, better, avoid negative impacts on forests where orangutans occur.

Identifying Future Drinkers: Behavioral Analysis of Monkeys Initiating Drinking to Intoxication is Predictive of Future Drinking Classification.

PubMed

Baker, Erich J; Walter, Nicole A R; Salo, Alex; Rivas Perea, Pablo; Moore, Sharon; Gonzales, Steven; Grant, Kathleen A

2017-03-01

The Monkey Alcohol Tissue Research Resource (MATRR) is a repository and analytics platform for detailed data derived from well-documented nonhuman primate (NHP) alcohol self-administration studies. This macaque model has demonstrated categorical drinking norms reflective of human drinking populations, resulting in consumption pattern classifications of very heavy drinking (VHD), heavy drinking (HD), binge drinking (BD), and low drinking (LD) individuals. Here, we expand on previous findings that suggest ethanol drinking patterns during initial drinking to intoxication can reliably predict future drinking category assignment. The classification strategy uses a machine-learning approach to examine an extensive set of daily drinking attributes during 90 sessions of induction across 7 cohorts of 5 to 8 monkeys for a total of 50 animals. A Random Forest classifier is employed to accurately predict categorical drinking after 12 months of self-administration. Predictive outcome accuracy is approximately 78% when classes are aggregated into 2 groups, "LD and BD" and "HD and VHD." A subsequent 2-step classification model distinguishes individual LD and BD categories with 90% accuracy and between HD and VHD categories with 95% accuracy. Average 4-category classification accuracy is 74%, and provides putative distinguishing behavioral characteristics between groupings. We demonstrate that data derived from the induction phase of this ethanol self-administration protocol have significant predictive power for future ethanol consumption patterns. Importantly, numerous predictive factors are longitudinal, measuring the change of drinking patterns through 3 stages of induction. Factors during induction that predict future heavy drinkers include being younger at the time of first intoxication and developing a shorter latency to first ethanol drink. Overall, this analysis identifies predictive characteristics in future very heavy drinkers that optimize intoxication, such as having increasingly fewer bouts with more drinks. This analysis also identifies characteristic avoidance of intoxicating topographies in future low drinkers, such as increasing number of bouts and waiting longer before the first ethanol drink. Copyright © 2017 The Authors Alcoholism: Clinical & Experimental Research published by Wiley Periodicals, Inc. on behalf of Research Society on Alcoholism.

Decoding the future from past experience: learning shapes predictions in early visual cortex.

PubMed

Luft, Caroline D B; Meeson, Alan; Welchman, Andrew E; Kourtzi, Zoe

2015-05-01

Learning the structure of the environment is critical for interpreting the current scene and predicting upcoming events. However, the brain mechanisms that support our ability to translate knowledge about scene statistics to sensory predictions remain largely unknown. Here we provide evidence that learning of temporal regularities shapes representations in early visual cortex that relate to our ability to predict sensory events. We tested the participants' ability to predict the orientation of a test stimulus after exposure to sequences of leftward- or rightward-oriented gratings. Using fMRI decoding, we identified brain patterns related to the observers' visual predictions rather than stimulus-driven activity. Decoding of predicted orientations following structured sequences was enhanced after training, while decoding of cued orientations following exposure to random sequences did not change. These predictive representations appear to be driven by the same large-scale neural populations that encode actual stimulus orientation and to be specific to the learned sequence structure. Thus our findings provide evidence that learning temporal structures supports our ability to predict future events by reactivating selective sensory representations as early as in primary visual cortex. Copyright © 2015 the American Physiological Society.

Life-history theory and climate change: resolving population and parental investment paradoxes

PubMed Central

Quinlan, Robert

2016-01-01

Population growth in the next half-century is on pace to raise global carbon emissions by half. Carbon emissions are associated with fertility as a by-product of somatic and parental investment, which is predicted to involve time orientation/preference as a mediating psychological mechanism. Here, we draw upon life-history theory (LHT) to investigate associations between future orientation and fertility, and their impacts on carbon emissions. We argue ‘K-strategy’ life history (LH) in high-income countries has resulted in parental investment behaviours involving future orientation that, paradoxically, promote unsustainable carbon emissions, thereby lowering the Earth's K or carrying capacity. Increasing the rate of approach towards this capacity are ‘r-strategy’ LHs in low-income countries that promote population growth. We explore interactions between future orientation and development that might slow the rate of approach towards global K. Examination of 67 000 individuals across 75 countries suggests that future orientation interacts with the relationship between environmental risk and fertility and with development related parental investment, particularly investment in higher education, to slow population growth and mitigate per capita carbon emissions. Results emphasize that LHT will be an important tool in understanding the demographic and consumption patterns that drive anthropogenic climate change. PMID:28018631

The Second Century: Our Vision for the Future.

ERIC Educational Resources Information Center

Dickman, Donna M.; Levinson, Ken

1990-01-01

This paper speculates on the coming century's opportunities and challenges for the Alexander Graham Bell Association. Medical advancements prolonging life and the subsequent increase in the elderly population are discussed, as are computer and telecommunications advances. Futurists' predictions of increasing disposable income and social conscience…

Feasibility of Forecasting Highway Safety in Support of Safety Incentive and Safety Target Programs.

DOT National Transportation Integrated Search

2007-11-01

Using the frequency of fatal crashes from the current observation period (e.g. month, year, etc.) as the : prediction of expected future performance does not account for changes in safety that result from : increases in exposure (population, addition...

Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population.

PubMed

Alimi, Temitope O; Fuller, Douglas O; Qualls, Whitney A; Herrera, Socrates V; Arevalo-Herrera, Myriam; Quinones, Martha L; Lacerda, Marcus V G; Beier, John C

2015-08-20

Changes in land use and land cover (LULC) as well as climate are likely to affect the geographic distribution of malaria vectors and parasites in the coming decades. At present, malaria transmission is concentrated mainly in the Amazon basin where extensive agriculture, mining, and logging activities have resulted in changes to local and regional hydrology, massive loss of forest cover, and increased contact between malaria vectors and hosts. Employing presence-only records, bioclimatic, topographic, hydrologic, LULC and human population data, we modeled the distribution of malaria and two of its dominant vectors, Anopheles darlingi, and Anopheles nuneztovari s.l. in northern South America using the species distribution modeling platform Maxent. Results from our land change modeling indicate that about 70,000 km(2) of forest land would be lost by 2050 and 78,000 km(2) by 2070 compared to 2010. The Maxent model predicted zones of relatively high habitat suitability for malaria and the vectors mainly within the Amazon and along coastlines. While areas with malaria are expected to decrease in line with current downward trends, both vectors are predicted to experience range expansions in the future. Elevation, annual precipitation and temperature were influential in all models both current and future. Human population mostly affected An. darlingi distribution while LULC changes influenced An. nuneztovari s.l. distribution. As the region tackles the challenge of malaria elimination, investigations such as this could be useful for planning and management purposes and aid in predicting and addressing potential impediments to elimination.

Collective behaviour, uncertainty and environmental change.

PubMed

Bentley, R Alexander; O'Brien, Michael J

2015-11-28

A central aspect of cultural evolutionary theory concerns how human groups respond to environmental change. Although we are painting with a broad brush, it is fair to say that prior to the twenty-first century, adaptation often happened gradually over multiple human generations, through a combination of individual and social learning, cumulative cultural evolution and demographic shifts. The result was a generally resilient and sustainable population. In the twenty-first century, however, considerable change happens within small portions of a human generation, on a vastly larger range of geographical and population scales and involving a greater degree of horizontal learning. As a way of gauging the complexity of societal response to environmental change in a globalized future, we discuss several theoretical tools for understanding how human groups adapt to uncertainty. We use our analysis to estimate the limits of predictability of future societal change, in the belief that knowing when to hedge bets is better than relying on a false sense of predictability. © 2015 The Author(s).

The Science-Policy Link: Stakeholder Reactions to the Uncertainties of Future Sea Level Rise

NASA Astrophysics Data System (ADS)

Plag, H.; Bye, B.

2011-12-01

Policy makers and stakeholders in the coastal zone are equally challenged by the risk of an anticipated rise of coastal Local Sea Level (LSL) as a consequence of future global warming. Many low-lying and often densely populated coastal areas are under risk of increased inundation. More than 40% of the global population is living in or near the coastal zone and this fraction is steadily increasing. A rise in LSL will increase the vulnerability of coastal infrastructure and population dramatically, with potentially devastating consequences for the global economy, society, and environment. Policy makers are faced with a trade-off between imposing today the often very high costs of coastal protection and adaptation upon national economies and leaving the costs of potential major disasters to future generations. They are in need of actionable information that provides guidance for the development of coastal zones resilient to future sea level changes. Part of this actionable information comes from risk and vulnerability assessments, which require information on future LSL changes as input. In most cases, a deterministic approach has been applied based on predictions of the plausible range of future LSL trajectories as input. However, there is little consensus in the scientific community on how these trajectories should be determined, and what the boundaries of the plausible range are. Over the last few years, many publications in Science, Nature and other peer-reviewed scientific journals have revealed a broad range of possible futures and significant epistemic uncertainties and gaps concerning LSL changes. Based on the somewhat diffuse science input, policy and decision makers have made rather different choices for mitigation and adaptation in cases such as Venice, The Netherlands, New York City, and the San Francisco Bay area. Replacing the deterministic, prediction-based approach with a statistical one that fully accounts for the uncertainties and epistemic gaps would provide a different kind of science input to policy makers and stakeholders. Like in many other insurance problems (for example, earthquakes), where deterministic predictions are not possible and decisions have to be made on the basis of statistics and probabilities, the statistical approach to coastal resilience would require stakeholders to make decisions on the basis of probabilities instead of predictions. The science input for informed decisions on adaptation would consist of general probabilities of decadal to century scale sea level changes derived from paleo records, including the probabilities for large and rapid rises. Similar to other problems where the appearance of a hazard is associated with a high risk (like a fire in a house), this approach would also require a monitoring and warning system (a "smoke detector") capable of detecting any onset of a rapid sea level rise.

Sex-specific lean body mass predictive equations are accurate in the obese paediatric population

PubMed Central

Jackson, Lanier B.; Henshaw, Melissa H.; Carter, Janet; Chowdhury, Shahryar M.

2015-01-01

Background The clinical assessment of lean body mass (LBM) is challenging in obese children. A sex-specific predictive equation for LBM derived from anthropometric data was recently validated in children. Aim The purpose of this study was to independently validate these predictive equations in the obese paediatric population. Subjects and methods Obese subjects aged 4–21 were analysed retrospectively. Predicted LBM (LBMp) was calculated using equations previously developed in children. Measured LBM (LBMm) was derived from dual-energy x-ray absorptiometry. Agreement was expressed as [(LBMm-LBMp)/LBMm] with 95% limits of agreement. Results Of 310 enrolled patients, 195 (63%) were females. The mean age was 11.8 ± 3.4 years and mean BMI Z-score was 2.3 ± 0.4. The average difference between LBMm and LBMp was −0.6% (−17.0%, 15.8%). Pearson’s correlation revealed a strong linear relationship between LBMm and LBMp (r=0.97, p<0.01). Conclusion This study validates the use of these clinically-derived sex-specific LBM predictive equations in the obese paediatric population. Future studies should use these equations to improve the ability to accurately classify LBM in obese children. PMID:26287383

Does Specification Matter? Experiments with Simple Multiregional Probabilistic Population Projections

PubMed Central

Raymer, James; Abel, Guy J.; Rogers, Andrei

2012-01-01

Population projection models that introduce uncertainty are a growing subset of projection models in general. In this paper, we focus on the importance of decisions made with regard to the model specifications adopted. We compare the forecasts and prediction intervals associated with four simple regional population projection models: an overall growth rate model, a component model with net migration, a component model with in-migration and out-migration rates, and a multiregional model with destination-specific out-migration rates. Vector autoregressive models are used to forecast future rates of growth, birth, death, net migration, in-migration and out-migration, and destination-specific out-migration for the North, Midlands and South regions in England. They are also used to forecast different international migration measures. The base data represent a time series of annual data provided by the Office for National Statistics from 1976 to 2008. The results illustrate how both the forecasted subpopulation totals and the corresponding prediction intervals differ for the multiregional model in comparison to other simpler models, as well as for different assumptions about international migration. The paper ends end with a discussion of our results and possible directions for future research. PMID:23236221

Forecasting climate change impacts on plant populations over large spatial extents

DOE PAGES

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; ...

2016-10-24

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less

Forecasting climate change impacts on plant populations over large spatial extents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less

Forecasting climate change impacts on plant populations over large spatial extents

USGS Publications Warehouse

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; Homer, Collin G.; Kleinhesselink, Andrew R.; Adler, Peter B.

2016-01-01

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. We overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.

An application of a zero-inflated lifetime distribution with multiple and incomplete data sources

DOE PAGES

Hamada, M. S.; Margevicius, K. J.

2016-02-11

In this study, we analyze data sampled from a population of parts in which an associated anomaly can occur at assembly or after assembly. Using a zero-inflated lifetime distribution to fit left-censored and right-censored data as well data from a supplementary sample, we make predictions about the proportion of the population with anomalies today and in the future. Goodness-of-fit is also addressed.

Tolerance and potential for adaptation of a Baltic Sea rockweed under predicted climate change conditions.

PubMed

Rugiu, Luca; Manninen, Iita; Rothäusler, Eva; Jormalainen, Veijo

2018-03-01

Climate change is threating species' persistence worldwide. To predict species responses to climate change we need information not just on their environmental tolerance but also on its adaptive potential. We tested how the foundation species of rocky littoral habitats, Fucus vesiculosus, responds to combined hyposalinity and warming projected to the Baltic Sea by 2070-2099. We quantified responses of replicated populations originating from the entrance, central, and marginal Baltic regions. Using replicated individuals, we tested for the presence of within-population tolerance variation. Future conditions hampered growth and survival of the central and marginal populations whereas the entrance populations fared well. Further, both the among- and within-population variation in responses to climate change indicated existence of genetic variation in tolerance. Such standing genetic variation provides the raw material necessary for adaptation to a changing environment, which may eventually ensure the persistence of the species in the inner Baltic Sea. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predictive Modeling of Rice Yellow Stem Borer Population Dynamics under Climate Change Scenarios in Indramayu

NASA Astrophysics Data System (ADS)

Nurhayati, E.; Koesmaryono, Y.; Impron

2017-03-01

Rice Yellow Stem Borer (YSB) is one of the major insect pests in rice plants that has high attack intensity in rice production center areas, especially in West Java. This pest is consider as holometabola insects that causes rice damage in the vegetative phase (deadheart) as well as generative phase (whitehead). Climatic factor is one of the environmental factors influence the pattern of dynamics population. The purpose of this study was to develop a predictive modeling of YSB pest dynamics population under climate change scenarios (2016-2035 period) using Dymex Model in Indramayu area, West Java. YSB modeling required two main components, namely climate parameters and YSB development lower threshold of temperature (To) to describe YSB life cycle in every phase. Calibration and validation test of models showed the coefficient of determination (R2) between the predicted results and observations of the study area were 0.74 and 0.88 respectively, which was able to illustrate the development, mortality, transfer of individuals from one stage to the next life also fecundity and YSB reproduction. On baseline climate condition, there was a tendency of population abundance peak (outbreak) occured when a change of rainfall intensity in the rainy season transition to dry season or the opposite conditions was happen. In both of application of climate change scenarios, the model outputs were generated well and able to predict the pattern of YSB population dynamics with a the increasing trend of specific population numbers, generation numbers per season and also shifting pattern of populations abundance peak in the future climatic conditions. These results can be adopted as a tool to predict outbreak and to give early warning to control YSB pest more effectively.

From Experiment to Theory: What Can We Learn from Growth Curves?

PubMed

Kareva, Irina; Karev, Georgy

2018-01-01

Finding an appropriate functional form to describe population growth based on key properties of a described system allows making justified predictions about future population development. This information can be of vital importance in all areas of research, ranging from cell growth to global demography. Here, we use this connection between theory and observation to pose the following question: what can we infer about intrinsic properties of a population (i.e., degree of heterogeneity, or dependence on external resources) based on which growth function best fits its growth dynamics? We investigate several nonstandard classes of multi-phase growth curves that capture different stages of population growth; these models include hyperbolic-exponential, exponential-linear, exponential-linear-saturation growth patterns. The constructed models account explicitly for the process of natural selection within inhomogeneous populations. Based on the underlying hypotheses for each of the models, we identify whether the population that it best fits by a particular curve is more likely to be homogeneous or heterogeneous, grow in a density-dependent or frequency-dependent manner, and whether it depends on external resources during any or all stages of its development. We apply these predictions to cancer cell growth and demographic data obtained from the literature. Our theory, if confirmed, can provide an additional biomarker and a predictive tool to complement experimental research.

Predictors of future anabolic androgenic steroid use.

PubMed

Wichstrøm, Lars

2006-09-01

To prospectively study the stability of anabolic androgenic steroid (AAS) use and predictors of AAS use, and to investigate whether AAS use alters the risk of later emotional and behavioral problems. Survey of a national sample of Norwegian high school students (age 15-19) in 1994 followed up in 1999 (N = 2924). Measures of frequent alcohol intoxication (50+ times per 12 months), cannabis use (12 months), hard drug use (12 months), being offered cannabis, eating problems, conduct problems, sexual debut before age 15, BMI, involvement in power sports, perceived physical appearance, and satisfaction with body parts were obtained. Life-time prevalence of AAS use were 1.9 and 0.8% in the follow-up period. Multivariate logistic regression revealed that future AAS use was predicted by young age, male gender, previous AAS use, involvement in power sports, and frequent alcohol intoxication. AAS use did not predict future emotional or behavioral problems other than reducing the risk of future frequent alcohol intoxication. Frequent alcohol intoxication and involvement in power sports appear to predict future AAS use. At the population level there was little stability in individual AAS use from adolescence to early adulthood. No detrimental effects of AAS use could be detected in this study, but low statistical power limits this conclusion.

A changing climate: impacts on human exposures to O3 using an integrated modeling methodology

EPA Science Inventory

Predicting the impacts of changing climate on human exposure to air pollution requires future scenarios that account for changes in ambient pollutant concentrations, population sizes and distributions, and housing stocks. An integrated methodology to model changes in human exposu...

Acclimatization to high-variance habitats does not enhance physiological tolerance of two key Caribbean corals to future temperature and pH.

PubMed

Camp, Emma F; Smith, David J; Evenhuis, Chris; Enochs, Ian; Manzello, Derek; Woodcock, Stephen; Suggett, David J

2016-05-25

Corals are acclimatized to populate dynamic habitats that neighbour coral reefs. Habitats such as seagrass beds exhibit broad diel changes in temperature and pH that routinely expose corals to conditions predicted for reefs over the next 50-100 years. However, whether such acclimatization effectively enhances physiological tolerance to, and hence provides refuge against, future climate scenarios remains unknown. Also, whether corals living in low-variance habitats can tolerate present-day high-variance conditions remains untested. We experimentally examined how pH and temperature predicted for the year 2100 affects the growth and physiology of two dominant Caribbean corals (Acropora palmata and Porites astreoides) native to habitats with intrinsically low (outer-reef terrace, LV) and/or high (neighbouring seagrass, HV) environmental variance. Under present-day temperature and pH, growth and metabolic rates (calcification, respiration and photosynthesis) were unchanged for HV versus LV populations. Superimposing future climate scenarios onto the HV and LV conditions did not result in any enhanced tolerance to colonies native to HV. Calcification rates were always lower for elevated temperature and/or reduced pH. Together, these results suggest that seagrass habitats may not serve as refugia against climate change if the magnitude of future temperature and pH changes is equivalent to neighbouring reef habitats. © 2016 The Author(s).

Projected future distribution of dentists in Japan.

PubMed

Ishimaru, Miho; Ono, Sachiko; Yasunaga, Hideo; Matsui, Hiroki; Koike, Soichi

2016-06-01

Appropriate health policies for the supply of dentists have been an ongoing issue in many developed countries. The purpose of this study was to estimate the future distribution of dentists with different working statuses in Japan and to discuss policy implications about the supply of dentists in any country. This was a retrospective cohort study using data from the National Survey of Physicians, Dentists and Pharmacists for 1972-2012. Based on data from the 2010 and 2012 surveys, we calculated by means of a Markov model the future number of dentists with different working statuses until 2042 according to sex. We estimated that the total number of active dentists will decrease from 2012 to 2042. The number of active dentists per 1,000 population was predicted to reach a peak in 2018, decrease by 4.2% from 2012 to 2038, and thereafter slightly increase. With regard to working status, the number of dentists with their own practices per 1,000 people was predicted to have reached a peak in 2014 and decrease by 22.0% until 2042. We estimated that the number of dentists used in dental clinics per 1,000 population will increase continuously between 2012 and 2042 by 20.0%. Our study suggests that maintaining this supply of dentists may lead to maldistribution of their working status in the future. © 2016 American Association of Public Health Dentistry.

Acclimatization to high-variance habitats does not enhance physiological tolerance of two key Caribbean corals to future temperature and pH

PubMed Central

Smith, David J.; Evenhuis, Chris; Enochs, Ian; Manzello, Derek; Woodcock, Stephen; Suggett, David J.

2016-01-01

Corals are acclimatized to populate dynamic habitats that neighbour coral reefs. Habitats such as seagrass beds exhibit broad diel changes in temperature and pH that routinely expose corals to conditions predicted for reefs over the next 50–100 years. However, whether such acclimatization effectively enhances physiological tolerance to, and hence provides refuge against, future climate scenarios remains unknown. Also, whether corals living in low-variance habitats can tolerate present-day high-variance conditions remains untested. We experimentally examined how pH and temperature predicted for the year 2100 affects the growth and physiology of two dominant Caribbean corals (Acropora palmata and Porites astreoides) native to habitats with intrinsically low (outer-reef terrace, LV) and/or high (neighbouring seagrass, HV) environmental variance. Under present-day temperature and pH, growth and metabolic rates (calcification, respiration and photosynthesis) were unchanged for HV versus LV populations. Superimposing future climate scenarios onto the HV and LV conditions did not result in any enhanced tolerance to colonies native to HV. Calcification rates were always lower for elevated temperature and/or reduced pH. Together, these results suggest that seagrass habitats may not serve as refugia against climate change if the magnitude of future temperature and pH changes is equivalent to neighbouring reef habitats. PMID:27194698

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fant, Charles; Schlosser, C. Adam; Gao, Xiang

The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify themore » primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region’s population will live in water-stressed regions in the near future. Lastly, tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers.« less

Demographic stability metrics for conservation prioritization of isolated populations.

PubMed

Finn, Debra S; Bogan, Michael T; Lytle, David A

2009-10-01

Systems of geographically isolated habitat patches house species that occur naturally as small, disjunct populations. Many of these species are of conservation concern, particularly under the interacting influences of isolation and rapid global change. One potential conservation strategy is to prioritize the populations most likely to persist through change and act as sources for future recolonization of less stable localities. We propose an approach to classify long-term population stability (and, presumably, future persistence potential) with composite demographic metrics derived from standard population-genetic data. Stability metrics can be related to simple habitat measures for a straightforward method of classifying localities to inform conservation management. We tested these ideas in a system of isolated desert headwater streams with mitochondrial sequence data from 16 populations of a flightless aquatic insect. Populations exhibited a wide range of stability scores, which were significantly predicted by dry-season aquatic habitat size. This preliminary test suggests strong potential for our proposed method of classifying isolated populations according to persistence potential. The approach is complementary to existing methods for prioritizing local habitats according to diversity patterns and should be tested further in other systems and with additional loci to inform composite demographic stability scores.

A simulation of dementia epidemiology and resource use in Australia.

PubMed

Standfield, Lachlan B; Comans, Tracy; Scuffham, Paul

2018-06-01

The number of people in the developed world who have dementia is predicted to rise markedly. This study presents a validated predictive model to assist decision-makers to determine this population's future resource requirements and target scarce health and welfare resources appropriately. A novel individual patient discrete event simulation was developed to estimate the future prevalence of dementia and related health and welfare resource use in Australia. When compared to other published results, the simulation generated valid estimates of dementia prevalence and resource use. The analysis predicted 298,000, 387,000 and 928,000 persons in Australia will have dementia in 2011, 2020 and 2050, respectively. Health and welfare resource use increased markedly over the simulated time-horizon and was affected by capacity constraints. This simulation provides useful estimates of future demands on dementia-related services allowing the exploration of the effects of capacity constraints. Implications for public health: The model demonstrates that under-resourcing of residential aged care may lead to inappropriate and inefficient use of hospital resources. To avoid these capacity constraints it is predicted that the number of aged care beds for persons with dementia will need to increase more than threefold from 2011 to 2050. © 2017 The Authors.

Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation

USGS Publications Warehouse

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.

Prediction, Communication and Urban policies. Is there enough space for three faces on a single medal?

NASA Astrophysics Data System (ADS)

Miozzo, D.; Ferraris, L.; Altamura, M.

2012-04-01

There are two possible answers to the question that this session poses (why predict?): Firstly, because scientists like to play God and envisage a future where the chaotic unfolding of atmospheric physics will be reviled by numerical weather prediction models. Secondly, because policy makers realised, in the last years, that the development of our unsustainable society made it impossible to tackle the "risk reduction problem" by solving its dilemma at the root and de-constructing in favour of a cutback of risk exposure. In synthesis the desire of omnipotence of science and the excessively costly future prospected by politicians made us believe that predicting natural hazards is un indispensable tile of a much more complex jigsaw. Civil Protection (CP) measures, those for which most of the predictions are needed, are however entangled within complex societal schemes. A perfect CP system, with perfect soi-disent predictions, is useless if not applied and disseminated through a long term policy of civic education. The entire population needs to became part of this educational stream aiming to a shared and participated empowerment of society. If on the one hand we have society and science on the other hand we have economy and urban policies. The economy deriving from the construction sector is in some countries seen as an indispensable asset for national financial stability. Furthermore the current economical crisis is slowing the adoption of vital risk-reduction interventions: to the same extent as in the aftermath of the Second World War, employment and very short termed economical strategies are overtaking strict urban planning and environmental rules. Thus the availability of funds intended towards the protection of the population has greatly decreased whilst, on the other hand, more buildings are being constructed in areas of great risk. Not only our landscapes are being radically changed but, in the long term, we are exponentially augmenting the exposure of the population to extreme events. This work wants to convey on these themes bringing forward the example of the recent flash flood which took place in Genoa (Liguria Region, Italy, November 2011). It will show how CP plans were present and how they precisely identified the vulnerable areas where unfortunately six women died. Forecasts were consistent to the unfolding of events and CP alerts were diffusely issued two days before the event, however the population was unaware of what was going to happen. To this aspect also the aforementioned faulty urban planning perpetrated in more than fifty years must be taken into account. Going back to the initial question, why do we predict? A realistic answer could be: because we cannot do anything else. It is time for policy makers to rethink completely the scheme of priorities of our society. Are we willing to annihilate the safety of our cities in the near future just to live one more year on the verge of bankruptcy? If things will not change in the near future we are afraid that these questions will be retrospectively answered by our sons and daughters.

Future methane emissions from animals

NASA Astrophysics Data System (ADS)

Anastasi, C.; Simpson, V. J.

1993-04-01

The future global emission of CH4 from enteric fermentation in animals has been estimated for cattle, sheep, and buffalo, which together contribute approximately 91% of the total CH4 emitted from domesticated animals at present. A simple model has been used to relate livestock levels to the national human populations for each country involved in breeding the three species included in this analysis. United Nations population predictions to 2025 were then included in the model to estimate future CH4 emissions. A variational analysis was carried out to investigate the effect of future changes in both the land available for grazing and the nutritional content of feedstocks. Results suggest that the total emission of CH4 from enteric fermentation in domestic animals will increase from 84 Tg CH4 per year (Tg = 1012 g) in 1990 to 119 (±12) Tg CH4 yr-1 by 2025. These values correspond to an average rate of increase over the next 35 years of 1.0 Tg CH4 yr-1.

Climate and human intervention effects on future fire activity and consequences for air pollution across the 21st century

NASA Astrophysics Data System (ADS)

Val Martin, M.; Pierce, J. R.; Heald, C. L.; Li, F.; Lawrence, D. M.; Wiedinmyer, C.; Tilmes, S.; Vitt, F.

2016-12-01

Emissions of aerosols and gases from fires have been shown to adversely affect air quality across the world. Fire activity is strongly related to climate and anthropogenic activities. Current fire projections for the 21st century seem very uncertain, ranging from increasing to declining depending on the climate, land cover change and population growth scenarios used. Here we present an analysis of the changes in future wildfire activity and consequences on air quality, with focus on PM2.5 and surface O3 over regions vulnerable to fire. We use the global Community Earth System Model (CESM) with a process-based fire model to simulate emissions from agriculture, peatland, deforestation and landscape fires for present-day and throughout the current century. We consider two future Representative Concentration Pathways climate scenarios combined with population density changes predicted from Shared Socio-economic Pathways to project climate and demographic effects on fire activity and further consequences for future air quality.

Current and Future Effects of Climate Change on Montane Amphibians

NASA Astrophysics Data System (ADS)

Corn, S.

2002-05-01

Breeding phenology of amphibians in inextricably linked to weather, and change in the timing of breeding resulting from climate change may have consequences for the fitness of individuals and may affect persistence of amphibian populations. Amphibians in some north temperate locations have been observed to breed earlier in recent years in response to warmer spring temperatures, but this is not a universal phenomenon. In mountain populations, phenology is influenced by snow deposition as much as temperature. A trend towards earlier breeding, associated with increasing El Niño frequency, may be occurring in the Cascade Mountains in Oregon, but only at lower elevations. There is no evidence for changes in the dates of breeding activity by amphibians in the Rocky Mountains. Too few amphibian species have been studied, and those for which data exist have been studied for too brief a span of years to allow general conclusions about the effects of climate change. However, regardless of whether climate change has contributed to current amphibian declines, changes in temperature and the extent and duration of snow cover predicted for the next century will have increasingly severe consequences for the persistence of some species. Additional observations from amphibian populations, and spatial and temporal modeling of climate variables are needed to generate predictions of past and future breeding phenology, and the effects on amphibian population dynamics.

Relevant microclimate for determining the development rate of malaria mosquitoes and possible implications of climate change.

PubMed

Paaijmans, Krijn P; Imbahale, Susan S; Thomas, Matthew B; Takken, Willem

2010-07-09

The relationship between mosquito development and temperature is one of the keys to understanding the current and future dynamics and distribution of vector-borne diseases such as malaria. Many process-based models use mean air temperature to estimate larval development times, and hence adult vector densities and/or malaria risk. Water temperatures in three different-sized water pools, as well as the adjacent air temperature in lowland and highland sites in western Kenya were monitored. Both air and water temperatures were fed into a widely-applied temperature-dependent development model for Anopheles gambiae immatures, and subsequently their impact on predicted vector abundance was assessed. Mean water temperature in typical mosquito breeding sites was 4-6 degrees C higher than the mean temperature of the adjacent air, resulting in larval development rates, and hence population growth rates, that are much higher than predicted based on air temperature. On the other hand, due to the non-linearities in the relationship between temperature and larval development rate, together with a marginal buffering in the increase in water temperature compared with air temperature, the relative increases in larval development rates predicted due to climate change are substantially less. Existing models will tend to underestimate mosquito population growth under current conditions, and may overestimate relative increases in population growth under future climate change. These results highlight the need for better integration of biological and environmental information at the scale relevant to mosquito biology.

Modeling microbial communities: current, developing, and future technologies for predicting microbial community interaction.

PubMed

Larsen, Peter; Hamada, Yuki; Gilbert, Jack

2012-07-31

Never has there been a greater opportunity for investigating microbial communities. Not only are the profound effects of microbial ecology on every aspect of Earth's geochemical cycles beginning to be understood, but also the analytical and computational tools for investigating microbial Earth are undergoing a rapid revolution. This environmental microbial interactome, the system of interactions between the microbiome and the environment, has shaped the planet's past and will undoubtedly continue to do so in the future. We review recent approaches for modeling microbial community structures and the interactions of microbial populations with their environments. Different modeling approaches consider the environmental microbial interactome from different aspects, and each provides insights to different facets of microbial ecology. We discuss the challenges and opportunities for the future of microbial modeling and describe recent advances in microbial community modeling that are extending current descriptive technologies into a predictive science. Copyright © 2012 Elsevier B.V. All rights reserved.

Quantifying similarity in reliability surfaces using the probability of agreement

DOE PAGES

Stevens, Nathaniel T.; Anderson-Cook, Christine Michaela

2017-03-30

When separate populations exhibit similar reliability as a function of multiple explanatory variables, combining them into a single population is tempting. This can simplify future predictions and reduce uncertainty associated with estimation. However, combining these populations may introduce bias if the underlying relationships are in fact different. The probability of agreement formally and intuitively quantifies the similarity of estimated reliability surfaces across a two-factor input space. An example from the reliability literature demonstrates the utility of the approach when deciding whether to combine two populations or to keep them as distinct. As a result, new graphical summaries provide strategies formore » visualizing the results.« less

Quantifying similarity in reliability surfaces using the probability of agreement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stevens, Nathaniel T.; Anderson-Cook, Christine Michaela

When separate populations exhibit similar reliability as a function of multiple explanatory variables, combining them into a single population is tempting. This can simplify future predictions and reduce uncertainty associated with estimation. However, combining these populations may introduce bias if the underlying relationships are in fact different. The probability of agreement formally and intuitively quantifies the similarity of estimated reliability surfaces across a two-factor input space. An example from the reliability literature demonstrates the utility of the approach when deciding whether to combine two populations or to keep them as distinct. As a result, new graphical summaries provide strategies formore » visualizing the results.« less

22 Years of predictive testing for Huntington's disease: the experience of the UK Huntington's Prediction Consortium.

PubMed

Baig, Sheharyar S; Strong, Mark; Rosser, Elisabeth; Taverner, Nicola V; Glew, Ruth; Miedzybrodzka, Zosia; Clarke, Angus; Craufurd, David; Quarrell, Oliver W

2016-10-01

Huntington's disease (HD) is a progressive neurodegenerative condition. At-risk individuals have accessed predictive testing via direct mutation testing since 1993. The UK Huntington's Prediction Consortium has collected anonymised data on UK predictive tests, annually, from 1993 to 2014: 9407 predictive tests were performed across 23 UK centres. Where gender was recorded, 4077 participants were male (44.3%) and 5122 were female (55.7%). The median age of participants was 37 years. The most common reason for predictive testing was to reduce uncertainty (70.5%). Of the 8441 predictive tests on individuals at 50% prior risk, 4629 (54.8%) were reported as mutation negative and 3790 (44.9%) were mutation positive, with 22 (0.3%) in the database being uninterpretable. Using a prevalence figure of 12.3 × 10(-5), the cumulative uptake of predictive testing in the 50% at-risk UK population from 1994 to 2014 was estimated at 17.4% (95% CI: 16.9-18.0%). We present the largest study conducted on predictive testing in HD. Our findings indicate that the vast majority of individuals at risk of HD (>80%) have not undergone predictive testing. Future therapies in HD will likely target presymptomatic individuals; therefore, identifying the at-risk population whose gene status is unknown is of significant public health value.

Global warming will reshuffle the areas of high prevalence and richness of three genera of avian blood parasites.

PubMed

Pérez-Rodríguez, Antón; de la Hera, Iván; Fernández-González, Sofía; Pérez-Tris, Javier

2014-08-01

The importance of parasitism for host populations depends on local parasite richness and prevalence: usually host individuals face higher infection risk in areas where parasites are most diverse, and host dispersal to or from these areas may have fitness consequences. Knowing how parasites are and will be distributed in space and time (in a context of global change) is thus crucial from both an ecological and a biological conservation perspective. Nevertheless, most research articles focus just on elaborating models of parasite distribution instead of parasite diversity. We produced distribution models of the areas where haemosporidian parasites are currently highly diverse (both at community and at within-host levels) and prevalent among Iberian populations of a model passerine host: the blackcap Sylvia atricapilla; and how these areas are expected to vary according to three scenarios of climate change. On the basis of these models, we analysed whether variation among populations in parasite richness or prevalence are expected to remain the same or change in the future, thereby reshuffling the geographic mosaic of host-parasite interactions as we observe it today. Our models predict a rearrangement of areas of high prevalence and richness of parasites in the future, with Haemoproteus and Leucocytozoon parasites (today the most diverse genera in blackcaps) losing areas of high diversity and Plasmodium parasites (the most virulent ones) gaining them. Likewise, the prevalence of multiple infections and parasite infracommunity richness would be reduced. Importantly, differences among populations in the prevalence and richness of parasites are expected to decrease in the future, creating a more homogeneous parasitic landscape. This predicts an altered geographic mosaic of host-parasite relationships, which will modify the interaction arena in which parasite virulence evolves. © 2014 John Wiley & Sons Ltd.

Role of genetics in adapting forests under climate change: lessons learned from common garden experiments in central Europe

NASA Astrophysics Data System (ADS)

Chakraborty, Debojyoti; Schueler, Silvio

2017-04-01

Adaptive management aiming at reducing vulnerability and enhancing the resilience of forested ecosystems is a key to preserving the potential of forests to provide multiple ecosystem services under climate change. Planting alternative or non native tree species adapted to future conditions and also utilizing the genetic variation within tree species has also been suggested as an important adaptive management strategy under climate change. Therefore, knowledge on suitable provenances/populations is a key issue. Provenance trial experiments, where several populations of a species are planted in a particular climate or throughout an appropriate climatic gradient offers a great opportunity to understand adaptive genetic variation within a tree species. These trials were primarily established, for identifying populations with desired growth and fitness characteristics. Due to the increasing interest in climate change, such trials were revisited to understand the relation between growth performance and climate and to recommend suitable populations for future conditions. Here we present the lessons learned from provenance trials of Norway spruce and Douglas -fir in central Europe. With data from provenance trials planted across a wide range of environmental conditions in central Europe we developed multivariate models, Universal Response Functions (URFs). The URFs predict growth performance as a function of climate of planting locations (i.e. environmental factors) and provenance/ population origin (i.e. genetic factors). The flexibility of the URFs as a decision making tool is remarkable. The model can be used as to identify suitable planting material for a give site, and vice versa and also as a species distribution model (SDM) with integrated genetic variation. Under current and climate change scenarios, the URFs were applied to predict populations with higher growth performance in central Europe and also as species distribution models for Douglas-fir (Pseudotsuga menziesii [Mirbel] Franco) and Norway spruce (Picea abies (L.) Karst). For both Douglas-fir and Norway spruce wide variation in growth performance were detected. Populations of Douglas-fir identified by the URFs to be optimum for central Europe current climate and climate change scenarios originate from western Cascades and coastal areas of British Columbia, Washington and Oregon. The current seed stands of Douglas-fir in North America, providing planting materials for Central Europe under the legal framework of the Organization for Economic Cooperation and Development (OECD) were found to be suitable for under future conditions. In case of Norway spruce provenances originating from warm and drier regions of south east Europe were found to be suitable for central Europe under future conditions. Even though calibrated with data from Central Europe, when applied as SDMs, the URFs predicted the observed occurrence of Douglas-fir in its native range in North America with reasonable accuracy compared to contemporary SDMs developed in North America. For both Douglas-fir and Norway spruce significant variation in habitat suitability was found depending on the planted population or seed source indicating the role of intraspecific variation in buffering effects of climate change.

Landscape genomic prediction for restoration of a Eucalyptus foundation species under climate change.

PubMed

Supple, Megan Ann; Bragg, Jason G; Broadhurst, Linda M; Nicotra, Adrienne B; Byrne, Margaret; Andrew, Rose L; Widdup, Abigail; Aitken, Nicola C; Borevitz, Justin O

2018-04-24

As species face rapid environmental change, we can build resilient populations through restoration projects that incorporate predicted future climates into seed sourcing decisions. Eucalyptus melliodora is a foundation species of a critically endangered community in Australia that is a target for restoration. We examined genomic and phenotypic variation to make empirical based recommendations for seed sourcing. We examined isolation by distance and isolation by environment, determining high levels of gene flow extending for 500 km and correlations with climate and soil variables. Growth experiments revealed extensive phenotypic variation both within and among sampling sites, but no site-specific differentiation in phenotypic plasticity. Model predictions suggest that seed can be sourced broadly across the landscape, providing ample diversity for adaptation to environmental change. Application of our landscape genomic model to E. melliodora restoration projects can identify genomic variation suitable for predicted future climates, thereby increasing the long term probability of successful restoration. © 2018, Supple et al.

Regulation of water resources for sustaining global future socioeconomic development

NASA Astrophysics Data System (ADS)

Chen, J.; SHI, H.; Sivakumar, B.

2016-12-01

With population projections indicating continued growth during this century, socio-economic problems (e.g., water, food, and energy shortages) will be most likely to occur, especially if proper planning, development, and management strategies are not adopted. In the present study, firstly, we explore the vital role of dams in promoting economic growth through analyzing the relationship between dams and Gross Domestic Product (GDP) at both global and national scales. Secondly, we analyze the current situation of global water scarcity based on the data representing water resources availability, dam development, and the level of economic development. Third, with comprehensive consideration of population growth as the major driving force, water resources availability as the basic supporting factor, and topography as the important constraint, this study addresses the question of dam development in the future and predicts the locations of future dams around the world.

The future impact of population growth and aging on coronary heart disease in China: projections from the Coronary Heart Disease Policy Model-China

PubMed Central

Moran, Andrew; Zhao, Dong; Gu, Dongfeng; Coxson, Pamela; Chen, Chung-Shiuan; Cheng, Jun; Liu, Jing; He, Jiang; Goldman, Lee

2008-01-01

Background China will experience an overall growth and aging of its adult population in coming decades. We used a computer model to forecast the future impact of these demographic changes on coronary heart disease (CHD) in China. Methods The CHD Policy Model is a validated state-transition, computer simulation of CHD on a national scale. China-specific CHD risk factor, incidence, case-fatality, and prevalence data were incorporated, and a CHD prediction model was generated from a Chinese cohort study and calibrated to age-specific Chinese mortality rates. Disability-adjusted life years (DALYs) due to CHD were calculated using standard methods. The projected population of China aged 35–84 years was entered, and CHD events, deaths, and DALYs were simulated over 2000–2029. CHD risk factors other than age and case-fatality were held at year 2000 levels. Sensitivity analyses tested uncertainty regarding CHD mortality coding, the proportion of total deaths attributable to CHD, and case-fatality. Results We predicted 7.8 million excess CHD events (a 69% increase) and 3.4 million excess CHD deaths (a 64% increase) in the decade 2020–2029 compared with 2000–2009. For 2030, we predicted 71% of almost one million annual CHD deaths will occur in persons ≥65 years old, while 67% of the growing annual burden of CHD death and disability will weigh on adults <65 years old. Substituting alternate CHD mortality assumptions led to 17–20% more predicted CHD deaths over 2000–2029, though the pattern of increases in CHD events and deaths over time remained. Conclusion We forecast that absolute numbers of CHD events and deaths will increase dramatically in China over 2010–2029, due to a growing and aging population alone. Recent data suggest CHD risk factor levels are increasing, so our projections may underestimate the extent of the potential CHD epidemic in China. PMID:19036167

C-reactive protein and other markers of inflammation in hemodialysis patients

PubMed Central

Heidari, Behzad

2013-01-01

Hemodialysis patients are at greater risk of cardiovascular disease. Higher than expected cardiovascular morbidity and mortality in this population has been attributed to dislipidemia as well as inflammation. The causes of inflammation in hemodialysis patients are multifactorial. Several markers were used for the detection of inflammatory reaction in patients with chronic renal disease. These markers can be used for the prediction of future cardiovascular events. Among the several parameters of inflammatory markers, serum, CRP is well known and its advantages for the detection of inflammation and its predictor ability has been evaluated in several studies. This review addressed the associated factors and markers of inflammation in hemodialysis patients. In addition, their ability in predicting future atherosclerosis and effect of treatment has been reviewed. However, this context particularly in using CRP as a prediction marker of inflammation and morbidity requires further studies. PMID:24009946

C-reactive protein and other markers of inflammation in hemodialysis patients.

PubMed

Heidari, Behzad

2013-01-01

Hemodialysis patients are at greater risk of cardiovascular disease. Higher than expected cardiovascular morbidity and mortality in this population has been attributed to dislipidemia as well as inflammation. The causes of inflammation in hemodialysis patients are multifactorial. Several markers were used for the detection of inflammatory reaction in patients with chronic renal disease. These markers can be used for the prediction of future cardiovascular events. Among the several parameters of inflammatory markers, serum, CRP is well known and its advantages for the detection of inflammation and its predictor ability has been evaluated in several studies. This review addressed the associated factors and markers of inflammation in hemodialysis patients. In addition, their ability in predicting future atherosclerosis and effect of treatment has been reviewed. However, this context particularly in using CRP as a prediction marker of inflammation and morbidity requires further studies.

Annual costs of chronic obstructive pulmonary disease in Finland during 1996–2006 and a prediction model for 2007–2030

PubMed Central

Herse, Fredrik; Kiljander, Toni; Lehtimäki, Lauri

2015-01-01

Background: Chronic obstructive pulmonary disease (COPD) is a major burden for the health care system, but the exact costs are difficult to estimate and there are insufficient data available on past and future time trends of COPD-related costs. Aims: The aim of the study was to calculate COPD-related costs in Finland during the years 1996–2006 and estimate future costs for the years 2007–2030. Methods: COPD-related direct and indirect costs in the public health care sector of the whole of Finland during the years 1996–2006 were retrieved from national registers. In addition, we made a mathematical prediction model on COPD costs for the years 2007–2030 on the basis of population projection and changes in smoking habits. Results: The total annual COPD-related costs amounted to about 100–110 million Euros in 1996–2006, with no obvious change, but there was a slight decrease in direct costs and an increase in indirect costs during these years. The estimation model predicted a 60% increase up to 166 million Euros in COPD-related annual costs by the year 2030. This is caused almost entirely by an increase in direct health care costs that reflect the predicted ageing of the Finnish population, as older age is a significant factor that increases the need for hospitalisation. Conclusions: The total annual COPD-related costs in Finland have been stable during the years 1996–2006, but if management strategies are not changed a significant increase in direct costs is expected by the year 2030 due to ageing of the population. PMID:25811648

The role of abiotic conditions in shaping the long-term patterns of a high-elevation Argentine ant invasion

USGS Publications Warehouse

Krushelnycky, P.D.; Joe, S.M.; Medeiros, A.C.; Daehler, C.C.; Loope, L.L.

2005-01-01

Analysis of long-term patterns of invasion can reveal the importance of abiotic factors in influencing invasion dynamics, and can help predict future patterns of spread. In the case of the invasive Argentine ant (Linepithema humile), most prior studies have investigated this species' limitations in hot and dry climates. However, spatial and temporal patterns of spread involving two ant populations over the course of 30 years at a high elevation site in Hawaii suggest that cold and wet conditions have influenced both the ant's distribution and its rate of invasion. In Haleakala National Park on Maui, we found that a population invading at lower elevation is limited by increasing rainfall and presumably by associated decreasing temperatures. A second, higher elevation population has spread outward in all directions, but rates of spread in different directions appear to have been strongly influenced by differences in elevation and temperature. Patterns of foraging activity were strongly tied to soil temperatures, supporting the hypothesis that variation in temperature can influence rates of spread. Based on past patterns of spread, we predicted a total potential range that covers nearly 50% of the park and 75% of the park's subalpine habitats. We compared this rough estimate with point predictions derived from a degree-day model for Argentine ant colony reproduction, and found that the two independent predictions match closely when soil temperatures are used in the model. The cold, wet conditions that have influenced Argentine ant invasion at this site are likely to be influential at other locations in this species' current and future worldwide distribution. ?? 2005 Blackwell Publishing Ltd.

[Dental practitioners in Israel: past, present and future].

PubMed

Mann, J; Vered, Y; Zini, A

2010-04-01

Since 1980 various studies have been published in Israel dealing with dental manpower issues, utilizing several methods such as manpower to population ratio. The dental literature pointed out that dentistry in Israel has an over supply of dentists and that manpower to population ratio is one of the highest in the world 1:770. All studies were based on the information provided by the Ministry of Health which showed that Israel has over 9500 dentists. The Israel Central Bureau of Statistics figures showed a much smaller number which was 5700 active dentists. This enormous gap in between two sources of information, following strict examination of the data revealed that the Bureau of Statistics information is reliable and hence, the real manpower to population ratio in Israel in 2008 was 1:1271. Prediction of manpower is extremely important and the base line information is crucial for future evaluations.

Trend in Obesity Prevalence in European Adult Cohort Populations during Follow-up since 1996 and Their Predictions to 2015

PubMed Central

von Ruesten, Anne; Steffen, Annika; Floegel, Anna; van der A, Daphne L.; Masala, Giovanna; Tjønneland, Anne; Halkjaer, Jytte; Palli, Domenico; Wareham, Nicholas J.; Loos, Ruth J. F.; Sørensen, Thorkild I. A.; Boeing, Heiner

2011-01-01

Objective To investigate trends in obesity prevalence in recent years and to predict the obesity prevalence in 2015 in European populations. Methods Data of 97 942 participants from seven cohorts involved in the European Prospective Investigation into Cancer and Nutrition (EPIC) study participating in the Diogenes project (named as “Diogenes cohort” in the following) with weight measurements at baseline and follow-up were used to predict future obesity prevalence with logistic linear and non-linear (leveling off) regression models. In addition, linear and leveling off models were fitted to the EPIC-Potsdam dataset with five weight measures during the observation period to find out which of these two models might provide the more realistic prediction. Results During a mean follow-up period of 6 years, the obesity prevalence in the Diogenes cohort increased from 13% to 17%. The linear prediction model predicted an overall obesity prevalence of about 30% in 2015, whereas the leveling off model predicted a prevalence of about 20%. In the EPIC-Potsdam cohort, the shape of obesity trend favors a leveling off model among men (R2 = 0.98), and a linear model among women (R2 = 0.99). Conclusion Our data show an increase in obesity prevalence since the 1990ies, and predictions by 2015 suggests a sizeable further increase in European populations. However, the estimates from the leveling off model were considerably lower. PMID:22102897

The invasive mosquito species Aedes albopictus: current knowledge and future perspectives

PubMed Central

Bonizzoni, Mariangela; Gasperi, Giuliano; Chen, Xioaguang; James, Anthony A.

2013-01-01

One of the most dynamic events in public health is being mediated by the global spread of the invasive mosquito Aedes albopictus. Its rapid expansion and vectorial capacity for various arboviruses affect an increasingly larger proportion of the world population. Responses to the challenges of controlling this vector are expected to be enhanced by an increased knowledge of its biology, ecology, and vector competence. Details of population genetics and structure will allow following, and possibly predicting, the geographical and temporal dynamics of its expansion, and will inform the practical operations of control programs. Experts are coming together now to describe the history, characterize the present circumstances, and collaborate on future efforts to understand and mitigate this emerging public health threat. PMID:23916878

The southern megalopolis: using the past to predict the future of urban sprawl in the Southeast U.S.

USGS Publications Warehouse

Terando, Adam; Costanza, Jennifer; Belyea, Curtis; Dunn, Robert R.; McKerrow, Alexa; Collazo, Jaime

2014-01-01

The future health of ecosystems is arguably as dependent on urban sprawl as it is on human-caused climatic warming. Urban sprawl strongly impacts the urban ecosystems it creates and the natural and agro-ecosystems that it displaces and fragments. Here, we project urban sprawl changes for the next 50 years for the fast-growing Southeast U.S. Previous studies have focused on modeling population density, but the urban extent is arguably as important as population density per se in terms of its ecological and conservation impacts. We develop simulations using the SLEUTH urban growth model that complement population-driven models but focus on spatial pattern and extent. To better capture the reach of low-density suburban development, we extend the capabilities of SLEUTH by incorporating street-network information. Our simulations point to a future in which the extent of urbanization in the Southeast is projected to increase by 101% to 192%. Our results highlight areas where ecosystem fragmentation is likely, and serve as a benchmark to explore the challenging tradeoffs between ecosystem health, economic growth and cultural desires.

The Southern Megalopolis: Using the Past to Predict the Future of Urban Sprawl in the Southeast U.S

PubMed Central

Terando, Adam J.; Costanza, Jennifer; Belyea, Curtis; Dunn, Robert R.; McKerrow, Alexa; Collazo, Jaime A.

2014-01-01

The future health of ecosystems is arguably as dependent on urban sprawl as it is on human-caused climatic warming. Urban sprawl strongly impacts the urban ecosystems it creates and the natural and agro-ecosystems that it displaces and fragments. Here, we project urban sprawl changes for the next 50 years for the fast-growing Southeast U.S. Previous studies have focused on modeling population density, but the urban extent is arguably as important as population density per se in terms of its ecological and conservation impacts. We develop simulations using the SLEUTH urban growth model that complement population-driven models but focus on spatial pattern and extent. To better capture the reach of low-density suburban development, we extend the capabilities of SLEUTH by incorporating street-network information. Our simulations point to a future in which the extent of urbanization in the Southeast is projected to increase by 101% to 192%. Our results highlight areas where ecosystem fragmentation is likely, and serve as a benchmark to explore the challenging tradeoffs between ecosystem health, economic growth and cultural desires. PMID:25054329

Using dynamic population simulations to extend resource selection analyses and prioritize habitats for conservation

USGS Publications Warehouse

Heinrichs, Julie; Aldridge, Cameron L.; O'Donnell, Michael; Schumaker, Nathan

2017-01-01

Prioritizing habitats for conservation is a challenging task, particularly for species with fluctuating populations and seasonally dynamic habitat needs. Although the use of resource selection models to identify and prioritize habitat for conservation is increasingly common, their ability to characterize important long-term habitats for dynamic populations are variable. To examine how habitats might be prioritized differently if resource selection was directly and dynamically linked with population fluctuations and movement limitations among seasonal habitats, we constructed a spatially explicit individual-based model for a dramatically fluctuating population requiring temporally varying resources. Using greater sage-grouse (Centrocercus urophasianus) in Wyoming as a case study, we used resource selection function maps to guide seasonal movement and habitat selection, but emergent population dynamics and simulated movement limitations modified long-term habitat occupancy. We compared priority habitats in RSF maps to long-term simulated habitat use. We examined the circumstances under which the explicit consideration of movement limitations, in combination with population fluctuations and trends, are likely to alter predictions of important habitats. In doing so, we assessed the future occupancy of protected areas under alternative population and habitat conditions. Habitat prioritizations based on resource selection models alone predicted high use in isolated parcels of habitat and in areas with low connectivity among seasonal habitats. In contrast, results based on more biologically-informed simulations emphasized central and connected areas near high-density populations, sometimes predicted to be low selection value. Dynamic models of habitat use can provide additional biological realism that can extend, and in some cases, contradict habitat use predictions generated from short-term or static resource selection analyses. The explicit inclusion of population dynamics and movement propensities via spatial simulation modeling frameworks may provide an informative means of predicting long-term habitat use, particularly for fluctuating populations with complex seasonal habitat needs. Importantly, our results indicate the possible need to consider habitat selection models as a starting point rather than the common end point for refining and prioritizing habitats for protection for cyclic and highly variable populations.

A comparison between the observed and predicted Fe II spectrum in different plasmas

NASA Astrophysics Data System (ADS)

Johansson, S.

This paper gives a survey of the spectral distribution of emission lines of Fe II, predicted from a single atomic model. The observed differences between the recorded and the predicted spectrum are discussed in terms of deficiencies of the model and interactions within the emitting plasma. A number of illustrative examples of unexpected features with applications to astrophysics are given. Selective population, due to charge transfer and resonant photo excitation, is elucidated. The future need of more laboratory data for Fe II as regards energy levels and line classification is also discussed.

Anticipating changes to future connectivity within a network of marine protected areas.

PubMed

Coleman, Melinda A; Cetina-Heredia, Paulina; Roughan, Moninya; Feng, Ming; van Sebille, Erik; Kelaher, Brendan P

2017-09-01

Continental boundary currents are projected to be altered under future scenarios of climate change. As these currents often influence dispersal and connectivity among populations of many marine organisms, changes to boundary currents may have dramatic implications for population persistence. Networks of marine protected areas (MPAs) often aim to maintain connectivity, but anticipation of the scale and extent of climatic impacts on connectivity are required to achieve this critical conservation goal in a future of climate change. For two key marine species (kelp and sea urchins), we use oceanographic modelling to predict how continental boundary currents are likely to change connectivity among a network of MPAs spanning over 1000 km of coastline off the coast of eastern Australia. Overall change in predicted connectivity among pairs of MPAs within the network did not change significantly over and above temporal variation within climatic scenarios, highlighting the need for future studies to incorporate temporal variation in dispersal to robustly anticipate likely change. However, the intricacies of connectivity between different pairs of MPAs were noteworthy. For kelp, poleward connectivity among pairs of MPAs tended to increase in the future, whereas equatorward connectivity tended to decrease. In contrast, for sea urchins, connectivity among pairs of MPAs generally decreased in both directions. Self-seeding within higher-latitude MPAs tended to increase, and the role of low-latitude MPAs as a sink for urchins changed significantly in contrasting ways. These projected changes have the potential to alter important genetic parameters with implications for adaptation and ecosystem vulnerability to climate change. Considering such changes, in the context of managing and designing MPA networks, may ensure that conservation goals are achieved into the future. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Accurate Prediction of Drug-Induced Liver Injury Using Stem Cell-Derived Populations

PubMed Central

Szkolnicka, Dagmara; Farnworth, Sarah L.; Lucendo-Villarin, Baltasar; Storck, Christopher; Zhou, Wenli; Iredale, John P.; Flint, Oliver

2014-01-01

Despite major progress in the knowledge and management of human liver injury, there are millions of people suffering from chronic liver disease. Currently, the only cure for end-stage liver disease is orthotopic liver transplantation; however, this approach is severely limited by organ donation. Alternative approaches to restoring liver function have therefore been pursued, including the use of somatic and stem cell populations. Although such approaches are essential in developing scalable treatments, there is also an imperative to develop predictive human systems that more effectively study and/or prevent the onset of liver disease and decompensated organ function. We used a renewable human stem cell resource, from defined genetic backgrounds, and drove them through developmental intermediates to yield highly active, drug-inducible, and predictive human hepatocyte populations. Most importantly, stem cell-derived hepatocytes displayed equivalence to primary adult hepatocytes, following incubation with known hepatotoxins. In summary, we have developed a serum-free, scalable, and shippable cell-based model that faithfully predicts the potential for human liver injury. Such a resource has direct application in human modeling and, in the future, could play an important role in developing renewable cell-based therapies. PMID:24375539

Evaluating effects of Everglades restoration on American crocodile populations in south Florida using a spatially-explicit, stage-based population model

USGS Publications Warehouse

Green, Timothy W.; Slone, Daniel H.; Swain, Eric D.; Cherkiss, Michael S.; Lohmann, Melinda; Mazzotti, Frank J.; Rice, Kenneth G.

2014-01-01

The distribution and abundance of the American crocodile (Crocodylus acutus) in the Florida Everglades is dependent on the timing, amount, and location of freshwater flow. One of the goals of the Comprehensive Everglades Restoration Plan (CERP) is to restore historic freshwater flows to American crocodile habitat throughout the Everglades. To predict the impacts on the crocodile population from planned restoration activities, we created a stage-based spatially explicit crocodile population model that incorporated regional hydrology models and American crocodile research and monitoring data. Growth and survival were influenced by salinity, water depth, and density-dependent interactions. A stage-structured spatial model was used with discrete spatial convolution to direct crocodiles toward attractive sources where conditions were favorable. The model predicted that CERP would have both positive and negative impacts on American crocodile growth, survival, and distribution. Overall, crocodile populations across south Florida were predicted to decrease approximately 3 % with the implementation of CERP compared to future conditions without restoration, but local increases up to 30 % occurred in the Joe Bay area near Taylor Slough, and local decreases up to 30 % occurred in the vicinity of Buttonwood Canal due to changes in salinity and freshwater flows.

How effective are risk assessments/measures for predicting future aggressive behaviour in adults with intellectual disabilities (ID): A systematic review and meta-analysis.

PubMed

Lofthouse, Rachael; Golding, Laura; Totsika, Vasiliki; Hastings, Richard; Lindsay, William

2017-12-01

Risk assessments assist professionals in the identification and management of risk of aggression. The present study aimed to systematically review evidence on the efficacy of assessments for managing the risk of physical aggression in adults with intellectual disabilities (ID). A literature search was conducted using the databases PsycINFO, EMBASE, MEDLINE, Web of Science, and Google Scholar. Electronic and hand searches identified 14 studies that met the inclusion criteria. Standardised mean difference effect sizes Area Under Curve (AUC) were calculated for studies. Random effects subgroup analysis was used to compare different types of risk measures (Actuarial, Structured Professional Judgment and dynamic), and prospective vs. catch-up longitudinal study designs. Overall, evidence of predictive validity was found for risk measures with ID populations: (AUC)=0.724, 95% CI [0.681, 0.768]. There was no variation in the performance of different types of risk measures, or different study design. Risk assessment measures predict the likelihood of aggression in ID population and are comparable to those in mainstream populations. Further meta-analysis is necessary when risk measures are more established in this population. Copyright © 2017 Elsevier Ltd. All rights reserved.

A prediction of the trend of population development in urban and rural areas in China.

PubMed

Hu, Y

1998-01-01

This study predicts trends in population growth, urbanization, and age structure in China. Data were obtained from the 1990 Census. Population totaled 1.22 billion at the end of 1996. The fertility model predicts future fertility by variant and parity; parameters are provided in a table. High, medium, and low fertility variants, respectively, are based on the total regressive fertility rates (TRFR) of 2.23, 1.9, and 1.6. The medium variant assumes 2 children in rural areas. The low variant is ideal and assumes no third parity in rural areas. Urbanization means an annual average increase of 0.5% after 1996 at pace I and 0.8% at pace II. Urban population will be 57.8% of total population by 2050. Under these three variants, population size in 2000 will be 898 million in rural and 403 million in urban areas, 869 million in rural and 400 million in urban areas, and 856 million in rural and 398 million in urban areas, respectively. Population will peak at 1.7 billion in 2050, at 1.48 billion in 2033, and at 1.38 billion in 2023, respectively. During the period 2000-2020, about 10-14 million rural migrants will move to urban areas; 10 million will move thereafter. The elderly aged over 60 years will reach 7% by 2000 and 20% by 2040. Rural population will age faster than urban population. The working age population will reach 775 million in 2000, peak at 868 million in 2016, and will always be over 60% of total population. School-age population will amount to over 300 million by 2030. Young population will always be more than 25% in rural areas, which is nearly 17 percentage points higher than in urban areas.

HIV-1 DNA predicts disease progression and post-treatment virological control

PubMed Central

Williams, James P; Hurst, Jacob; Stöhr, Wolfgang; Robinson, Nicola; Brown, Helen; Fisher, Martin; Kinloch, Sabine; Cooper, David; Schechter, Mauro; Tambussi, Giuseppe; Fidler, Sarah; Carrington, Mary; Babiker, Abdel; Weber, Jonathan

2014-01-01

In HIV-1 infection, a population of latently infected cells facilitates viral persistence despite antiretroviral therapy (ART). With the aim of identifying individuals in whom ART might induce a period of viraemic control on stopping therapy, we hypothesised that quantification of the pool of latently infected cells in primary HIV-1 infection (PHI) would predict clinical progression and viral replication following ART. We measured HIV-1 DNA in a highly characterised randomised population of individuals with PHI. We explored associations between HIV-1 DNA and immunological and virological markers of clinical progression, including viral rebound in those interrupting therapy. In multivariable analyses, HIV-1 DNA was more predictive of disease progression than plasma viral load and, at treatment interruption, predicted time to plasma virus rebound. HIV-1 DNA may help identify individuals who could safely interrupt ART in future HIV-1 eradication trials. Clinical trial registration: ISRCTN76742797 and EudraCT2004-000446-20 DOI: http://dx.doi.org/10.7554/eLife.03821.001 PMID:25217531

Using artificial neural network and satellite data to predict rice yield in Bangladesh

NASA Astrophysics Data System (ADS)

Akhand, Kawsar; Nizamuddin, Mohammad; Roytman, Leonid; Kogan, Felix; Goldberg, Mitch

2015-09-01

Rice production in Bangladesh is a crucial part of the national economy and providing about 70 percent of an average citizen's total calorie intake. The demand for rice is constantly rising as the new populations are added in every year in Bangladesh. Due to the increase in population, the cultivation land decreases. In addition, Bangladesh is faced with production constraints such as drought, flooding, salinity, lack of irrigation facilities and lack of modern technology. To maintain self sufficiency in rice, Bangladesh will have to continue to expand rice production by increasing yield at a rate that is at least equal to the population growth until the demand of rice has stabilized. Accurate rice yield prediction is one of the most important challenges in managing supply and demand of rice as well as decision making processes. Artificial Neural Network (ANN) is used to construct a model to predict Aus rice yield in Bangladesh. Advanced Very High Resolution Radiometer (AVHRR)-based remote sensing satellite data vegetation health (VH) indices (Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) are used as input variables and official statistics of Aus rice yield is used as target variable for ANN prediction model. The result obtained with ANN method is encouraging and the error of prediction is less than 10%. Therefore, prediction can play an important role in planning and storing of sufficient rice to face in any future uncertainty.

Intraspecific niche models for ponderosa pine (Pinus ponderosa) suggest potential variability in population-level response to climate change.

PubMed

Maguire, Kaitlin C; Shinneman, Douglas J; Potter, Kevin M; Hipkins, Valerie D

2018-03-14

Unique responses to climate change can occur across intraspecific levels, resulting in individualistic adaptation or movement patterns among populations within a given species. Thus, the need to model potential responses among genetically distinct populations within a species is increasingly recognized. However, predictive models of future distributions are regularly fit at the species level, often because intraspecific variation is unknown or is identified only within limited sample locations. In this study, we considered the role of intraspecific variation to shape the geographic distribution of ponderosa pine (Pinus ponderosa), an ecologically and economically important tree species in North America. Morphological and genetic variation across the distribution of ponderosa pine suggest the need to model intraspecific populations: the two varieties (var. ponderosa and var. scopulorum) and several haplotype groups within each variety have been shown to occupy unique climatic niches, suggesting populations have distinct evolutionary lineages adapted to different environmental conditions. We utilized a recently-available, geographically-widespread dataset of intraspecific variation (haplotypes) for ponderosa pine and a recently-devised lineage distance modeling approach to derive additional, likely intraspecific occurrence locations. We confirmed the relative uniqueness of each haplotype-climate relationship using a niche-overlap analysis, and developed ecological niche models (ENMs) to project the distribution for two varieties and eight haplotypes under future climate forecasts. Future projections of haplotype niche distributions generally revealed greater potential range loss than predicted for the varieties. This difference may reflect intraspecific responses of distinct evolutionary lineages. However, directional trends are generally consistent across intraspecific levels, and include a loss of distributional area and an upward shift in elevation. Our results demonstrate the utility in modeling intraspecific response to changing climate and they inform management and conservation strategies, by identifying haplotypes and geographic areas that may be most at risk, or most secure, under projected climate change.

Intraspecific niche models for ponderosa pine (Pinus ponderosa) suggest potential variability in population-level response to climate change

USGS Publications Warehouse

Maguire, Kaitlin C.; Shinneman, Douglas; Potter, Kevin M.; Hipkins, Valerie D.

2018-01-01

Unique responses to climate change can occur across intraspecific levels, resulting in individualistic adaptation or movement patterns among populations within a given species. Thus, the need to model potential responses among genetically distinct populations within a species is increasingly recognized. However, predictive models of future distributions are regularly fit at the species level, often because intraspecific variation is unknown or is identified only within limited sample locations. In this study, we considered the role of intraspecific variation to shape the geographic distribution of ponderosa pine (Pinus ponderosa), an ecologically and economically important tree species in North America. Morphological and genetic variation across the distribution of ponderosa pine suggest the need to model intraspecific populations: the two varieties (var. ponderosa and var. scopulorum) and several haplotype groups within each variety have been shown to occupy unique climatic niches, suggesting populations have distinct evolutionary lineages adapted to different environmental conditions. We utilized a recently-available, geographically-widespread dataset of intraspecific variation (haplotypes) for ponderosa pine and a recently-devised lineage distance modeling approach to derive additional, likely intraspecific occurrence locations. We confirmed the relative uniqueness of each haplotype-climate relationship using a niche-overlap analysis, and developed ecological niche models (ENMs) to project the distribution for two varieties and eight haplotypes under future climate forecasts. Future projections of haplotype niche distributions generally revealed greater potential range loss than predicted for the varieties. This difference may reflect intraspecific responses of distinct evolutionary lineages. However, directional trends are generally consistent across intraspecific levels, and include a loss of distributional area and an upward shift in elevation. Our results demonstrate the utility in modeling intraspecific response to changing climate and they inform management and conservation strategies, by identifying haplotypes and geographic areas that may be most at risk, or most secure, under projected climate change.

Human Population Density and Extinction Risk in the World's Carnivores

PubMed Central

Purvis, Andy; Sechrest, Wes; Gittleman, John L; Bielby, Jon; Mace, Georgina M

2004-01-01

Understanding why some species are at high risk of extinction, while others remain relatively safe, is central to the development of a predictive conservation science. Recent studies have shown that a species' extinction risk may be determined by two types of factors: intrinsic biological traits and exposure to external anthropogenic threats. However, little is known about the relative and interacting effects of intrinsic and external variables on extinction risk. Using phylogenetic comparative methods, we show that extinction risk in the mammal order Carnivora is predicted more strongly by biology than exposure to high-density human populations. However, biology interacts with human population density to determine extinction risk: biological traits explain 80% of variation in risk for carnivore species with high levels of exposure to human populations, compared to 45% for carnivores generally. The results suggest that biology will become a more critical determinant of risk as human populations expand. We demonstrate how a model predicting extinction risk from biology can be combined with projected human population density to identify species likely to move most rapidly towards extinction by the year 2030. African viverrid species are particularly likely to become threatened, even though most are currently considered relatively safe. We suggest that a preemptive approach to species conservation is needed to identify and protect species that may not be threatened at present but may become so in the near future. PMID:15252445

Adolescents' Changing Future Expectations Predict the Timing of Adult Role Transitions

ERIC Educational Resources Information Center

Beal, Sarah J.; Crockett, Lisa J.; Peugh, James

2016-01-01

Individual differences in the transition to adulthood are well established. This study examines the extent to which heterogeneity in pathways to adulthood that have been observed in the broader U.S. population are mirrored in adolescents' expectations regarding when they will experience key adult role transitions (e.g., marriage). Patterns of…

Educational Planning: The Census Bureau Can Help.

ERIC Educational Resources Information Center

Whitson, Dorothy W.

The author states that projection of future populations is not feasible because the chief factor in the computations, the birth rate, cannot be predicted with certainty. The paper discusses some national implications, and also suggests that census data by school district can be useful in improving formulas for distribution of federal and State…

The Use of One-Sample Prediction Intervals for Estimating CO2 Scrubber Canister Durations

DTIC Science & Technology

2012-10-01

Grade and 812 D-Grade Sofnolime.3 Definitions According to Devore,4 A CI (confidence interval) refers to a parameter, or population ... characteristic , whose value is fixed but unknown to us. In contrast, a future value of Y is not a parameter but instead a random variable; for this

Modeling potential movements of the emerald ash borer: the model framework

Treesearch

Louis R. Iverson; Anantha Prasad; Jonathan Bossenbroek; Davis Sydnor; Mark W. Schwartz

2010-01-01

The emerald ash borer (EAB, Agrilus planipennis Fairmaire) is threatening to decimate native ashes (Fraxinus spp.) across North America and, so far, has devastated ash populations across sections of Michigan, Ohio, Indiana, and Ontario. We are attempting to develop a computer model that will predict EAB future movement by adapting...

Should Nuclear Energy Form Part of the UK's Energy Future?

ERIC Educational Resources Information Center

Campbell, Peter

2003-01-01

Energy policies are under review everywhere, as the world tries to meet targets for reducing climate change despite continuing population growth. A major change in energy patterns is needed, with the critical period for transition predictably happening when young people currently at school are in their middle years of their lives. This article…

What can nuclear energy do for society?

NASA Technical Reports Server (NTRS)

Rom, F. E.

1971-01-01

The utilization of nuclear energy and the predicted impact of future uses of nuclear energy are discussed. Areas of application in electric power production and transportation methods are described. It is concluded that the need for many forms of nuclear energy will become critical as the requirements for power to supply an increasing population are met.

Real-time web-based assessment of total population risk of future emergency department utilization: statewide prospective active case finding study.

PubMed

Hu, Zhongkai; Jin, Bo; Shin, Andrew Y; Zhu, Chunqing; Zhao, Yifan; Hao, Shiying; Zheng, Le; Fu, Changlin; Wen, Qiaojun; Ji, Jun; Li, Zhen; Wang, Yong; Zheng, Xiaolin; Dai, Dorothy; Culver, Devore S; Alfreds, Shaun T; Rogow, Todd; Stearns, Frank; Sylvester, Karl G; Widen, Eric; Ling, Xuefeng B

2015-01-13

An easily accessible real-time Web-based utility to assess patient risks of future emergency department (ED) visits can help the health care provider guide the allocation of resources to better manage higher-risk patient populations and thereby reduce unnecessary use of EDs. Our main objective was to develop a Health Information Exchange-based, next 6-month ED risk surveillance system in the state of Maine. Data on electronic medical record (EMR) encounters integrated by HealthInfoNet (HIN), Maine's Health Information Exchange, were used to develop the Web-based surveillance system for a population ED future 6-month risk prediction. To model, a retrospective cohort of 829,641 patients with comprehensive clinical histories from January 1 to December 31, 2012 was used for training and then tested with a prospective cohort of 875,979 patients from July 1, 2012, to June 30, 2013. The multivariate statistical analysis identified 101 variables predictive of future defined 6-month risk of ED visit: 4 age groups, history of 8 different encounter types, history of 17 primary and 8 secondary diagnoses, 8 specific chronic diseases, 28 laboratory test results, history of 3 radiographic tests, and history of 25 outpatient prescription medications. The c-statistics for the retrospective and prospective cohorts were 0.739 and 0.732 respectively. Integration of our method into the HIN secure statewide data system in real time prospectively validated its performance. Cluster analysis in both the retrospective and prospective analyses revealed discrete subpopulations of high-risk patients, grouped around multiple "anchoring" demographics and chronic conditions. With the Web-based population risk-monitoring enterprise dashboards, the effectiveness of the active case finding algorithm has been validated by clinicians and caregivers in Maine. The active case finding model and associated real-time Web-based app were designed to track the evolving nature of total population risk, in a longitudinal manner, for ED visits across all payers, all diseases, and all age groups. Therefore, providers can implement targeted care management strategies to the patient subgroups with similar patterns of clinical histories, driving the delivery of more efficient and effective health care interventions. To the best of our knowledge, this prospectively validated EMR-based, Web-based tool is the first one to allow real-time total population risk assessment for statewide ED visits.

Shifting species interactions in terrestrial dryland ecosystems under altered water availability and climate change.

PubMed

McCluney, Kevin E; Belnap, Jayne; Collins, Scott L; González, Angélica L; Hagen, Elizabeth M; Nathaniel Holland, J; Kotler, Burt P; Maestre, Fernando T; Smith, Stanley D; Wolf, Blair O

2012-08-01

Species interactions play key roles in linking the responses of populations, communities, and ecosystems to environmental change. For instance, species interactions are an important determinant of the complexity of changes in trophic biomass with variation in resources. Water resources are a major driver of terrestrial ecology and climate change is expected to greatly alter the distribution of this critical resource. While previous studies have documented strong effects of global environmental change on species interactions in general, responses can vary from region to region. Dryland ecosystems occupy more than one-third of the Earth's land mass, are greatly affected by changes in water availability, and are predicted to be hotspots of climate change. Thus, it is imperative to understand the effects of environmental change on these globally significant ecosystems. Here, we review studies of the responses of population-level plant-plant, plant-herbivore, and predator-prey interactions to changes in water availability in dryland environments in order to develop new hypotheses and predictions to guide future research. To help explain patterns of interaction outcomes, we developed a conceptual model that views interaction outcomes as shifting between (1) competition and facilitation (plant-plant), (2) herbivory, neutralism, or mutualism (plant-herbivore), or (3) neutralism and predation (predator-prey), as water availability crosses physiological, behavioural, or population-density thresholds. We link our conceptual model to hypothetical scenarios of current and future water availability to make testable predictions about the influence of changes in water availability on species interactions. We also examine potential implications of our conceptual model for the relative importance of top-down effects and the linearity of patterns of change in trophic biomass with changes in water availability. Finally, we highlight key research needs and some possible broader impacts of our findings. Overall, we hope to stimulate and guide future research that links changes in water availability to patterns of species interactions and the dynamics of populations and communities in dryland ecosystems. © 2011 The Authors. Biological Reviews © 2011 Cambridge Philosophical Society.

Cancer morbidity among methyl isocyanate exposed long- term survivors and their offspring: a hospital-based five year descriptive study (2006 - 2011) and future directions to predict cancer risk in the affected population.

PubMed

Senthilkumar, Chinnu Sugavanam; Malla, Tahir Mohi-ud-Din; Sah, Nand Kishore; Ganesh, Narayanan

2011-01-01

The purpose of this study was to update both researchers and clinicians about the cancer incidence in methyl isocyanate (MIC) exposed long-term survivors and in their offspring, focusing on the etiological plausibility. In the time period 2006-2011, cancer morbidity was evaluated in the population surviving after exposure to (MIC) on December 3rd, 1984, in Bhopal. This descriptive study is based on hospital registration of 1261 cancer patients those are MIC gas victims and their subsequently born offspring. Morbidity status was studied on the basis of gender, age, organ and site with relative percentages. Cancers on specific sites, with special reference to breast (n=231) (18.31%), lung (n=103) (8.16%), tongue (n=103) (8.16%), buccal mucosa (n=94) (7.45%), cervix (n=72) (5.70%), and esophagus (n=68) (5.39%) were found in high proportions. Ovary (n=43) (3.40%), brain (n=42) (3.33%), larynx (n=40) (3.17%), non-Hodgkin's (n=31) (2.45%), gallbladder (n=29) (2.29%), stomach (n=28) (2.22%), head and neck (n=28) (2.22%), liver (n=27) (2.14%), acute lymphoid leukemia (n=24) (1.90%), rectum (n=20) (1.58%), colon (n=20) (1.58%), chronic myeloid leukemia (n=17) (1.34%), alveolus (n=17) (1.34%), Hodgkin's (n=14) (1.11%), uterus (n=14) (1.11%), multiple myeloma (n=14) (1.11%), and prostate (n=11) (0.87%) lesions were observed less frequently. Remarkably, gradual increase of cancers on different organs and sites were observed in the long- term survivors and their offspring. The present study observed some cancers which were not previously reported in this population. In addition, we also present the future research directions with systematic approaches to predict cancer risk in long-term survivors and their future generations. On the basis of this morbidity report, we suggest the need of biological surveillance through immune system biomonitoring and cytogenetic screening to predict the cancer risk in the MIC exposed population and their offspring.

The future burden of obesity-related diseases in the 53 WHO European-Region countries and the impact of effective interventions: a modelling study

PubMed Central

Webber, Laura; Divajeva, Diana; Marsh, Tim; McPherson, Klim; Brown, Martin; Galea, Gauden; Breda, Joao

2014-01-01

Objective Non-communicable diseases (NCDs) are the biggest cause of death in Europe putting an unsustainable burden on already struggling health systems. Increases in obesity are a major cause of NCDs. This paper projects the future burden of coronary heart disease (CHD), stroke, type 2 diabetes and seven cancers by 2030 in 53 WHO European Region countries based on current and past body mass index (BMI) trends. It also tests the impact of obesity interventions on the future disease burden. Setting and participants Secondary data analysis of country-specific epidemiological data using a microsimulation modelling process. Interventions The effect of three hypothetical scenarios on the future burden of disease in 2030 was tested: baseline scenario, BMI trends go unchecked; intervention 1, population BMI decreases by 1%; intervention 2, BMI decreases by 5%. Primary and secondary outcome measures Quantifying the future burden of major NCDs and the impact of interventions on this future disease burden. Results By 2030 in the whole of the European region, the prevalence of diabetes, CHD and stroke and cancers was projected to reach an average of 3990, 4672 and 2046 cases/100 000, respectively. The highest prevalence of diabetes was predicted in Slovakia (10 870), CHD and stroke—in Greece (11 292) and cancers—in Finland (5615 cases/100 000). A 5% fall in population BMI was projected to significantly reduce cumulative incidence of diseases. The largest reduction in diabetes and CHD and stroke was observed in Slovakia (3054 and 3369 cases/100 000, respectively), and in cancers was predicted in Germany (331/100 000). Conclusions Modelling future disease trends is a useful tool for policymakers so that they can allocate resources effectively and implement policies to prevent NCDs. Future research will allow real policy interventions to be tested; however, better surveillance data on NCDs and their risk factors are essential for research and policy. PMID:25063459

Population ageing and dental care.

PubMed

Harford, Jane

2009-04-01

Population ageing is a fact in both developed and developing countries. The concern about population ageing largely arises from the combination of a greater number of older people requiring greater amounts of healthcare services and pensions, and relatively fewer people working to pay for them. Oral health and dental care are important aspects of health and health care. Lower rates of edentulism and an ageing population mean that older people will feature more prominently in dental services. Traditionally, economic studies of ageing have focused on the fiscal implications of ageing, projecting the increased burden on health and welfare services that accompanies ageing. It assumed that ageing is the major driver of recent changes and those past trends will simply be amplified by faster population ageing in the future. Less work has been done to understand other past drivers of increased healthcare spending and their implications for the future. The conclusion of these reports is usually that population ageing is unaffordable with current policy settings. They have proposed policies to deal with population ageing which focused on increasing workforce participation and worker productivity to increase the tax base and reducing entitlements. However, the affordability question is as much political as a numerical. There are no clearly articulated criteria for affordability and little opportunity for public discourse about what citizens are willing to pay in taxes to support an ageing population. While the reports do not necessarily reflect public opinion, they will certainly shape it. Predicting the future for oral health is more fraught than for general health, as oral health is in the midst of an epidemiological transition from high rates of edentulism and tooth loss to low rates. Changes in the pattern of dental expenditure in the past do not mirror the experience of rapid increases in per capita expenditure on older age groups as regards general health. Dentistry's marginal status means that less work has been done to understand the future consequences of these changes and how they will interact with population ageing. Further than this though, we need to understand why the future might look as these projections suggest, so that we may look at ways that it can be shaped.

Projections of Water Stress Based on an Ensemble of Socioeconomic Growth and Climate Change Scenarios: A Case Study in Asia

PubMed Central

Fant, Charles; Schlosser, C. Adam; Gao, Xiang; Strzepek, Kenneth; Reilly, John

2016-01-01

The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify the primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region’s population will live in water-stressed regions in the near future. Tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers. PMID:27028871

[Dental manpower prediction in Israel for 2017].

PubMed

Vered, Y; Zini, A; Mann, J

2010-07-01

A recent study published by the authors indicated that according to the Israeli Central Bureau of Statistics in 2008, Israel had 5800 active dentists, a figure well below the publication by the Ministry of Health. Based on this figure, using the manpower to population ratio method, the following results were obtained: The predicted number of dentist in 2017 would be 6090, based on, the estimated number of Israel: graduates, the estimated number of dentists who would arrive in Israel as immigrants or Israelis who studied abroad, based on an attrition rate of 3% and on the assumption that the number of dentists leaving the country is negligible. Table 2, based on manpower to population ratio, indicates that by 2017, Israel would have 1 dentist per 1400 population, a ratio which is still far above what many countries present, but high for Israel. This might reflect a dramatic change, from employment in public clinics, back to private practices. The results clearly indicate that a shortage of dentists is predicted in the near future and a major brainstorming is urgently required to evaluate these results.

Predictions of future ephemeral springtime waterbird stopover habitat availability under global change

USGS Publications Warehouse

Uden, Daniel R.; Allen, Craig R.; Bishop, Andrew A.; Grosse, Roger; Jorgensen, Christopher F.; LaGrange, Theodore G.; Stutheit, Randy G.; Vrtiska, Mark P.

2015-01-01

In the present period of rapid, worldwide change in climate and landuse (i.e., global change), successful biodiversity conservation warrants proactive management responses, especially for long-distance migratory species. However, the development and implementation of management strategies can be impeded by high levels of uncertainty and low levels of control over potentially impactful future events and their effects. Scenario planning and modeling are useful tools for expanding perspectives and informing decisions under these conditions. We coupled scenario planning and statistical modeling to explain and predict playa wetland inundation (i.e., presence/absence of water) and ponded area (i.e., extent of water) in the Rainwater Basin, an anthropogenically altered landscape that provides critical stopover habitat for migratory waterbirds. Inundation and ponded area models for total wetlands, those embedded in rowcrop fields, and those not embedded in rowcrop fields were trained and tested with wetland ponding data from 2004 and 2006–2009, and then used to make additional predictions under two alternative climate change scenarios for the year 2050, yielding a total of six predictive models and 18 prediction sets. Model performance ranged from moderate to good, with inundation models outperforming ponded area models, and models for non-rowcrop-embedded wetlands outperforming models for total wetlands and rowcrop-embedded wetlands. Model predictions indicate that if the temperature and precipitation changes assumed under our climate change scenarios occur, wetland stopover habitat availability in the Rainwater Basin could decrease in the future. The results of this and similar studies could be aggregated to increase knowledge about the potential spatial and temporal distributions of future stopover habitat along migration corridors, and to develop and prioritize multi-scale management actions aimed at mitigating the detrimental effects of global change on migratory waterbird populations.

Prediction Markets and Beliefs about Climate: Results from Agent-Based Simulations

NASA Astrophysics Data System (ADS)

Gilligan, J. M.; John, N. J.; van der Linden, M.

2015-12-01

Climate scientists have long been frustrated by persistent doubts a large portion of the public expresses toward the scientific consensus about anthropogenic global warming. The political and ideological polarization of this doubt led Vandenbergh, Raimi, and Gilligan [1] to propose that prediction markets for climate change might influence the opinions of those who mistrust the scientific community but do trust the power of markets.We have developed an agent-based simulation of a climate prediction market in which traders buy and sell future contracts that will pay off at some future year with a value that depends on the global average temperature at that time. The traders form a heterogeneous population with different ideological positions, different beliefs about anthropogenic global warming, and different degrees of risk aversion. We also vary characteristics of the market, including the topology of social networks among the traders, the number of traders, and the completeness of the market. Traders adjust their beliefs about climate according to the gains and losses they and other traders in their social network experience. This model predicts that if global temperature is predominantly driven by greenhouse gas concentrations, prediction markets will cause traders' beliefs to converge toward correctly accepting anthropogenic warming as real. This convergence is largely independent of the structure of the market and the characteristics of the population of traders. However, it may take considerable time for beliefs to converge. Conversely, if temperature does not depend on greenhouse gases, the model predicts that traders' beliefs will not converge. We will discuss the policy-relevance of these results and more generally, the use of agent-based market simulations for policy analysis regarding climate change, seasonal agricultural weather forecasts, and other applications.[1] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).

Temperature drives abundance fluctuations, but spatial dynamics is constrained by landscape configuration: Implications for climate-driven range shift in a butterfly.

PubMed

Fourcade, Yoan; Ranius, Thomas; Öckinger, Erik

2017-10-01

Prediction of species distributions in an altered climate requires knowledge on how global- and local-scale factors interact to limit their current distributions. Such knowledge can be gained through studies of spatial population dynamics at climatic range margins. Here, using a butterfly (Pyrgus armoricanus) as model species, we first predicted based on species distribution modelling that its climatically suitable habitats currently extend north of its realized range. Projecting the model into scenarios of future climate, we showed that the distribution of climatically suitable habitats may shift northward by an additional 400 km in the future. Second, we used a 13-year monitoring dataset including the majority of all habitat patches at the species northern range margin to assess the synergetic impact of temperature fluctuations and spatial distribution of habitat, microclimatic conditions and habitat quality, on abundance and colonization-extinction dynamics. The fluctuation in abundance between years was almost entirely determined by the variation in temperature during the species larval development. In contrast, colonization and extinction dynamics were better explained by patch area, between-patch connectivity and host plant density. This suggests that the response of the species to future climate change may be limited by future land use and how its host plants respond to climate change. It is, thus, probable that dispersal limitation will prevent P. armoricanus from reaching its potential future distribution. We argue that models of range dynamics should consider the factors influencing metapopulation dynamics, especially at the range edges, and not only broad-scale climate. It includes factors acting at the scale of habitat patches such as habitat quality and microclimate and landscape-scale factors such as the spatial configuration of potentially suitable patches. Knowledge of population dynamics under various environmental conditions, and the incorporation of realistic scenarios of future land use, appears essential to provide predictions useful for actions mitigating the negative effects of climate change. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Dietary Sodium Consumption Predicts Future Blood Pressure and Incident Hypertension in the Japanese Normotensive General Population

PubMed Central

Takase, Hiroyuki; Sugiura, Tomonori; Kimura, Genjiro; Ohte, Nobuyuki; Dohi, Yasuaki

2015-01-01

Background Although there is a close relationship between dietary sodium and hypertension, the concept that persons with relatively high dietary sodium are at increased risk of developing hypertension compared with those with relatively low dietary sodium has not been studied intensively in a cohort. Methods and Results We conducted an observational study to investigate whether dietary sodium intake predicts future blood pressure and the onset of hypertension in the general population. Individual sodium intake was estimated by calculating 24-hour urinary sodium excretion from spot urine in 4523 normotensive participants who visited our hospital for a health checkup. After a baseline examination, they were followed for a median of 1143 days, with the end point being development of hypertension. During the follow-up period, hypertension developed in 1027 participants (22.7%). The risk of developing hypertension was higher in those with higher rather than lower sodium intake (hazard ratio 1.25, 95% CI 1.04 to 1.50). In multivariate Cox proportional hazards regression analysis, baseline sodium intake and the yearly change in sodium intake during the follow-up period (as continuous variables) correlated with the incidence of hypertension. Furthermore, both the yearly increase in sodium intake and baseline sodium intake showed significant correlations with the yearly increase in systolic blood pressure in multivariate regression analysis after adjustment for possible risk factors. Conclusions Both relatively high levels of dietary sodium intake and gradual increases in dietary sodium are associated with future increases in blood pressure and the incidence of hypertension in the Japanese general population. PMID:26224048

Detecting fast radio bursts at decametric wavelengths

NASA Astrophysics Data System (ADS)

Rajwade, K. M.; Lorimer, D. R.

2017-02-01

Fast radio bursts (FRBs) are highly dispersed, sporadic radio pulses which are likely extragalactic in nature. Here, we investigate the constraints on the source population from surveys carried out at frequencies <1 GHz. All but one FRB has so far been discovered in the 1-2 GHz band, but new and emerging instruments look set to become valuable probes of the FRB population at sub-GHz frequencies in the near future. In this paper, we consider the impacts of free-free absorption and multipath scattering in our analysis via a number of different assumptions about the intervening medium. We consider previous low-frequency surveys along with an ongoing survey with University of Technology digital backend for the Molonglo Observatory Synthesis Telescope (UTMOST) as well as future observations with the Canadian Hydrogen Intensity Mapping Experiment (CHIME) and the Hydrogen Intensity and Real-time Analysis eXperiment (HIRAX). We predict that CHIME and HIRAX will be able to observe ˜30 or more FRBs per day, even in the most extreme scenarios where free-free absorption and scattering can significantly impact the fluxes below 1 GHz. We also show that UTMOST will detect 1-2 FRBs per month of observations. For CHIME and HIRAX, the detection rates also depend greatly on the assumed FRB distance scale. Some of the models we investigated predict an increase in the FRB flux as a function of redshift at low frequencies. If FRBs are truly cosmological sources, this effect may impact future surveys in this band, particularly if the FRB population traces the cosmic star formation rate.

Dealing with China's future population decline: a proposal for replacing low birth rates with sustainable rates.

PubMed

Cao, Shixiong; Wang, Xiuqing

2009-09-01

Decreasing population levels due to declining birth rates are becoming a potentially serious social problem in developed and rapidly developing countries. China urgently needed to reduce birth rates so that its population would decline to a sustainable level, and the family planning policy designed to achieve this goal has largely succeeded. However, continuing to pursue this policy is leading to serious, unanticipated problems such as a shift in the country's population distribution towards the elderly and increasing difficulty supporting that elderly population. Social and political changes that promoted low birth rates and the lack of effective policies to encourage higher birth rates suggest that mitigating the consequences of the predicted population decline will depend on a revised approach based on achieving sustainable birth rates.

Irruptive dynamics of introduced caribou on Adak Island, Alaska: an evaluation of Riney-Caughley model predictions

USGS Publications Warehouse

Ricca, Mark A.; Van Vuren, Dirk H.; Weckerly, Floyd W.; Williams, Jeffrey C.; Miles, A. Keith

2014-01-01

Large mammalian herbivores introduced to islands without predators are predicted to undergo irruptive population and spatial dynamics, but only a few well-documented case studies support this paradigm. We used the Riney-Caughley model as a framework to test predictions of irruptive population growth and spatial expansion of caribou (Rangifer tarandus granti) introduced to Adak Island in the Aleutian archipelago of Alaska in 1958 and 1959. We utilized a time series of spatially explicit counts conducted on this population intermittently over a 54-year period. Population size increased from 23 released animals to approximately 2900 animals in 2012. Population dynamics were characterized by two distinct periods of irruptive growth separated by a long time period of relative stability, and the catalyst for the initial irruption was more likely related to annual variation in hunting pressure than weather conditions. An unexpected pattern resembling logistic population growth occurred between the peak of the second irruption in 2005 and the next survey conducted seven years later in 2012. Model simulations indicated that an increase in reported harvest alone could not explain the deceleration in population growth, yet high levels of unreported harvest combined with increasing density-dependent feedbacks on fecundity and survival were the most plausible explanation for the observed population trend. No studies of introduced island Rangifer have measured a time series of spatial use to the extent described in this study. Spatial use patterns during the post-calving season strongly supported Riney-Caughley model predictions, whereby high-density core areas expanded outwardly as population size increased. During the calving season, caribou displayed marked site fidelity across the full range of population densities despite availability of other suitable habitats for calving. Finally, dispersal and reproduction on neighboring Kagalaska Island represented a new dispersal front for irruptive dynamics and a new challenge for resource managers. The future demography of caribou on both islands is far from certain, yet sustained and significant hunting pressure should be a vital management tool.

22 Years of predictive testing for Huntington's disease: the experience of the UK Huntington's Prediction Consortium

PubMed Central

Baig, Sheharyar S; Strong, Mark; Rosser, Elisabeth; Taverner, Nicola V; Glew, Ruth; Miedzybrodzka, Zosia; Clarke, Angus; Craufurd, David; Quarrell, Oliver W

2016-01-01

Huntington's disease (HD) is a progressive neurodegenerative condition. At-risk individuals have accessed predictive testing via direct mutation testing since 1993. The UK Huntington's Prediction Consortium has collected anonymised data on UK predictive tests, annually, from 1993 to 2014: 9407 predictive tests were performed across 23 UK centres. Where gender was recorded, 4077 participants were male (44.3%) and 5122 were female (55.7%). The median age of participants was 37 years. The most common reason for predictive testing was to reduce uncertainty (70.5%). Of the 8441 predictive tests on individuals at 50% prior risk, 4629 (54.8%) were reported as mutation negative and 3790 (44.9%) were mutation positive, with 22 (0.3%) in the database being uninterpretable. Using a prevalence figure of 12.3 × 10−5, the cumulative uptake of predictive testing in the 50% at-risk UK population from 1994 to 2014 was estimated at 17.4% (95% CI: 16.9–18.0%). We present the largest study conducted on predictive testing in HD. Our findings indicate that the vast majority of individuals at risk of HD (>80%) have not undergone predictive testing. Future therapies in HD will likely target presymptomatic individuals; therefore, identifying the at-risk population whose gene status is unknown is of significant public health value. PMID:27165004

Assessing global range expansion in a cryptic species complex: insights from the red seaweed genus Asparagopsis (Florideophyceae).

PubMed

Zanolla, Marianela; Altamirano, María; Carmona, Raquel; De la Rosa, Julio; Souza-Egipsy, Virginia; Sherwood, Alison; Tsiamis, Konstantinos; Barbosa, Ana Márcia; Muñoz, Antonio Román; Andreakis, Nikos

2018-02-01

The mitochondrial genetic diversity, distribution and invasive potential of multiple cryptic operational taxonomic units (OTUs) of the red invasive seaweed Asparagopsis were assessed by studying introduced Mediterranean and Hawaiian populations. Invasive behavior of each Asparagopsis OTU was inferred from phylogeographic reconstructions, past historical demographic dynamics, recent range expansion assessments and future distributional predictions obtained from demographic models. Genealogical networks resolved Asparagopsis gametophytes and tetrasporophytes into four A. taxiformis and one A. armata cryptic OTUs. Falkenbergia isolates of A. taxiformis L3 were recovered for the first time in the western Mediterranean Sea and represent a new introduction for this area. Neutrality statistics supported past range expansion for A. taxiformis L1 and L2 in Hawaii. On the other hand, extreme geographic expansion and an increase in effective population size were found only for A. taxiformis L2 in the western Mediterranean Sea. Distribution models predicted shifts of the climatically suitable areas and population expansion for A. armata L1 and A. taxiformis L1 and L2. Our integrated study confirms a high invasive risk for A. taxiformis L1 and L2 in temperate and tropical areas. Despite the differences in predictions among modelling approaches, a number of regions were identified as zones with high invasion risk for A. taxiformis L2. Since range shifts are likely climate-driven phenomena, future invasive behavior cannot be excluded for the rest of the lineages. © 2017 Phycological Society of America.

Spatial vulnerability of Australian urban populations to extreme heat events

NASA Astrophysics Data System (ADS)

Loughnan, Margaret; Tapper, Nigel; Phan, Thu; Lynch, Kellie; McInnes, Judith

2013-04-01

Extreme heat events pose a risk to the health of all individuals, especially the elderly and the chronically ill, and are associated with an increased demand for healthcare services. In order to address this problem, policy makers' need information about temperatures above which mortality and morbidity of the exposed population is likely to increase, where the vulnerable groups in the community are located, and how the risks from extreme heat events are likely to change in the future. This study identified threshold temperatures for all Australian capital cities, developed a spatial index of population vulnerability, and used climate model output to predict changes in the number of days exceeding temperature thresholds in the future, as well as changes in risk related to changes in urban density and an ageing population. The study has shown that daily maximum and minimum temperatures from the Bureau of Meteorology forecasts can be used to calculate temperature thresholds for heat alert days. The key risk factors related to adverse health outcomes were found to be areas with intense urban heat islands, areas with higher proportions of older people, and areas with ethnic communities. Maps of spatial vulnerability have been developed to provide information to assist emergency managers, healthcare professionals, and ancillary services develop heatwave preparedness plans at a local scale that target vulnerable groups and address heat-related health risks. The numbers of days exceeding current heat thresholds are predicted to increase over the next 20 to 40 years in all Australian capital cities.

Estimating current and future streamflow characteristics at ungaged sites, central and eastern Montana, with application to evaluating effects of climate change on fish populations

USGS Publications Warehouse

Sando, Roy; Chase, Katherine J.

2017-03-23

A common statistical procedure for estimating streamflow statistics at ungaged locations is to develop a relational model between streamflow and drainage basin characteristics at gaged locations using least squares regression analysis; however, least squares regression methods are parametric and make constraining assumptions about the data distribution. The random forest regression method provides an alternative nonparametric method for estimating streamflow characteristics at ungaged sites and requires that the data meet fewer statistical conditions than least squares regression methods.Random forest regression analysis was used to develop predictive models for 89 streamflow characteristics using Precipitation-Runoff Modeling System simulated streamflow data and drainage basin characteristics at 179 sites in central and eastern Montana. The predictive models were developed from streamflow data simulated for current (baseline, water years 1982–99) conditions and three future periods (water years 2021–38, 2046–63, and 2071–88) under three different climate-change scenarios. These predictive models were then used to predict streamflow characteristics for baseline conditions and three future periods at 1,707 fish sampling sites in central and eastern Montana. The average root mean square error for all predictive models was about 50 percent. When streamflow predictions at 23 fish sampling sites were compared to nearby locations with simulated data, the mean relative percent difference was about 43 percent. When predictions were compared to streamflow data recorded at 21 U.S. Geological Survey streamflow-gaging stations outside of the calibration basins, the average mean absolute percent error was about 73 percent.

Meeting the Sustainable Development Goals leads to lower world population growth

PubMed Central

Abel, Guy J.; Barakat, Bilal; KC, Samir; Lutz, Wolfgang

2016-01-01

Here we show the extent to which the expected world population growth could be lowered by successfully implementing the recently agreed-upon Sustainable Development Goals (SDGs). The SDGs include specific quantitative targets on mortality, reproductive health, and education for all girls by 2030, measures that will directly and indirectly affect future demographic trends. Based on a multidimensional model of population dynamics that stratifies national populations by age, sex, and level of education with educational fertility and mortality differentials, we translate these goals into SDG population scenarios, resulting in population sizes between 8.2 and 8.7 billion in 2100. Because these results lie outside the 95% prediction range given by the 2015 United Nations probabilistic population projections, we complement the study with sensitivity analyses of these projections that suggest that those prediction intervals are too narrow because of uncertainty in baseline data, conservative assumptions on correlations, and the possibility of new policies influencing these trends. Although the analysis presented here rests on several assumptions about the implementation of the SDGs and the persistence of educational, fertility, and mortality differentials, it quantitatively illustrates the view that demography is not destiny and that policies can make a decisive difference. In particular, advances in female education and reproductive health can contribute greatly to reducing world population growth. PMID:27911797

Meeting the Sustainable Development Goals leads to lower world population growth.

PubMed

Abel, Guy J; Barakat, Bilal; Kc, Samir; Lutz, Wolfgang

2016-12-13

Here we show the extent to which the expected world population growth could be lowered by successfully implementing the recently agreed-upon Sustainable Development Goals (SDGs). The SDGs include specific quantitative targets on mortality, reproductive health, and education for all girls by 2030, measures that will directly and indirectly affect future demographic trends. Based on a multidimensional model of population dynamics that stratifies national populations by age, sex, and level of education with educational fertility and mortality differentials, we translate these goals into SDG population scenarios, resulting in population sizes between 8.2 and 8.7 billion in 2100. Because these results lie outside the 95% prediction range given by the 2015 United Nations probabilistic population projections, we complement the study with sensitivity analyses of these projections that suggest that those prediction intervals are too narrow because of uncertainty in baseline data, conservative assumptions on correlations, and the possibility of new policies influencing these trends. Although the analysis presented here rests on several assumptions about the implementation of the SDGs and the persistence of educational, fertility, and mortality differentials, it quantitatively illustrates the view that demography is not destiny and that policies can make a decisive difference. In particular, advances in female education and reproductive health can contribute greatly to reducing world population growth.

A projection of lesser prairie chicken (Tympanuchus pallidicinctus) populations range-wide

USGS Publications Warehouse

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.

A validation study of a clinical prediction rule for screening asymptomatic chlamydia and gonorrhoea infections among heterosexuals in British Columbia.

PubMed

Falasinnu, Titilola; Gilbert, Mark; Gustafson, Paul; Shoveller, Jean

2016-02-01

One component of effective sexually transmitted infections (STIs) control is ensuring those at highest risk of STIs have access to clinical services because terminating transmission in this group will prevent most future cases. Here, we describe the results of a validation study of a clinical prediction rule for identifying individuals at increased risk for chlamydia and gonorrhoea infection derived in Vancouver, British Columbia (BC), against a population of asymptomatic patients attending sexual health clinics in other geographical settings in BC. We examined electronic records (2000-2012) from clinic visits at seven sexual health clinics in geographical locations outside Vancouver. The model's calibration and discrimination were examined by the area under the receiver operating characteristic curve (AUC) and the Hosmer-Lemeshow (H-L) statistic, respectively. We also examined the sensitivity and proportion of patients that would need to be screened at different cut-offs of the risk score. The prevalence of infection was 5.3% (n=10 425) in the geographical validation population. The prediction rule showed good performance in this population (AUC, 0.69; H-L p=0.26). Possible risk scores ranged from -2 to 27. We identified a risk score cut-off point of ≥8 that detected cases with a sensitivity of 86% by screening 63% of the geographical validation population. The prediction rule showed good generalisability in STI clinics outside of Vancouver with improved discriminative performance compared with temporal validation. The prediction rule has the potential for augmenting triaging services in STI clinics and enhancing targeted testing in population-based screening programmes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Evolution of marginal populations of an invasive vine increases the likelihood of future spread

Treesearch

Francis F. Kilkenny; Laura F. Galloway

2015-01-01

The prediction of invasion patterns may require an understanding of intraspecific differentiation in invasive species and its interaction with climate change. We compare Japanese honeysuckle (Lonicera japonica) plants from the core (100-150 yr old) and northern margin (< 65 yr old) of their North American invaded range to determine whether evolution...

Comparing methods for measuring the rate of spread of invading populations

Treesearch

Marius Gilbert; Andrew Liebhold

2010-01-01

Measuring rates of spread during biological invasions is important for predicting where and when invading organisms will spread in the future as well as for quantifying the influence of environmental conditions on invasion speed. While several methods have been proposed in the literature to measure spread rates, a comprehensive comparison of their accuracy when applied...

Modeling potential movements of the emerald ash borer: the model framework

Treesearch

Louis R. Iverson; Anantha Prasad; Jonathan Bossenbroek; Davis Sydnor; Mark W. Schwartz

2010-01-01

The emerald ash borer (EAB, Agrilus planipennis Fairmaire) is threatening to decimate native ashes (Fraxinus spp.) across North America and, so far, has devastated ash populations across sections of Michigan, Ohio, Indiana, and Ontario. We are attempting to develop a computer model that will predict EAB future movement by adapting a model developed...

Neither Feast nor Famine: Summary of the Second Twenty Year Forecast Project.

ERIC Educational Resources Information Center

Enzer, Selwyn; And Others

1977-01-01

The key question to ask in determining whether a solution will be found to the world food problem is whether people will learn to effectively manage the food/population balance. Predictions concerning the world food situation should be made on the basis of these factors: (1) possible future changes involving technological development, political…

The 2008-18 Job Outlook in Brief

ERIC Educational Resources Information Center

Occupational Outlook Quarterly, 2010

2010-01-01

Some occupations will fare better than others over the 2008-18 decade. Although it's impossible to predict the future, one can gain insight into job outlook by analyzing trends in population growth, technological advances, and business practices. This insight is helpful in planning a career. Every 2 years, the U.S. Bureau of Labor Statistics (BLS)…

Predicting Effects of Coastal Acidification on Marine Bivalve ...

EPA Pesticide Factsheets

The partial pressure of carbon dioxide (pCO2) is increasing in the oceans and causing changes in seawater pH commonly described as ocean or coastal acidification. It is now well-established that, when reproduced in laboratory experiments, these increases in pCO2 can reduce survival and growth of early life stage bivalves. However, the effects that these impairments would have on whole populations of bivalves are unknown. In this study, these laboratory responses were incorporated into field-parameterized population models to assess population-level sensitivities to acidification for two northeast bivalve species with different life histories: Mercenaria mercenaria (hard clam) and Argopecten irradians (bay scallop). The resulting models permitted translation of laboratory pCO2 response functions into population-level responses to examine population sensitivity to future pCO2 changes. Preliminary results from our models indicate that if the current M. mercenaria negative population growth rate was attributed to the effects of pCO2 on early life stages, the population would decline at a rate of 50% per ten years at 420 microatmospheres (µatm) pCO2. If the current population growth rate was attributed to other additive factors (e.g., harvest, harmful algal blooms), M. mercenaria populations were predicted to decline at a rate of 50% per ten years at the preliminary estimate of 1010 µatm pCO2. The estimated population growth rate was positive for A. irradians,

Combining a weed traits database with a population dynamics model predicts shifts in weed communities.

PubMed

Storkey, J; Holst, N; Bøjer, O Q; Bigongiali, F; Bocci, G; Colbach, N; Dorner, Z; Riemens, M M; Sartorato, I; Sønderskov, M; Verschwele, A

2015-04-01

A functional approach to predicting shifts in weed floras in response to management or environmental change requires the combination of data on weed traits with analytical frameworks that capture the filtering effect of selection pressures on traits. A weed traits database (WTDB) was designed, populated and analysed, initially using data for 19 common European weeds, to begin to consolidate trait data in a single repository. The initial choice of traits was driven by the requirements of empirical models of weed population dynamics to identify correlations between traits and model parameters. These relationships were used to build a generic model, operating at the level of functional traits, to simulate the impact of increasing herbicide and fertiliser use on virtual weeds along gradients of seed weight and maximum height. The model generated 'fitness contours' (defined as population growth rates) within this trait space in different scenarios, onto which two sets of weed species, defined as common or declining in the UK, were mapped. The effect of increasing inputs on the weed flora was successfully simulated; 77% of common species were predicted to have stable or increasing populations under high fertiliser and herbicide use, in contrast with only 29% of the species that have declined. Future development of the WTDB will aim to increase the number of species covered, incorporate a wider range of traits and analyse intraspecific variability under contrasting management and environments.

Using the satellite-derived NDVI to assess ecological responses to environmental change.

PubMed

Pettorelli, Nathalie; Vik, Jon Olav; Mysterud, Atle; Gaillard, Jean-Michel; Tucker, Compton J; Stenseth, Nils Chr

2005-09-01

Assessing how environmental changes affect the distribution and dynamics of vegetation and animal populations is becoming increasingly important for terrestrial ecologists to enable better predictions of the effects of global warming, biodiversity reduction or habitat degradation. The ability to predict ecological responses has often been hampered by our rather limited understanding of trophic interactions. Indeed, it has proven difficult to discern direct and indirect effects of environmental change on animal populations owing to limited information about vegetation at large temporal and spatial scales. The rapidly increasing use of the Normalized Difference Vegetation Index (NDVI) in ecological studies has recently changed this situation. Here, we review the use of the NDVI in recent ecological studies and outline its possible key role in future research of environmental change in an ecosystem context.

VTE Risk assessment - a prognostic Model: BATER Cohort Study of young women.

PubMed

Heinemann, Lothar Aj; Dominh, Thai; Assmann, Anita; Schramm, Wolfgang; Schürmann, Rolf; Hilpert, Jan; Spannagl, Michael

2005-04-18

BACKGROUND: Community-based cohort studies are not available that evaluated the predictive power of both clinical and genetic risk factors for venous thromboembolism (VTE). There is, however, clinical need to forecast the likelihood of future occurrence of VTE, at least qualitatively, to support decisions about intensity of diagnostic or preventive measures. MATERIALS AND METHODS: A 10-year observation period of the Bavarian Thromboembolic Risk (BATER) study, a cohort study of 4337 women (18-55 years), was used to develop a predictive model of VTE based on clinical and genetic variables at baseline (1993). The objective was to prepare a probabilistic scheme that discriminates women with virtually no VTE risk from those at higher levels of absolute VTE risk in the foreseeable future. A multivariate analysis determined which variables at baseline were the best predictors of a future VTE event, provided a ranking according to the predictive power, and permitted to design a simple graphic scheme to assess the individual VTE risk using five predictor variables. RESULTS: Thirty-four new confirmed VTEs occurred during the observation period of over 32,000 women-years (WYs). A model was developed mainly based on clinical information (personal history of previous VTE and family history of VTE, age, BMI) and one composite genetic risk markers (combining Factor V Leiden and Prothrombin G20210A Mutation). Four levels of increasing VTE risk were arbitrarily defined to map the prevalence in the study population: No/low risk of VTE (61.3%), moderate risk (21.1%), high risk (6.0%), very high risk of future VTE (0.9%). In 10.6% of the population the risk assessment was not possible due to lacking VTE cases. The average incidence rates for VTE in these four levels were: 4.1, 12.3, 47.2, and 170.5 per 104 WYs for no, moderate, high, and very high risk, respectively. CONCLUSION: Our prognostic tool - containing clinical information (and if available also genetic data) - seems to be worthwhile testing in medical practice in order to confirm or refute the positive findings of this study. Our cohort study will be continued to include more VTE cases and to increase predictive value of the model.

Clinical history and biologic age predicted falls better than objective functional tests.

PubMed

Gerdhem, Paul; Ringsberg, Karin A M; Akesson, Kristina; Obrant, Karl J

2005-03-01

Fall risk assessment is important because the consequences, such as a fracture, may be devastating. The objective of this study was to find the test or tests that best predicted falls in a population-based sample of elderly women. The fall-predictive ability of a questionnaire, a subjective estimate of biologic age and objective functional tests (gait, balance [Romberg and sway test], thigh muscle strength, and visual acuity) were compared in 984 randomly selected women, all 75 years of age. A recalled fall was the most important predictor for future falls. Only recalled falls and intake of psycho-active drugs independently predicted future falls. Women with at least five of the most important fall predictors (previous falls, conditions affecting the balance, tendency to fall, intake of psychoactive medication, inability to stand on one leg, high biologic age) had an odds ratio of 11.27 (95% confidence interval 4.61-27.60) for a fall (sensitivity 70%, specificity 79%). The more time-consuming objective functional tests were of limited importance for fall prediction. A simple clinical history, the inability to stand on one leg, and a subjective estimate of biologic age were more important as part of the fall risk assessment.

Personalized Cancer Medicine: Molecular Diagnostics, Predictive biomarkers, and Drug Resistance

PubMed Central

Gonzalez de Castro, D; Clarke, P A; Al-Lazikani, B; Workman, P

2013-01-01

The progressive elucidation of the molecular pathogenesis of cancer has fueled the rational development of targeted drugs for patient populations stratified by genetic characteristics. Here we discuss general challenges relating to molecular diagnostics and describe predictive biomarkers for personalized cancer medicine. We also highlight resistance mechanisms for epidermal growth factor receptor (EGFR) kinase inhibitors in lung cancer. We envisage a future requiring the use of longitudinal genome sequencing and other omics technologies alongside combinatorial treatment to overcome cellular and molecular heterogeneity and prevent resistance caused by clonal evolution. PMID:23361103

Projecting the Demand for Dental Care in 2040.

PubMed

Manski, Richard J; Meyerhoefer, Chad D

2017-08-01

The purpose of this study was to provide a forward-thinking assessment of the underlying factors likely to impact trends in dental care demand and the need for dental providers in 2020, 2025, and beyond. Dental workforce trends and their likely impact on the need for dentists are a function of predicted dental care demand, which will in turn be determined by the size and characteristics of our population size, economic outlook, the state of public and private dental care insurance, trends in dental care delivery, professionally determined dental care need, and population health beliefs. Projecting rates of dental care utilization far into the future is difficult because projections must be made using historical data, and established trends may not persist if there is structural change in the future. Nonetheless, when structural change occurs, it does not typically affect all aspects of the economy, so there is value in describing the likely future impact of current trends. This article was written as part of the project "Advancing Dental Education in the 21 st Century."

Black and white and read all over: the past, present and future of giant panda genetics.

PubMed

Wei, Fuwen; Hu, Yibo; Zhu, Lifeng; Bruford, Michael W; Zhan, Xiangjiang; Zhang, Lei

2012-12-01

Few species attract much more attention from the public and scientists than the giant panda (Ailuropoda melanoleuca), a popular, enigmatic but highly endangered species. The application of molecular genetics to its biology and conservation has facilitated surprising insights into the biology of giant pandas as well as the effectiveness of conservation efforts during the past decades. Here, we review the history of genetic advances in this species, from phylogeny, demographical history, genetic variation, population structure, noninvasive population census and adaptive evolution to reveal to what extent the current status of the giant panda is a reflection of its evolutionary legacy, as opposed to the influence of anthropogenic factors that have negatively impacted this species. In addition, we summarize the conservation implications of these genetic findings applied for the management of this high-profile species. Finally, on the basis of these advances and predictable future changes in genetic technology, we discuss future research directions that seem promising for giant panda biology and conservation. © 2012 Blackwell Publishing Ltd.

Global-change vulnerability of a key plant resource, the African palms.

PubMed

Blach-Overgaard, Anne; Balslev, Henrik; Dransfield, John; Normand, Signe; Svenning, Jens-Christian

2015-07-27

Palms are keystone species in tropical ecosystems and provide essential ecosystem services to rural people worldwide. However, many palm species are threatened by habitat loss and over-exploitation. Furthermore, palms are sensitive to climate and thus vulnerable to future climate changes. Here, we provide a first quantitative assessment of the future risks to the African palm flora, finding that African palm species on average may experience a decline in climatic suitability in >70% of their current ranges by 2080. This suitability loss may, however, be almost halved if migration to nearby climatically suitable sites succeeds. Worryingly, 42% of the areas with 80-100% of species losing climate suitability are also characterized by high human population density (HPD). By 2080, >90% of all African palm species' ranges will likely occur at HPDs leading to increased risks of habitat loss and overexploitation. Additionally, up to 87% of all species are predicted to lose climatic suitability within current protected areas (PAs) by 2080. In summary, a major plant component of tropical ecosystems and provider of ecosystem services to rural populations will face strongly increased pressures from climate change and human populations in the near future.

Mathematical modelling methodologies in predictive food microbiology: a SWOT analysis.

PubMed

Ferrer, Jordi; Prats, Clara; López, Daniel; Vives-Rego, Josep

2009-08-31

Predictive microbiology is the area of food microbiology that attempts to forecast the quantitative evolution of microbial populations over time. This is achieved to a great extent through models that include the mechanisms governing population dynamics. Traditionally, the models used in predictive microbiology are whole-system continuous models that describe population dynamics by means of equations applied to extensive or averaged variables of the whole system. Many existing models can be classified by specific criteria. We can distinguish between survival and growth models by seeing whether they tackle mortality or cell duplication. We can distinguish between empirical (phenomenological) models, which mathematically describe specific behaviour, and theoretical (mechanistic) models with a biological basis, which search for the underlying mechanisms driving already observed phenomena. We can also distinguish between primary, secondary and tertiary models, by examining their treatment of the effects of external factors and constraints on the microbial community. Recently, the use of spatially explicit Individual-based Models (IbMs) has spread through predictive microbiology, due to the current technological capacity of performing measurements on single individual cells and thanks to the consolidation of computational modelling. Spatially explicit IbMs are bottom-up approaches to microbial communities that build bridges between the description of micro-organisms at the cell level and macroscopic observations at the population level. They provide greater insight into the mesoscale phenomena that link unicellular and population levels. Every model is built in response to a particular question and with different aims. Even so, in this research we conducted a SWOT (Strength, Weaknesses, Opportunities and Threats) analysis of the different approaches (population continuous modelling and Individual-based Modelling), which we hope will be helpful for current and future researchers.

Beyond climate envelopes: effects of weather on regional population trends in butterflies.

PubMed

WallisDeVries, Michiel F; Baxter, Wendy; Van Vliet, Arnold J H

2011-10-01

Although the effects of climate change on biodiversity are increasingly evident by the shifts in species ranges across taxonomical groups, the underlying mechanisms affecting individual species are still poorly understood. The power of climate envelopes to predict future ranges has been seriously questioned in recent studies. Amongst others, an improved understanding of the effects of current weather on population trends is required. We analysed the relation between butterfly abundance and the weather experienced during the life cycle for successive years using data collected within the framework of the Dutch Butterfly Monitoring Scheme for 40 species over a 15-year period and corresponding climate data. Both average and extreme temperature and precipitation events were identified, and multiple regression was applied to explain annual changes in population indices. Significant weather effects were obtained for 39 species, with the most frequent effects associated with temperature. However, positive density-dependence suggested climatic independent trends in at least 12 species. Validation of the short-term predictions revealed a good potential for climate-based predictions of population trends in 20 species. Nevertheless, data from the warm and dry year of 2003 indicate that negative effects of climatic extremes are generally underestimated for habitat specialists in drought-susceptible habitats, whereas generalists remain unaffected. Further climatic warming is expected to influence the trends of 13 species, leading to an improvement for nine species, but a continued decline in the majority of species. Expectations from climate envelope models overestimate the positive effects of climate change in northwestern Europe. Our results underline the challenge to include population trends in predicting range shifts in response to climate change.

Ecological genomics predicts climate vulnerability in an endangered southwestern songbird.

PubMed

Ruegg, Kristen; Bay, Rachael A; Anderson, Eric C; Saracco, James F; Harrigan, Ryan J; Whitfield, Mary; Paxton, Eben H; Smith, Thomas B

2018-05-09

Few regions have been more severely impacted by climate change in the USA than the Desert Southwest. Here, we use ecological genomics to assess the potential for adaptation to rising global temperatures in a widespread songbird, the willow flycatcher (Empidonax traillii), and find the endangered desert southwestern subspecies (E. t. extimus) most vulnerable to future climate change. Highly significant correlations between present abundance and estimates of genomic vulnerability - the mismatch between current and predicted future genotype-environment relationships - indicate small, fragmented populations of the southwestern willow flycatcher will have to adapt most to keep pace with climate change. Links between climate-associated genotypes and genes important to thermal tolerance in birds provide a potential mechanism for adaptation to temperature extremes. Our results demonstrate that the incorporation of genotype-environment relationships into landscape-scale models of climate vulnerability can facilitate more precise predictions of climate impacts and help guide conservation in threatened and endangered groups. © 2018 John Wiley & Sons Ltd/CNRS.

Distribution and Numbers of Pygmies in Central African Forests

PubMed Central

Olivero, Jesús; Fa, John E.; Farfán, Miguel A.; Lewis, Jerome; Hewlett, Barry; Breuer, Thomas; Carpaneto, Giuseppe M.; Fernández, María; Germi, Francesco; Hattori, Shiho; Head, Josephine; Ichikawa, Mitsuo; Kitanaishi, Koichi; Knights, Jessica; Matsuura, Naoki; Migliano, Andrea; Nese, Barbara; Noss, Andrew; Ekoumou, Dieudonné Ongbwa; Paulin, Pascale; Real, Raimundo; Riddell, Mike; Stevenson, Edward G. J.; Toda, Mikako; Vargas, J. Mario; Yasuoka, Hirokazu; Nasi, Robert

2016-01-01

Pygmy populations occupy a vast territory extending west-to-east along the central African belt from the Congo Basin to Lake Victoria. However, their numbers and actual distribution is not known precisely. Here, we undertake this task by using locational data and population sizes for an unprecedented number of known Pygmy camps and settlements (n = 654) in five of the nine countries where currently distributed. With these data we develop spatial distribution models based on the favourability function, which distinguish areas with favourable environmental conditions from those less suitable for Pygmy presence. Highly favourable areas were significantly explained by presence of tropical forests, and by lower human pressure variables. For documented Pygmy settlements, we use the relationship between observed population sizes and predicted favourability values to estimate the total Pygmy population throughout Central Africa. We estimate that around 920,000 Pygmies (over 60% in DRC) is possible within favourable forest areas in Central Africa. We argue that fragmentation of the existing Pygmy populations, alongside pressure from extractive industries and sometimes conflict with conservation areas, endanger their future. There is an urgent need to inform policies that can mitigate against future external threats to these indigenous peoples’ culture and lifestyles. PMID:26735953

Distribution and Numbers of Pygmies in Central African Forests.

PubMed

Olivero, Jesús; Fa, John E; Farfán, Miguel A; Lewis, Jerome; Hewlett, Barry; Breuer, Thomas; Carpaneto, Giuseppe M; Fernández, María; Germi, Francesco; Hattori, Shiho; Head, Josephine; Ichikawa, Mitsuo; Kitanaishi, Koichi; Knights, Jessica; Matsuura, Naoki; Migliano, Andrea; Nese, Barbara; Noss, Andrew; Ekoumou, Dieudonné Ongbwa; Paulin, Pascale; Real, Raimundo; Riddell, Mike; Stevenson, Edward G J; Toda, Mikako; Vargas, J Mario; Yasuoka, Hirokazu; Nasi, Robert

2016-01-01

Pygmy populations occupy a vast territory extending west-to-east along the central African belt from the Congo Basin to Lake Victoria. However, their numbers and actual distribution is not known precisely. Here, we undertake this task by using locational data and population sizes for an unprecedented number of known Pygmy camps and settlements (n = 654) in five of the nine countries where currently distributed. With these data we develop spatial distribution models based on the favourability function, which distinguish areas with favourable environmental conditions from those less suitable for Pygmy presence. Highly favourable areas were significantly explained by presence of tropical forests, and by lower human pressure variables. For documented Pygmy settlements, we use the relationship between observed population sizes and predicted favourability values to estimate the total Pygmy population throughout Central Africa. We estimate that around 920,000 Pygmies (over 60% in DRC) is possible within favourable forest areas in Central Africa. We argue that fragmentation of the existing Pygmy populations, alongside pressure from extractive industries and sometimes conflict with conservation areas, endanger their future. There is an urgent need to inform policies that can mitigate against future external threats to these indigenous peoples' culture and lifestyles.

Decadal-scale variation in diet forecasts persistently poor breeding under ocean warming in a tropical seabird

PubMed Central

Tompkins, Emily M.; Townsend, Howard M.

2017-01-01

Climate change effects on population dynamics of natural populations are well documented at higher latitudes, where relatively rapid warming illuminates cause-effect relationships, but not in the tropics and especially the marine tropics, where warming has been slow. Here we forecast the indirect effect of ocean warming on a top predator, Nazca boobies in the equatorial Galápagos Islands, where rising water temperature is expected to exceed the upper thermal tolerance of a key prey item in the future, severely reducing its availability within the boobies’ foraging envelope. From 1983 to 1997 boobies ate mostly sardines, a densely aggregated, highly nutritious food. From 1997 until the present, flying fish, a lower quality food, replaced sardines. Breeding success under the poor diet fell dramatically, causing the population growth rate to fall below 1, indicating a shrinking population. Population growth may not recover: rapid future warming is predicted around Galápagos, usually exceeding the upper lethal temperature and maximum spawning temperature of sardines within 100 years, displacing them permanently from the boobies’ island-constrained foraging range. This provides rare evidence of the effect of ocean warming on a tropical marine vertebrate. PMID:28832597

Decadal-scale variation in diet forecasts persistently poor breeding under ocean warming in a tropical seabird.

PubMed

Tompkins, Emily M; Townsend, Howard M; Anderson, David J

2017-01-01

Climate change effects on population dynamics of natural populations are well documented at higher latitudes, where relatively rapid warming illuminates cause-effect relationships, but not in the tropics and especially the marine tropics, where warming has been slow. Here we forecast the indirect effect of ocean warming on a top predator, Nazca boobies in the equatorial Galápagos Islands, where rising water temperature is expected to exceed the upper thermal tolerance of a key prey item in the future, severely reducing its availability within the boobies' foraging envelope. From 1983 to 1997 boobies ate mostly sardines, a densely aggregated, highly nutritious food. From 1997 until the present, flying fish, a lower quality food, replaced sardines. Breeding success under the poor diet fell dramatically, causing the population growth rate to fall below 1, indicating a shrinking population. Population growth may not recover: rapid future warming is predicted around Galápagos, usually exceeding the upper lethal temperature and maximum spawning temperature of sardines within 100 years, displacing them permanently from the boobies' island-constrained foraging range. This provides rare evidence of the effect of ocean warming on a tropical marine vertebrate.

Future Cognitive Ability: US IQ Prediction until 2060 Based on NAEP.

PubMed

Rindermann, Heiner; Pichelmann, Stefan

2015-01-01

The US National Assessment of Educational Progress (NAEP) measures cognitive competences in reading and mathematics of US students (last 2012 survey N = 50,000). The long-term development based on results from 1971 to 2012 allows a prediction of future cognitive trends. For predicting US averages also demographic trends have to be considered. The largest groups' (White) average of 1978/80 was set at M = 100 and SD = 15 and was used as a benchmark. Based on two past NAEP development periods for 17-year-old students, 1978/80 to 2012 (more optimistic) and 1992 to 2012 (more pessimistic), and demographic projections from the US Census Bureau, cognitive trends until 2060 for the entire age cohort and ethnic groups were estimated. Estimated population averages for 2060 are 103 (optimistic) or 102 (pessimistic). The average rise per decade is dec = 0.76 or 0.45 IQ points. White-Black and White-Hispanic gaps are declining by half, Asian-White gaps treble. The catch-up of minorities (their faster ability growth) contributes around 2 IQ to the general rise of 3 IQ; however, their larger demographic increase reduces the general rise at about the similar amount (-1.4 IQ). Because minorities with faster ability growth also rise in their population proportion the interactive term is positive (around 1 IQ). Consequences for economic and societal development are discussed.

Future Cognitive Ability: US IQ Prediction until 2060 Based on NAEP

PubMed Central

2015-01-01

The US National Assessment of Educational Progress (NAEP) measures cognitive competences in reading and mathematics of US students (last 2012 survey N = 50,000). The long-term development based on results from 1971 to 2012 allows a prediction of future cognitive trends. For predicting US averages also demographic trends have to be considered. The largest groups’ (White) average of 1978/80 was set at M = 100 and SD = 15 and was used as a benchmark. Based on two past NAEP development periods for 17-year-old students, 1978/80 to 2012 (more optimistic) and 1992 to 2012 (more pessimistic), and demographic projections from the US Census Bureau, cognitive trends until 2060 for the entire age cohort and ethnic groups were estimated. Estimated population averages for 2060 are 103 (optimistic) or 102 (pessimistic). The average rise per decade is dec = 0.76 or 0.45 IQ points. White-Black and White-Hispanic gaps are declining by half, Asian-White gaps treble. The catch-up of minorities (their faster ability growth) contributes around 2 IQ to the general rise of 3 IQ; however, their larger demographic increase reduces the general rise at about the similar amount (-1.4 IQ). Because minorities with faster ability growth also rise in their population proportion the interactive term is positive (around 1 IQ). Consequences for economic and societal development are discussed. PMID:26460731

Projections of water stress based on an ensemble of socioeconomic growth and climate change scenarios: A case study in Asia

DOE PAGES

Fant, Charles; Schlosser, C. Adam; Gao, Xiang; ...

2016-03-30

The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in current methods to estimate these factors in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia in a future with unconstrained emissions. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify themore » primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. There is strong evidence to suggest that, in the absence of autonomous adaptation or societal response, a much larger portion of the region’s population will live in water-stressed regions in the near future. Lastly, tools and studies such as these can effectively investigate large-scale system sensitivities and can be useful in engaging and informing decision makers.« less

Comparing the reliability of related populations with the probability of agreement

DOE PAGES

Stevens, Nathaniel T.; Anderson-Cook, Christine M.

2016-07-26

Combining information from different populations to improve precision, simplify future predictions, or improve underlying understanding of relationships can be advantageous when considering the reliability of several related sets of systems. Using the probability of agreement to help quantify the similarities of populations can help to give a realistic assessment of whether the systems have reliability that are sufficiently similar for practical purposes to be treated as a homogeneous population. In addition, the new method is described and illustrated with an example involving two generations of a complex system where the reliability is modeled using either a logistic or probit regressionmore » model. Note that supplementary materials including code, datasets, and added discussion are available online.« less

Comparing the reliability of related populations with the probability of agreement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stevens, Nathaniel T.; Anderson-Cook, Christine M.

Combining information from different populations to improve precision, simplify future predictions, or improve underlying understanding of relationships can be advantageous when considering the reliability of several related sets of systems. Using the probability of agreement to help quantify the similarities of populations can help to give a realistic assessment of whether the systems have reliability that are sufficiently similar for practical purposes to be treated as a homogeneous population. In addition, the new method is described and illustrated with an example involving two generations of a complex system where the reliability is modeled using either a logistic or probit regressionmore » model. Note that supplementary materials including code, datasets, and added discussion are available online.« less

Incorporating exposure to pitch canker disease to support management decisions of Pinus pinaster Ait. in the face of climate change.

PubMed

Serra-Varela, María Jesús; Alía, Ricardo; Pórtoles, Javier; Gonzalo, Julián; Soliño, Mario; Grivet, Delphine; Raposo, Rosa

2017-01-01

Climate change is gravely affecting forest ecosystems, resulting in large distribution shifts as well as in increasing infection diseases and biological invasions. Accordingly, forest management requires an evaluation of exposure to climate change that should integrate both its abiotic and biotic components. Here we address the implications of climate change in an emerging disease by analysing both the host species (Pinus pinaster, Maritime pine) and the pathogen's (Fusarium circinatum, pitch canker) environmental suitability i.e. estimating the host's risk of habitat loss and the disease`s future environmental range. We constrained our study area to the Spanish Iberian Peninsula, where accurate climate and pitch canker occurrence databases were available. While P. pinaster is widely distributed across the study area, the disease has only been detected in its north-central and north-western edges. We fitted species distribution models for the current distribution of the conifer and the disease. Then, these models were projected into nine Global Climate Models and two different climatic scenarios which totalled to 18 different future climate predictions representative of 2050. Based on the level of agreement among them, we created future suitability maps for the pine and for the disease independently, which were then used to assess exposure of current populations of P. pinaster to abiotic and biotic effects of climate change. Almost the entire distribution of P. pinaster in the Spanish Iberian Peninsula will be subjected to abiotic exposure likely to be driven by the predicted increase in drought events in the future. Furthermore, we detected a reduction in exposure to pitch canker that will be concentrated along the north-western edge of the study area. Setting up breeding programs is recommended in highly exposed and productive populations, while silvicultural methods and monitoring should be applied in those less productive, but still exposed, populations.

Incorporating exposure to pitch canker disease to support management decisions of Pinus pinaster Ait. in the face of climate change

PubMed Central

Serra-Varela, María Jesús; Alía, Ricardo; Pórtoles, Javier; Gonzalo, Julián; Soliño, Mario; Grivet, Delphine; Raposo, Rosa

2017-01-01

Climate change is gravely affecting forest ecosystems, resulting in large distribution shifts as well as in increasing infection diseases and biological invasions. Accordingly, forest management requires an evaluation of exposure to climate change that should integrate both its abiotic and biotic components. Here we address the implications of climate change in an emerging disease by analysing both the host species (Pinus pinaster, Maritime pine) and the pathogen’s (Fusarium circinatum, pitch canker) environmental suitability i.e. estimating the host’s risk of habitat loss and the disease`s future environmental range. We constrained our study area to the Spanish Iberian Peninsula, where accurate climate and pitch canker occurrence databases were available. While P. pinaster is widely distributed across the study area, the disease has only been detected in its north-central and north-western edges. We fitted species distribution models for the current distribution of the conifer and the disease. Then, these models were projected into nine Global Climate Models and two different climatic scenarios which totalled to 18 different future climate predictions representative of 2050. Based on the level of agreement among them, we created future suitability maps for the pine and for the disease independently, which were then used to assess exposure of current populations of P. pinaster to abiotic and biotic effects of climate change. Almost the entire distribution of P. pinaster in the Spanish Iberian Peninsula will be subjected to abiotic exposure likely to be driven by the predicted increase in drought events in the future. Furthermore, we detected a reduction in exposure to pitch canker that will be concentrated along the north-western edge of the study area. Setting up breeding programs is recommended in highly exposed and productive populations, while silvicultural methods and monitoring should be applied in those less productive, but still exposed, populations. PMID:28192454

Combining Satellite Measurements and Numerical Flood Prediction Models to Save Lives and Property from Flooding

NASA Astrophysics Data System (ADS)

Saleh, F.; Garambois, P. A.; Biancamaria, S.

2017-12-01

Floods are considered the major natural threats to human societies across all continents. Consequences of floods in highly populated areas are more dramatic with losses of human lives and substantial property damage. This risk is projected to increase with the effects of climate change, particularly sea-level rise, increasing storm frequencies and intensities and increasing population and economic assets in such urban watersheds. Despite the advances in computational resources and modeling techniques, significant gaps exist in predicting complex processes and accurately representing the initial state of the system. Improving flood prediction models and data assimilation chains through satellite has become an absolute priority to produce accurate flood forecasts with sufficient lead times. The overarching goal of this work is to assess the benefits of the Surface Water Ocean Topography SWOT satellite data from a flood prediction perspective. The near real time methodology is based on combining satellite data from a simulator that mimics the future SWOT data, numerical models, high resolution elevation data and real-time local measurement in the New York/New Jersey area.

New formulae for estimating stature in the Balkans.

PubMed

Ross, Ann H; Konigsberg, Lyle W

2002-01-01

Recent studies of secular change and allometry have observed differential limb proportions between the sexes, among and within populations. These studies suggest that stature prediction formulae developed from American Whites may be inappropriate for European populations. The purpose of this investigation is to present more appropriate stature prediction equations for use in the Balkans to aid present-day identifications of the victims of genocide. The reference sample totals 545 white males obtained from World War II data. The Eastern European sample totals 177 males and includes both Bosnian and Croatian victims of the recent war. Mean stature for Eastern Europeans was obtained from the literature. Results show that formulae based on Trotter and Gleser systematically underestimate stature in the Balkans. Because Eastern Europeans are taller than American Whites it is appropriate to use this as an "informative prior" that can be applied to future cases. This informative prior can be used in predictive formulae, since it is probably similar to the sample from which the Balkan forensic cases were drawn. Based on Bayes' Theorem new predictive stature formulae are presented for Eastern Europeans.

Modelling the impacts of global change on concentrations of Escherichia coli in an urban river

NASA Astrophysics Data System (ADS)

Jalliffier-Verne, Isabelle; Leconte, Robert; Huaringa-Alvarez, Uriel; Heniche, Mourad; Madoux-Humery, Anne-Sophie; Autixier, Laurène; Galarneau, Martine; Servais, Pierre; Prévost, Michèle; Dorner, Sarah

2017-10-01

Discharges of combined sewer system overflows (CSOs) affect water quality in drinking water sources despite increasing regulation and discharge restrictions. A hydrodynamic model was applied to simulate the transport and dispersion of fecal contaminants from CSO discharges and to quantify the impacts of climate and population changes on the water quality of the river used as a drinking water source in Québec, Canada. The dispersion model was used to quantify Escherichia coli (E. coli) concentrations at drinking water intakes. Extreme flows during high and low water events were based on a frequency analysis in current and future climate scenarios. The increase of the number of discharges was quantified in current and future climate scenarios with regards to the frequency of overflows observed between 2009 and 2012. For future climate scenarios, effects of an increase of population were estimated according to current population growth statistics, independently of local changes in precipitation that are more difficult to predict than changes to regional scale hydrology. Under ;business-as-usual; scenarios restricting increases in CSO discharge frequency, mean E. coli concentrations at downstream drinking water intakes are expected to increase by up to 87% depending on the future climate scenario and could lead to changes in drinking water treatment requirements for the worst case scenarios. The greatest uncertainties are related to future local discharge loads. Climate change adaptation with regards to drinking water quality must focus on characterizing the impacts of global change at a local scale. Source water protection planning must consider the impacts of climate and population change to avoid further degradation of water quality.

A prediction algorithm for first onset of major depression in the general population: development and validation.

PubMed

Wang, JianLi; Sareen, Jitender; Patten, Scott; Bolton, James; Schmitz, Norbert; Birney, Arden

2014-05-01

Prediction algorithms are useful for making clinical decisions and for population health planning. However, such prediction algorithms for first onset of major depression do not exist. The objective of this study was to develop and validate a prediction algorithm for first onset of major depression in the general population. Longitudinal study design with approximate 3-year follow-up. The study was based on data from a nationally representative sample of the US general population. A total of 28 059 individuals who participated in Waves 1 and 2 of the US National Epidemiologic Survey on Alcohol and Related Conditions and who had not had major depression at Wave 1 were included. The prediction algorithm was developed using logistic regression modelling in 21 813 participants from three census regions. The algorithm was validated in participants from the 4th census region (n=6246). Major depression occurred since Wave 1 of the National Epidemiologic Survey on Alcohol and Related Conditions, assessed by the Alcohol Use Disorder and Associated Disabilities Interview Schedule-diagnostic and statistical manual for mental disorders IV. A prediction algorithm containing 17 unique risk factors was developed. The algorithm had good discriminative power (C statistics=0.7538, 95% CI 0.7378 to 0.7699) and excellent calibration (F-adjusted test=1.00, p=0.448) with the weighted data. In the validation sample, the algorithm had a C statistic of 0.7259 and excellent calibration (Hosmer-Lemeshow χ(2)=3.41, p=0.906). The developed prediction algorithm has good discrimination and calibration capacity. It can be used by clinicians, mental health policy-makers and service planners and the general public to predict future risk of having major depression. The application of the algorithm may lead to increased personalisation of treatment, better clinical decisions and more optimal mental health service planning.

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

NASA Technical Reports Server (NTRS)

Viken, Jeff; Dollyhigh, Samuel; Smith, Jeremy; Trani, Antonio; Baik, Hojong; Hinze, Nicholas; Ashiabor, Senanu

2006-01-01

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Rapid ongoing decline of Baird's tapir in Cusuco National Park, Honduras.

PubMed

McCANN, Niall P; Wheeler, Phil M; Coles, Tim; Bruford, Michael W

2012-12-01

During the International Tapir Symposium 16-21 Oct 2011, the conservation of Baird's tapir (Tapirus bairdii) in Honduras received a boost with the signing of a memorandum of understanding between the Minister Director of the Honduran Institute of Conservation and Forestry (ICF) and the Tapir Specialist Group (TSG). Despite this agreement, accelerating levels of hunting and habitat loss continue to pose a threat to Baird's tapir in Honduras. An ongoing study in Cusuco National Park in northwestern Honduras has been monitoring changes in population dynamics of Baird's tapir since 2006 through the collection of occupancy data. The study has identified an increase in hunting pressure, coinciding with a drastic decline in the encounter rate with Baird's tapir spoor. Here, we examine the significance of a range of demographic variables on Baird's tapir occupancy in Cusuco National Park using the software PRESENCE, and simulate the effects of different management strategies on the future dynamics of the population using the stochastic simulation software VORTEX. The predictions of the theoretical population models are compared to observed changes in occupancy levels. We found that non-intervention resulted in the local extinction of Baird's tapir within a very short time frame, but that various intervention models enabled the population to recover to near carrying capacity. Occupancy and extinction probability were shown to respond markedly to the increase in hunting pressure; and occupancy models supported the future population predictions generated by VORTEX. Our study suggests that immediate intervention is required to reduce hunting pressure to near historical levels to prevent the imminent local extinction of the species. © 2012 Wiley Publishing Asia Pty Ltd, ISZS and IOZ/CAS.

Estimation of Future PM2.5- and Ozone-related Mortality over the Continental United States in a Changing Climate: An application of High-resolution Dynamical Downscaling Technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Jian; Fu, Joshua S.; Huang, Kan

This paper evaluates the PM2.5- and ozone-related mortality at present (2000s) and in the future (2050s) over the continental United States by using the Environmental Benefits Mapping and Analysis Program (BenMAP-CE). Atmospheric chemical fields are simulated by WRF/CMAQ (horizontal resolution: 12 × 12km), applying the dynamical downscaling technique from global climate-chemistry models under the Representative Concentration Pathways scenario (RCP 8.5). Future air quality results predict that the annual mean PM2.5 concentrations in continental US will decrease nationwide, especially in the eastern US and west coast. However, the ozone concentration is projected to decrease in the Eastern US but increase inmore » the Western US. Future mortality is evaluated under two scenarios (1) holding future population and baseline incidence rate at the present level and (2) decreasing the future baseline incidence rate but increasing the future population. For PM2.5, the entire continental US presents a decreasing trend of PM2.5-related mortality by the 2050s in Scenario (1), primarily resulting from the emissions reduction. While in Scenario (2), almost half of the continental states show a rising tendency of PM2.5-related mortality, due to the dominant influence of population growth. In particular, the highest PM2.5-related deaths and the biggest discrepancy between present and future PM2.5-related deaths will both occur in California in 2050s. For the ozone-related premature mortality, the simulation shows nation-wide rising tendency in 2050s under both two scenarios, mainly due to the increase of ozone concentration and population in the future. Furthermore, the uncertainty analysis shows that the effect of the all causes mortality is much larger than for specific causes. This assessment is the result of the accumulated uncertainty of generating datasets. The uncertainty range of ozone-related all cause premature mortality is narrower than the PM2.5-related all cause mortality, due to its smaller standard deviation of beta parameter.« less

The predicted influence of climate change on lesser prairie-chicken reproductive parameters

USGS Publications Warehouse

Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, D.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Nina events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

The predicted influence of climate change on lesser prairie-chicken reproductive parameters.

PubMed

Grisham, Blake A; Boal, Clint W; Haukos, David A; Davis, Dawn M; Boydston, Kathy K; Dixon, Charles; Heck, Willard R

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

Online Prediction of Health Care Utilization in the Next Six Months Based on Electronic Health Record Information: A Cohort and Validation Study.

PubMed

Hu, Zhongkai; Hao, Shiying; Jin, Bo; Shin, Andrew Young; Zhu, Chunqing; Huang, Min; Wang, Yue; Zheng, Le; Dai, Dorothy; Culver, Devore S; Alfreds, Shaun T; Rogow, Todd; Stearns, Frank; Sylvester, Karl G; Widen, Eric; Ling, Xuefeng

2015-09-22

The increasing rate of health care expenditures in the United States has placed a significant burden on the nation's economy. Predicting future health care utilization of patients can provide useful information to better understand and manage overall health care deliveries and clinical resource allocation. This study developed an electronic medical record (EMR)-based online risk model predictive of resource utilization for patients in Maine in the next 6 months across all payers, all diseases, and all demographic groups. In the HealthInfoNet, Maine's health information exchange (HIE), a retrospective cohort of 1,273,114 patients was constructed with the preceding 12-month EMR. Each patient's next 6-month (between January 1, 2013 and June 30, 2013) health care resource utilization was retrospectively scored ranging from 0 to 100 and a decision tree-based predictive model was developed. Our model was later integrated in the Maine HIE population exploration system to allow a prospective validation analysis of 1,358,153 patients by forecasting their next 6-month risk of resource utilization between July 1, 2013 and December 31, 2013. Prospectively predicted risks, on either an individual level or a population (per 1000 patients) level, were consistent with the next 6-month resource utilization distributions and the clinical patterns at the population level. Results demonstrated the strong correlation between its care resource utilization and our risk scores, supporting the effectiveness of our model. With the online population risk monitoring enterprise dashboards, the effectiveness of the predictive algorithm has been validated by clinicians and caregivers in the State of Maine. The model and associated online applications were designed for tracking the evolving nature of total population risk, in a longitudinal manner, for health care resource utilization. It will enable more effective care management strategies driving improved patient outcomes.

Online Prediction of Health Care Utilization in the Next Six Months Based on Electronic Health Record Information: A Cohort and Validation Study

PubMed Central

Hu, Zhongkai; Hao, Shiying; Jin, Bo; Shin, Andrew Young; Zhu, Chunqing; Huang, Min; Wang, Yue; Zheng, Le; Dai, Dorothy; Culver, Devore S; Alfreds, Shaun T; Rogow, Todd; Stearns, Frank

2015-01-01

Background The increasing rate of health care expenditures in the United States has placed a significant burden on the nation’s economy. Predicting future health care utilization of patients can provide useful information to better understand and manage overall health care deliveries and clinical resource allocation. Objective This study developed an electronic medical record (EMR)-based online risk model predictive of resource utilization for patients in Maine in the next 6 months across all payers, all diseases, and all demographic groups. Methods In the HealthInfoNet, Maine’s health information exchange (HIE), a retrospective cohort of 1,273,114 patients was constructed with the preceding 12-month EMR. Each patient’s next 6-month (between January 1, 2013 and June 30, 2013) health care resource utilization was retrospectively scored ranging from 0 to 100 and a decision tree–based predictive model was developed. Our model was later integrated in the Maine HIE population exploration system to allow a prospective validation analysis of 1,358,153 patients by forecasting their next 6-month risk of resource utilization between July 1, 2013 and December 31, 2013. Results Prospectively predicted risks, on either an individual level or a population (per 1000 patients) level, were consistent with the next 6-month resource utilization distributions and the clinical patterns at the population level. Results demonstrated the strong correlation between its care resource utilization and our risk scores, supporting the effectiveness of our model. With the online population risk monitoring enterprise dashboards, the effectiveness of the predictive algorithm has been validated by clinicians and caregivers in the State of Maine. Conclusions The model and associated online applications were designed for tracking the evolving nature of total population risk, in a longitudinal manner, for health care resource utilization. It will enable more effective care management strategies driving improved patient outcomes. PMID:26395541

Estimating quality-adjusted life-year loss due to noncommunicable diseases in Korean adults through to the year 2040.

PubMed

Ock, Minsu; Han, Jung Won; Lee, Jin Yong; Kim, Seon-Ha; Jo, Min-Woo

2015-01-01

To estimate the loss in quality-adjusted life-years (QALYs) in Korean adults due to 13 noncommunicable diseases (NCDs) in 2010 and predict changes in QALY loss through to the year 2040. Thirteen NCDs (hypertension, diabetes mellitus, hyperlipidemia, stroke, myocardial infarction, angina, arthritis, osteoporosis, asthma, allergic rhinitis, atopic dermatitis, cataract, and depression) were selected from the Korean Community Health Survey 2010. The EuroQol five-dimensional questionnaire index from the Korean Community Health Survey 2010 and the Korean valuation set were used to estimate utility weights according to sex, age, and disease. Morbidity data were also obtained from the Korean Community Health Survey 2010. Mortality data according to disease and life expectancy were retrieved from the Korean Statistical Information Service. To predict future QALY loss, future population projection data from the Korean Statistical Information Service were used as substitutes for 2010 population size. Among the assessed 13 NCDs, the largest total QALY loss was for hypertension (513,113 QALYs; units are omitted hereafter), followed by arthritis (509,317) and stroke (431,049). The largest QALY loss due to mortality was stroke (306,733), whereas the largest QALY loss due to morbidity was arthritis (502,513). By applying the middle estimate of future population, the largest increase in total QALY loss between 2010 and 2040 was for hypertension (840,582), followed by stroke (719,076) and diabetes mellitus (474,607). Hypertension, arthritis, and stroke are important in terms of total QALY loss, which will continuous to increase because of aging. These results could be used to develop cost-effective interventions that reduce the burden of NCDs. Copyright © 2015. Published by Elsevier Inc.

Dietary Sodium Consumption Predicts Future Blood Pressure and Incident Hypertension in the Japanese Normotensive General Population.

PubMed

Takase, Hiroyuki; Sugiura, Tomonori; Kimura, Genjiro; Ohte, Nobuyuki; Dohi, Yasuaki

2015-07-29

Although there is a close relationship between dietary sodium and hypertension, the concept that persons with relatively high dietary sodium are at increased risk of developing hypertension compared with those with relatively low dietary sodium has not been studied intensively in a cohort. We conducted an observational study to investigate whether dietary sodium intake predicts future blood pressure and the onset of hypertension in the general population. Individual sodium intake was estimated by calculating 24-hour urinary sodium excretion from spot urine in 4523 normotensive participants who visited our hospital for a health checkup. After a baseline examination, they were followed for a median of 1143 days, with the end point being development of hypertension. During the follow-up period, hypertension developed in 1027 participants (22.7%). The risk of developing hypertension was higher in those with higher rather than lower sodium intake (hazard ratio 1.25, 95% CI 1.04 to 1.50). In multivariate Cox proportional hazards regression analysis, baseline sodium intake and the yearly change in sodium intake during the follow-up period (as continuous variables) correlated with the incidence of hypertension. Furthermore, both the yearly increase in sodium intake and baseline sodium intake showed significant correlations with the yearly increase in systolic blood pressure in multivariate regression analysis after adjustment for possible risk factors. Both relatively high levels of dietary sodium intake and gradual increases in dietary sodium are associated with future increases in blood pressure and the incidence of hypertension in the Japanese general population. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Population-Level Transcriptomic Responses of the Southern Ocean Salp Salpa thompsoni to Environment Variability of the Western Antarctic Peninsula Region

NASA Astrophysics Data System (ADS)

Bucklin, A. C.; Batta Lona, P. G.; Maas, A. E.; O'Neill, R. J.; Wiebe, P. H.

2015-12-01

In response to the changing Antarctic climate, the Southern Ocean salp Salpa thompsoni has shown altered patterns of distribution and abundance that are anticipated to have profound impacts on pelagic food webs and ecosystem dynamics. The physiological and molecular processes that underlay ecological function and biogeographical distribution are key to understanding present-day dynamics and predicting future trajectories. This study examined transcriptome-wide patterns of gene expression in relation to biological and physical oceanographic conditions in coastal, shelf and offshore waters of the Western Antarctic Peninsula (WAP) region during austral spring and summer 2011. Based on field observations and collections, seasonal changes in the distribution and abundance of salps of different life stages were associated with differences in water mass structure of the WAP. Our observations are consistent with previous suggestions that bathymetry and currents in Bransfield Strait could generate a retentive cell for an overwintering population of S. thompsoni, which may generate the characteristic salp blooms found throughout the region later in summer. The statistical analysis of transcriptome-wide patterns of gene expression revealed differences among salps collected in different seasons and from different habitats (i.e., coastal versus offshore) in the WAP. Gene expression patterns also clustered by station in austral spring - but not summer - collections, suggesting stronger heterogeneity of environmental conditions. During the summer, differentially expressed genes covered a wider range of functions, including those associated with stress responses. Future research using novel molecular transcriptomic / genomic characterization of S. thompsoni will allow more complete understanding of individual-, population-, and species-level responses to environmental variability and prediction of future dynamics of Southern Ocean food webs and ecosystems.

The Work Ability of Hong Kong Construction Workers in Relation to Individual and Work-Related Factors.

PubMed

Ng, Jacky Y K; Chan, Alan H S

2018-05-14

The shortage in Hong Kong of construction workers is expected to worsen in future due to the aging population and increasing construction activity. Construction work is dangerous and to help reduce the premature loss of construction workers due to work-related disabilities, this study measured the work ability of 420 Hong Kong construction workers with a Work Ability Index (WAI) which can be used to predict present and future work performance. Given the importance of WAI, in this study the effects of individual and work-related factors on WAI were examined to develop and validate a WAI model to predict how individual and work-related factors affect work ability. The findings will be useful for formulating a pragmatic intervention program to improve the work ability of construction workers and keep them in the work force.

Visualization and classification of physiological failure modes in ensemble hemorrhage simulation

NASA Astrophysics Data System (ADS)

Zhang, Song; Pruett, William Andrew; Hester, Robert

2015-01-01

In an emergency situation such as hemorrhage, doctors need to predict which patients need immediate treatment and care. This task is difficult because of the diverse response to hemorrhage in human population. Ensemble physiological simulations provide a means to sample a diverse range of subjects and may have a better chance of containing the correct solution. However, to reveal the patterns and trends from the ensemble simulation is a challenging task. We have developed a visualization framework for ensemble physiological simulations. The visualization helps users identify trends among ensemble members, classify ensemble member into subpopulations for analysis, and provide prediction to future events by matching a new patient's data to existing ensembles. We demonstrated the effectiveness of the visualization on simulated physiological data. The lessons learned here can be applied to clinically-collected physiological data in the future.

Can theory predict the process of suicide on entry to prison? Predicting dynamic risk factors for suicide ideation in a high-risk prison population.

PubMed

Slade, Karen; Edelman, Robert

2014-01-01

Each year approximately 110,000 people are imprisoned in England and Wales and new prisoners remain one of the highest risk groups for suicide across the world. The reduction of suicide in prisoners remains difficult as assessments and interventions tend to rely on static risk factors with few theoretical or integrated models yet evaluated. To identify the dynamic factors that contribute to suicide ideation in this population based on Williams and Pollock's (2001) Cry of Pain (CoP) model. New arrivals (N = 198) into prison were asked to complete measures derived from the CoP model plus clinical and prison-specific factors. It was hypothesized that the factors of the CoP model would be predictive of suicide ideation. Support was provided for the defeat and entrapment aspects of the CoP model with previous self-harm, repeated times in prison, and suicide-permissive cognitions also key in predicting suicide ideation for prisoners on entry to prison. An integrated and dynamic model was developed that has utility in predicting suicide in early-stage prisoners. Implications for both theory and practice are discussed along with recommendations for future research.

Tick exposure and extreme climate events impact survival and threaten the persistence of a long-lived lizard.

PubMed

Jones, Alice R; Bull, C Michael; Brook, Barry W; Wells, Konstans; Pollock, Kenneth H; Fordham, Damien A

2016-03-01

Assessing the impacts of multiple, often synergistic, stressors on the population dynamics of long-lived species is becoming increasingly important due to recent and future global change. Tiliqua rugosa (sleepy lizard) is a long-lived skink (>30 years) that is adapted to survive in semi-arid environments with varying levels of parasite exposure and highly seasonal food availability. We used an exhaustive database of 30 years of capture-mark-recapture records to quantify the impacts of both parasite exposure and environmental conditions on the lizard's survival rates and long-term population dynamics. Lizard abundance was relatively stable throughout the study period; however, there were changing patterns in adult and juvenile apparent survival rates, driven by spatial and temporal variation in levels of tick exposure and temporal variation in environmental conditions. Extreme weather events during the winter and spring seasons were identified as important environmental drivers of survival. Climate models predict a dramatic increase in the frequency of extreme hot and dry winter and spring seasons in our South Australian study region; from a contemporary probability of 0.17 up to 0.47-0.83 in 2080 depending on the emissions scenario. Our stochastic population model projections showed that these future climatic conditions will induce a decline in the abundance of this long-lived reptile of up to 67% within 30 years from 2080, under worst case scenario modelling. The results have broad implications for future work investigating the drivers of population dynamics and persistence. We highlight the importance of long-term data sets and accounting for synergistic impacts between multiple stressors. We show that predicted increases in the frequency of extreme climate events have the potential to considerably and negatively influence a long-lived species, which might previously have been assumed to be resilient to environmental perturbations. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

Systematic review of prognostic prediction models for acute kidney injury (AKI) in general hospital populations.

PubMed

Hodgson, Luke Eliot; Sarnowski, Alexander; Roderick, Paul J; Dimitrov, Borislav D; Venn, Richard M; Forni, Lui G

2017-09-27

Critically appraise prediction models for hospital-acquired acute kidney injury (HA-AKI) in general populations. Systematic review. Medline, Embase and Web of Science until November 2016. Studies describing development of a multivariable model for predicting HA-AKI in non-specialised adult hospital populations. Published guidance followed for data extraction reporting and appraisal. 14 046 references were screened. Of 53 HA-AKI prediction models, 11 met inclusion criteria (general medicine and/or surgery populations, 474 478 patient episodes) and five externally validated. The most common predictors were age (n=9 models), diabetes (5), admission serum creatinine (SCr) (5), chronic kidney disease (CKD) (4), drugs (diuretics (4) and/or ACE inhibitors/angiotensin-receptor blockers (3)), bicarbonate and heart failure (4 models each). Heterogeneity was identified for outcome definition. Deficiencies in reporting included handling of predictors, missing data and sample size. Admission SCr was frequently taken to represent baseline renal function. Most models were considered at high risk of bias. Area under the receiver operating characteristic curves to predict HA-AKI ranged 0.71-0.80 in derivation (reported in 8/11 studies), 0.66-0.80 for internal validation studies (n=7) and 0.65-0.71 in five external validations. For calibration, the Hosmer-Lemeshow test or a calibration plot was provided in 4/11 derivations, 3/11 internal and 3/5 external validations. A minority of the models allow easy bedside calculation and potential electronic automation. No impact analysis studies were found. AKI prediction models may help address shortcomings in risk assessment; however, in general hospital populations, few have external validation. Similar predictors reflect an elderly demographic with chronic comorbidities. Reporting deficiencies mirrors prediction research more broadly, with handling of SCr (baseline function and use as a predictor) a concern. Future research should focus on validation, exploration of electronic linkage and impact analysis. The latter could combine a prediction model with AKI alerting to address prevention and early recognition of evolving AKI. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

The TSH levels and risk of hypothyroidism: Results from a population based prospective cohort study in an Iranian adult's population.

PubMed

Aminorroaya, Ashraf; Meamar, Rokhsareh; Amini, Massoud; Feizi, Awat; Nasri, Maryam; Tabatabaei, Azamosadat; Faghihimani, Elham

2017-06-01

The aim of current study was to assess the relationship between serum TSH levels and hypothyroidism risk in the euthyroid population. In a population-based cohort study, a total of 615 individuals with a normal baseline TSH, from of total population (n=2254) in 2006, were followed up for 6years. TSH, total T4, thyroid peroxidase antibody (TPOAb), and thyroglobulin antibody (TgAb) were measured. The relative risk (RR) and 95% confidence interval (95%CI) were calculated based on logistic regression. The Receiver Operating Characteristic (ROC) analysis along with area under the curve (AUC) was used to prediction of future hypothyroidism. TSH level in 2006 was a significant predictor for overt hypothyroidism, in the total population (RR=3.5) and female (RR=1.37) (all, P value<0.05). A cutoff value of TSH at 2.05mIU/L [AUC: (CI95 %), 0.68 (0.44-0.92; P=0.05)] was obtained for differentiating the patients with overt hypothyroidism from euthyroid. However, this cut off was not observed when we included only negative TPO and TgAbs people in 2006. The RR of hypothyroidism increased gradually when TSH level increased from 2.06-3.6mIU/L to >3.6mIU/L in the total population and both sexes. In women, the risk of overt hypothyroidism was significantly higher in subjects with TSH above 3.6 than those subject with THS levels≤2.05 [RR: (CI95 %), 20.57(2.-207.04), P value<0.05]. A cutoff value of TSH at 2.05mIU/L could predict the development of overt hypothyroidism in future. However, it was not applicable for people with negative TPOAb and negative TgAb. Copyright © 2016 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Humans, Topograpghy, and Wildland Fire: The Ingredients for Long-term Patterns in Ecosystems

Treesearch

Richard P. Guyette; Daniel C. Dey

2000-01-01

Three factors, human population density, topography, and culture interact to create temporal and spatial differences in the frequency of fire at the landscape level. These factors can be quantitatively related to fire frequency. The fire model can be used to reconstruct historic and to predict future frequency of fire in ecosystems, as well as to identify long-term...

Humans, topography, and wildland fire: The ingredients for long-term patterns in ecosystems

Treesearch

Richard P. Guyette; Daniel C. Dey

2000-01-01

Three factors, human population density, topography,and culture interact to create temporal and spatial differences in the frequency of fire at the landscape level. These facters can be quantitatively related to fire frequency. The fire model can be used to reconstruct historic and to predict future frequency of fire in ecosystems, as well as to identify long-term...

Climate change response of great basin bristlecone pine in the Nevada NSF-EPSCoR Project (www.nvclimatechange.org)

Treesearch

Franco Biondi; Scotty Strachan

2011-01-01

Predicting the future of high-elevation pine populations is closely linked to correctly interpreting their past responses to climatic variability. As a proxy index of climate, dendrochronological records have the advantage of seasonal to annual resolution over multiple centuries to millennia (Bradley 1999). All climate reconstructions rely on the 'uniformity...

DECLINE AND EXTINCTION OF LAKE TROUT IN THE GREAT LAKES: CAN BIOLOGICAL INDICATORS HELP DIAGNOSE CAUSES, IDENTIFY REMEDIAL ACTIONS, AND PREDICT FUTURE CONDITIONS?

EPA Science Inventory

The lake trout, Salvelinus namaycush, is the predominant top predator native fish species of the Great Lakes. Lake trout are valued for commercial and recreational use in addition to their ecological importance. In the last half of the 20th century, population declines lead to vi...

Predicting the effects of climate change on population connectivity and genetic diversity of an imperiled freshwater mussel, Cumberlandia monodonta (Bivalvia: Margaritiferidae), in riverine systems.

PubMed

Inoue, Kentaro; Berg, David J

2017-01-01

In the face of global climate change, organisms may respond to temperature increases by shifting their ranges poleward or to higher altitudes. However, the direction of range shifts in riverine systems is less clear. Because rivers are dendritic networks, there is only one dispersal route from any given location to another. Thus, range shifts are only possible if branches are connected by suitable habitat, and stream-dwelling organisms can disperse through these branches. We used Cumberlandia monodonta (Bivalvia: Unionoida: Margaritiferidae) as a model species to investigate the effects of climate change on population connectivity because a majority of contemporary populations are panmictic. We combined ecological niche models (ENMs) with population genetic simulations to investigate the effects of climate change on population connectivity and genetic diversity of C. monodonta. The ENMs were constructed using bioclimatic and landscape data to project shifts in suitable habitat under future climate scenarios. We then used forward-time simulations to project potential changes in genetic diversity and population connectivity based on these range shifts. ENM results under current conditions indicated long stretches of highly suitable habitat in rivers where C. monodonta persists; populations in the upper Mississippi River remain connected by suitable habitat that does not impede gene flow. Future climate scenarios projected northward and headwater-ward range contraction and drastic declines in habitat suitability for most extant populations throughout the Mississippi River Basin. Simulations indicated that climate change would greatly reduce genetic diversity and connectivity across populations. Results suggest that a single, large population of C. monodonta will become further fragmented into smaller populations, each of which will be isolated and begin to differentiate genetically. Because C. monodonta is a widely distributed species and purely aquatic, our results suggest that persistence and connectivity of stream-dwelling organisms will be significantly altered in response to future climate change. © 2016 John Wiley & Sons Ltd.

Developing a dashboard to help measure and achieve the triple aim: a population-based cohort study.

PubMed

Seow, Hsien-Yeang; Sibley, Lyn M

2014-08-30

Health system planners aim to pursue the three goals of Triple Aim: 1) reduce health care costs; 2) improve population health; and 3) improve the care experience. Moreover, they also need measures that can reliably predict future health care needs in order to manage effectively the health system performance. Yet few measures exist to assess Triple Aim and predict future needs at a health system level. The purpose of this study is to explore the novel application of a case-mix adjustment method in order to measure and help improve the Triple Aim of health system performance. We applied a case-mix adjustment method to a population-based analysis to assess its usefulness as a measure of health system performance and Triple Aim. The study design was a retrospective, cohort study of adults from Ontario, Canada using administrative databases: individuals were assigned a predicted illness burden score using a case-mix adjustment system from diagnoses and health utilization data in 2008, and then followed forward to assess the actual health care utilization and costs in the following year (2009). We applied the Johns Hopkins Adjusted Clinical Group (ACG) Case-Mix System to categorize individuals into 60 levels of healthcare need, called ACGs. The outcomes were: 1) Number of individuals per ACG; 2) Total system costs per ACG; and 3) Mean cost per person per ACG, which together formed a health system "dashboard". We identified 11.4 million adults. 16.1% were aged 65 or older, 3.2 million (28%) did not use health care services that year, and 45,000 (0.4%) were in the highest acuity ACG category using 12 times more than an average adult. The sickest 1%, 5% and 15% of the population use about 10%, 30% and 50% of total health system costs respectively. The dashboard measures 2 dimensions of Triple Aim: 1) reduced costs: when total system costs per ACG or when average costs per person is reduced; and 2) improved population health: when more people move into healthier rather than sicker ACGs. It can help to achieve the third aim, improved care experience, when ACG utilization predictions are reported to providers to proactively develop care plans. The dashboard, developed via case-mix methods, measures 2 of the Triple Aim goals and can help health system planners better manage their health delivery systems.

Single-trial dynamics of motor cortex and their applications to brain-machine interfaces

PubMed Central

Kao, Jonathan C.; Nuyujukian, Paul; Ryu, Stephen I.; Churchland, Mark M.; Cunningham, John P.; Shenoy, Krishna V.

2015-01-01

Increasing evidence suggests that neural population responses have their own internal drive, or dynamics, that describe how the neural population evolves through time. An important prediction of neural dynamical models is that previously observed neural activity is informative of noisy yet-to-be-observed activity on single-trials, and may thus have a denoising effect. To investigate this prediction, we built and characterized dynamical models of single-trial motor cortical activity. We find these models capture salient dynamical features of the neural population and are informative of future neural activity on single trials. To assess how neural dynamics may beneficially denoise single-trial neural activity, we incorporate neural dynamics into a brain–machine interface (BMI). In online experiments, we find that a neural dynamical BMI achieves substantially higher performance than its non-dynamical counterpart. These results provide evidence that neural dynamics beneficially inform the temporal evolution of neural activity on single trials and may directly impact the performance of BMIs. PMID:26220660

Game theory in the death galaxy: interaction of cancer and stromal cells in tumour microenvironment.

PubMed

Wu, Amy; Liao, David; Tlsty, Thea D; Sturm, James C; Austin, Robert H

2014-08-06

Preventing relapse is the major challenge to effective therapy in cancer. Within the tumour, stromal (ST) cells play an important role in cancer progression and the emergence of drug resistance. During cancer treatment, the fitness of cancer cells can be enhanced by ST cells because their molecular signalling interaction delays the drug-induced apoptosis of cancer cells. On the other hand, competition among cancer and ST cells for space or resources should not be ignored. We explore the population dynamics of multiple myeloma (MM) versus bone marrow ST cells by using an experimental microecology that we call the death galaxy, with a stable drug gradient and connected microhabitats. Evolutionary game theory is a quantitative way to capture the frequency-dependent nature of interactive populations. Therefore, we use evolutionary game theory to model the populations in the death galaxy with the gradients of pay-offs and successfully predict the future densities of MM and ST cells. We discuss the possible clinical use of such analysis for predicting cancer progression.

Climatic Factors Driving Invasion of the Tiger Mosquito (Aedes albopictus) into New Areas of Trentino, Northern Italy

PubMed Central

Castellani, Cristina; Arnoldi, Daniele; Rizzoli, Annapaola

2011-01-01

Background The tiger mosquito (Aedes albopictus), vector of several emerging diseases, is expanding into more northerly latitudes as well as into higher altitudes in northern Italy. Changes in the pattern of distribution of the tiger mosquito may affect the potential spread of infectious diseases transmitted by this species in Europe. Therefore, predicting suitable areas of future establishment and spread is essential for planning early prevention and control strategies. Methodology/Principal Findings To identify the areas currently most suitable for the occurrence of the tiger mosquito in the Province of Trento, we combined field entomological observations with analyses of satellite temperature data (MODIS Land Surface Temperature: LST) and human population data. We determine threshold conditions for the survival of overwintering eggs and for adult survival using both January mean temperatures and annual mean temperatures. We show that the 0°C LST threshold for January mean temperatures and the 11°C threshold for annual mean temperatures provide the best predictors for identifying the areas that could potentially support populations of this mosquito. In fact, human population density and distance to human settlements appear to be less important variables affecting mosquito distribution in this area. Finally, we evaluated the future establishment and spread of this species in relation to predicted climate warming by considering the A2 scenario for 2050 statistically downscaled at regional level in which winter and annual temperatures increase by 1.5 and 1°C, respectively. Conclusions/Significance MODIS satellite LST data are useful for accurately predicting potential areas of tiger mosquito distribution and for revealing the range limits of this species in mountainous areas, predictions which could be extended to an European scale. We show that the observed trend of increasing temperatures due to climate change could facilitate further invasion of Ae. albopictus into new areas. PMID:21525991

Modeling the evolution of infrared galaxies: a parametric backward evolution model

NASA Astrophysics Data System (ADS)

Béthermin, M.; Dole, H.; Lagache, G.; Le Borgne, D.; Penin, A.

2011-05-01

Aims: We attempt to model the infrared galaxy evolution in as simple a way as possible and reproduce statistical properties such as the number counts between 15 μm and 1.1 mm, the luminosity functions, and the redshift distributions. We then use the fitted model to interpret observations from Spitzer, AKARI, BLAST, LABOCA, AzTEC, SPT, and Herschel, and make predictions for Planck and future experiments such as CCAT or SPICA. Methods: This model uses an evolution in density and luminosity of the luminosity function parametrized by broken power-laws with two breaks at redshift ~0.9 and 2, and contains the two populations of the Lagache model: normal and starburst galaxies. We also take into account the effect of the strong lensing of high-redshift sub-millimeter galaxies. This effect is significant in the sub-mm and mm range near 50 mJy. It has 13 free parameters and eight additional calibration parameters. We fit the parameters to the IRAS, Spitzer, Herschel, and AzTEC measurements with a Monte Carlo Markov chain. Results: The model adjusted to deep counts at key wavelengths reproduces the counts from mid-infrared to millimeter wavelengths, as well as the mid-infrared luminosity functions. We discuss the contribution to both the cosmic infrared background (CIB) and the infrared luminosity density of the different populations. We also estimate the effect of the lensing on the number counts, and discuss the discovery by the South Pole Telescope (SPT) of a very bright population lying at high redshift. We predict the contribution of the lensed sources to the Planck number counts, the confusion level for future missions using a P(D) formalism, and the Universe opacity to TeV photons caused by the CIB. Material of the model (software, tables and predictions) is available online.

Prediction of anthropometric accommodation in aircraft cockpits

NASA Astrophysics Data System (ADS)

Zehner, Gregory Franklin

Designing aircraft cockpits to accommodate the wide range of body sizes existing in the U.S. population has always been a difficult problem for Crewstation Engineers. The approach taken in the design of military aircraft has been to restrict the range of body sizes allowed into flight training, and then to develop standards and specifications to ensure that the majority of the pilots are accommodated. Accommodation in this instance is defined as the ability to: (1) Adequately see, reach, and actuate controls; (2) Have external visual fields so that the pilot can see to land, clear for other aircraft, and perform a wide variety of missions (ground support/attack or air to air combat); and (3) Finally, if problems arise, the pilot has to be able to escape safely. Each of these areas is directly affected by the body size of the pilot. Unfortunately, accommodation problems persist and may get worse. Currently the USAF is considering relaxing body size entrance requirements so that smaller and larger people could become pilots. This will make existing accommodation problems much worse. This dissertation describes a methodology for correcting this problem and demonstrates the method by predicting pilot fit and performance in the USAF T-38A aircraft based on anthropometric data. The methods described can be applied to a variety of design applications where fitting the human operator into a system is a major concern. A systematic approach is described which includes: defining the user population, setting functional requirements that operators must be able to perform, testing the ability of the user population to perform the functional requirements, and developing predictive equations for selecting future users of the system. Also described is a process for the development of new anthropometric design criteria and cockpit design methods that assure body size accommodation is improved in the future.

Model-based conservation planning of the genetic diversity of Phellodendron amurense Rupr due to climate change

PubMed Central

Wan, Jizhong; Wang, Chunjing; Yu, Jinghua; Nie, Siming; Han, Shijie; Zu, Yuangang; Chen, Changmei; Yuan, Shusheng; Wang, Qinggui

2014-01-01

Climate change affects both habitat suitability and the genetic diversity of wild plants. Therefore, predicting and establishing the most effective and coherent conservation areas is essential for the conservation of genetic diversity in response to climate change. This is because genetic variance is a product not only of habitat suitability in conservation areas but also of efficient protection and management. Phellodendron amurense Rupr. is a tree species (family Rutaceae) that is endangered due to excessive and illegal harvesting for use in Chinese medicine. Here, we test a general computational method for the prediction of priority conservation areas (PCAs) by measuring the genetic diversity of P. amurense across the entirety of northeast China using a single strand repeat analysis of twenty microsatellite markers. Using computational modeling, we evaluated the geographical distribution of the species, both now and in different future climate change scenarios. Different populations were analyzed according to genetic diversity, and PCAs were identified using a spatial conservation prioritization framework. These conservation areas were optimized to account for the geographical distribution of P. amurense both now and in the future, to effectively promote gene flow, and to have a long period of validity. In situ and ex situ conservation, strategies for vulnerable populations were proposed. Three populations with low genetic diversity are predicted to be negatively affected by climate change, making conservation of genetic diversity challenging due to decreasing habitat suitability. Habitat suitability was important for the assessment of genetic variability in existing nature reserves, which were found to be much smaller than the proposed PCAs. Finally, a simple set of conservation measures was established through modeling. This combined molecular and computational ecology approach provides a framework for planning the protection of species endangered by climate change. PMID:25165526

Dispersion of the invasive common carp Cyprinus carpio in southern South America: changes and expectations, westward and southward.

PubMed

Crichigno, S; Cordero, P; Blasetti, G; Cussac, V

2016-07-01

Common carp Cyprinus carpio possess multiple traits that contribute to their success as an invasive species. They have been introduced across the globe, and abundant populations can have numerous negative effects. Although ecological niche-based modelling techniques have been used to predict the potential range of C. carpio invasion in U.S.A., occurrence and abundance patterns have not yet been considered on a regional scale. In the present review new locations are documented, the status of the southernmost population has been studied and the probability of new lakes and reservoirs being colonized by C. carpio has been obtained and related to environmental conditions. The new localities for C. carpio have expanded its distribution westward, into the Andean Region, and present results from the South American southernmost population have shown a well-established population. Analysis of presence data provided two principal results: (1) the probability of a site being with C. carpio can be inferred using environmental variables and (2) the probability of a site being with C. carpio is a useful tool for the prediction of future invasions. Selective fishing on the Negro basin could constitute a potential mitigation measure, decreasing the abundance of the species and thus reducing the species' potential for southward expansion. These results reinforce the idea that artisanal fisheries, food production and conservation interests should be taken into account by local government management agencies in any discussion regarding the southern distribution of C. carpio in the near future. © 2016 The Fisheries Society of the British Isles.

Climate-driven range shifts explain the distribution of extant gene pools and predict future loss of unique lineages in a marine brown alga.

PubMed

Assis, J; Serrão, E A; Claro, B; Perrin, C; Pearson, G A

2014-06-01

The climate-driven dynamics of species ranges is a critical research question in evolutionary ecology. We ask whether present intraspecific diversity is determined by the imprint of past climate. This is an ongoing debate requiring interdisciplinary examination of population genetic pools and persistence patterns across global ranges. Previously, contrasting inferences and predictions have resulted from distinct genomic coverage and/or geographical information. We aim to describe and explain the causes of geographical contrasts in genetic diversity and their consequences for the future baseline of the global genetic pool, by comparing present geographical distribution of genetic diversity and differentiation with predictive species distribution modelling (SDM) during past extremes, present time and future climate scenarios for a brown alga, Fucus vesiculosus. SDM showed that both atmospheric and oceanic variables shape the global distribution of intertidal species, revealing regions of persistence, extinction and expansion during glacial and postglacial periods. These explained the distribution and structure of present genetic diversity, consisting of differentiated genetic pools with maximal diversity in areas of long-term persistence. Most of the present species range comprises postglacial expansion zones and, in contrast to highly dispersive marine organisms, expansions involved only local fronts, leaving distinct genetic pools at rear edges. Besides unravelling a complex phylogeographical history and showing congruence between genetic diversity and persistent distribution zones, supporting the hypothesis of niche conservatism, range shifts and loss of unique genetic diversity at the rear edge were predicted for future climate scenarios, impoverishing the global gene pool. © 2014 John Wiley & Sons Ltd.

National surveys of military personnel, nursing students, and the public: drivers of military nursing careers.

PubMed

Donelan, Karen; Romano, Carol; Buerhaus, Peter; DesRoches, Catherine; Applebaum, Sandra; Ward, Johanna Rm; Schoneboom, Bruce A; Hinshaw, Ada Sue

2014-05-01

The U.S. health care system is facing a projected nursing shortage of unprecedented magnitude. Although military nursing services recently have been able to meet their nursing recruitment quotas, national studies have predicted a long-term nursing shortage that may affect future recruitment for the Nurse Corps of the three military services. Data are needed to plan for recruitment incentives and the impact of those incentives on targeted populations of likely future nurses. Data are drawn from three online surveys conducted in 2011-2012, including surveys of 1,302 Army, Navy, and Air Force personnel serving on major military bases, 914 nursing students at colleges with entry Bachelor of Science in Nursing programs located nearby major military bases, and a qualitative survey of 1,200 young adults, age 18-39, in the general public. The three populations are different in several demographic characteristics. We explored perceptions of military careers, nursing careers and barriers, and incentives to pursue military nursing careers in all populations. Perceptions differ among the groups. The results of this study may help to inform strategies for reaching out to specific populations with targeted messages that focus on barriers and facilitators relevant to each to successfully recruit a diverse Nurse Corps for the future. Reprint & Copyright © 2014 Association of Military Surgeons of the U.S.

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

NASA Technical Reports Server (NTRS)

Viken, Jeff; Dollyhigh, Samuel; Smith, Jeremy; Trani, Antonio; Baik, Hojong; Hinze, Nicholas; Ashiabor, Senanu

2006-01-01

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

The relationship between victimization and mental health functioning in homeless youth and adults.

PubMed

Rattelade, Stephanie; Farrell, Susan; Aubry, Tim; Klodawsky, Fran

2014-06-01

This study examined the relationship between victimization and mental health functioning in homeless individuals. Homeless populations experience higher levels of victimization than the general population, which in turn have a detrimental effect on their mental health. A sample of 304 homeless adults and youth completed one-on-one interviews, answering questions on mental health, past victimization, and recent victimization experiences. A hierarchical linear regression showed that experiences of childhood sexual abuse predicted lower mental health functioning after controlling for the sex and age of individuals. The study findings are applicable to current support programs for victims in the homeless population and are relevant to future research on homelessness and victimization.

Tax reform, population ageing and the changing labour supply behaviour of married women.

PubMed

Apps, P

1991-01-01

"The burden of financing retirement incomes in an ageing population is predicted to rise sharply in future decades. This paper investigates the effects of reforms to the Australian tax-benefit system involving a greater reliance on proportional taxation for raising revenue and a more targeted welfare system for cutting government expenditure, in order to reduce expected budget deficits. Estimates of changes in net incomes and hours of work suggest that reforms of this kind shift the tax burden to lower and middle income households with a second earner and that they can have counter-productive labour supply effects. The study explores the impact of projected increases in female work force participation and illustrates the importance of shifts in the labour supply of married women in predicting the fiscal effects of demographic change." excerpt

Future of endemic flora of biodiversity hotspots in India.

PubMed

Chitale, Vishwas Sudhir; Behera, Mukund Dev; Roy, Partha Sarthi

2014-01-01

India is one of the 12 mega biodiversity countries of the world, which represents 11% of world's flora in about 2.4% of global land mass. Approximately 28% of the total Indian flora and 33% of angiosperms occurring in India are endemic. Higher human population density in biodiversity hotspots in India puts undue pressure on these sensitive eco-regions. In the present study, we predict the future distribution of 637 endemic plant species from three biodiversity hotspots in India; Himalaya, Western Ghats, Indo-Burma, based on A1B scenario for year 2050 and 2080. We develop individual variable based models as well as mixed models in MaxEnt by combining ten least co-related bioclimatic variables, two disturbance variables and one physiography variable as predictor variables. The projected changes suggest that the endemic flora will be adversely impacted, even under such a moderate climate scenario. The future distribution is predicted to shift in northern and north-eastern direction in Himalaya and Indo-Burma, while in southern and south-western direction in Western Ghats, due to cooler climatic conditions in these regions. In the future distribution of endemic plants, we observe a significant shift and reduction in the distribution range compared to the present distribution. The model predicts a 23.99% range reduction and a 7.70% range expansion in future distribution by 2050, while a 41.34% range reduction and a 24.10% range expansion by 2080. Integration of disturbance and physiography variables along with bioclimatic variables in the models improved the prediction accuracy. Mixed models provide most accurate results for most of the combinations of climatic and non-climatic variables as compared to individual variable based models. We conclude that a) regions with cooler climates and higher moisture availability could serve as refugia for endemic plants in future climatic conditions; b) mixed models provide more accurate results, compared to single variable based models.

Future of Endemic Flora of Biodiversity Hotspots in India

PubMed Central

Chitale, Vishwas Sudhir; Behera, Mukund Dev; Roy, Partha Sarthi

2014-01-01

India is one of the 12 mega biodiversity countries of the world, which represents 11% of world's flora in about 2.4% of global land mass. Approximately 28% of the total Indian flora and 33% of angiosperms occurring in India are endemic. Higher human population density in biodiversity hotspots in India puts undue pressure on these sensitive eco-regions. In the present study, we predict the future distribution of 637 endemic plant species from three biodiversity hotspots in India; Himalaya, Western Ghats, Indo-Burma, based on A1B scenario for year 2050 and 2080. We develop individual variable based models as well as mixed models in MaxEnt by combining ten least co-related bioclimatic variables, two disturbance variables and one physiography variable as predictor variables. The projected changes suggest that the endemic flora will be adversely impacted, even under such a moderate climate scenario. The future distribution is predicted to shift in northern and north-eastern direction in Himalaya and Indo-Burma, while in southern and south-western direction in Western Ghats, due to cooler climatic conditions in these regions. In the future distribution of endemic plants, we observe a significant shift and reduction in the distribution range compared to the present distribution. The model predicts a 23.99% range reduction and a 7.70% range expansion in future distribution by 2050, while a 41.34% range reduction and a 24.10% range expansion by 2080. Integration of disturbance and physiography variables along with bioclimatic variables in the models improved the prediction accuracy. Mixed models provide most accurate results for most of the combinations of climatic and non-climatic variables as compared to individual variable based models. We conclude that a) regions with cooler climates and higher moisture availability could serve as refugia for endemic plants in future climatic conditions; b) mixed models provide more accurate results, compared to single variable based models. PMID:25501852

Recent range expansion of a terrestrial orchid corresponds with climate-driven variation in its population dynamics.

PubMed

van der Meer, Sascha; Jacquemyn, Hans; Carey, Peter D; Jongejans, Eelke

2016-06-01

The population dynamics and distribution limits of plant species are predicted to change as the climate changes. However, it remains unclear to what extent climate variables affect population dynamics, which vital rates are most sensitive to climate change, and whether the same vital rates drive population dynamics in different populations. In this study, we used long-term demographic data from two populations of the terrestrial orchid Himantoglossum hircinum growing at the northern edge of their geographic range to quantify the influence of climate change on demographic vital rates. Integral projection models were constructed to study how climate conditions between 1991 and 2006 affected population dynamics and to assess how projected future climate change will affect the long-term viability of this species. Based on the parameterised vital rate functions and the observed climatic conditions, one of the studied populations had an average population growth rate above 1 (λ = 1.04), while the other was declining at ca. 3 % year(-1) (λ = 0.97). Variation in temperature and precipitation mainly affected population growth through their effect on survival and fecundity. Based on UK Climate Projection 2009 estimates of future climate conditions for three greenhouse gas emission scenarios, population growth rates are expected to increase in one of the studied populations. Overall, our results indicate that the observed changes in climatic conditions appeared to be beneficial to the long-term survival of the species in the UK and suggest that they may have been the driving force behind the current range expansion of H. hircinum in England.

Unpredictable food supply modifies costs of reproduction and hampers individual optimization.

PubMed

Török, János; Hegyi, Gergely; Tóth, László; Könczey, Réka

2004-11-01

Investment into the current reproductive attempt is thought to be at the expense of survival and/or future reproduction. Individuals are therefore expected to adjust their decisions to their physiological state and predictable aspects of environmental quality. The main predictions of the individual optimization hypothesis for bird clutch sizes are: (1) an increase in the number of recruits with an increasing number of eggs in natural broods, with no corresponding impairment of parental survival or future reproduction, and (2) a decrease in the fitness of parents in response to both negative and positive brood size manipulation, as a result of a low number of recruits, poor future reproduction of parents, or both. We analysed environmental influences on costs and optimization of reproduction on 6 years of natural and experimentally manipulated broods in a Central European population of the collared flycatcher. Based on dramatic differences in caterpillar availability, we classified breeding seasons as average and rich food years. The categorization was substantiated by the majority of present and future fitness components of adults and offspring. Neither observational nor experimental data supported the individual optimization hypothesis, in contrast to a Scandinavian population of the species. The quality of fledglings deteriorated, and the number of recruits did not increase with natural clutch size. Manipulation revealed significant costs of reproduction to female parents in terms of future reproductive potential. However, the influence of manipulation on recruitment was linear, with no significant polynomial effect. The number of recruits increased with manipulation in rich food years and tended to decrease in average years, so control broods did not recruit more young than manipulated broods in any of the year types. This indicates that females did not optimize their clutch size, and that they generally laid fewer eggs than optimal in rich food years. Mean yearly clutch size did not follow food availability, which suggests that females cannot predict food supply of the brood-rearing period at the beginning of the season. This lack of information on future food conditions seems to prevent them from accurately estimating their optimal clutch size for each season. Our results suggest that individual optimization may not be a general pattern even within a species, and alternative mechanisms are needed to explain clutch size variation.

Accurate predictions of population-level changes in sequence and structural properties of HIV-1 Env using a volatility-controlled diffusion model

PubMed Central

DeLeon, Orlando; Hodis, Hagit; O’Malley, Yunxia; Johnson, Jacklyn; Salimi, Hamid; Zhai, Yinjie; Winter, Elizabeth; Remec, Claire; Eichelberger, Noah; Van Cleave, Brandon; Puliadi, Ramya; Harrington, Robert D.; Stapleton, Jack T.; Haim, Hillel

2017-01-01

The envelope glycoproteins (Envs) of HIV-1 continuously evolve in the host by random mutations and recombination events. The resulting diversity of Env variants circulating in the population and their continuing diversification process limit the efficacy of AIDS vaccines. We examined the historic changes in Env sequence and structural features (measured by integrity of epitopes on the Env trimer) in a geographically defined population in the United States. As expected, many Env features were relatively conserved during the 1980s. From this state, some features diversified whereas others remained conserved across the years. We sought to identify “clues” to predict the observed historic diversification patterns. Comparison of viruses that cocirculate in patients at any given time revealed that each feature of Env (sequence or structural) exists at a defined level of variance. The in-host variance of each feature is highly conserved among individuals but can vary between different HIV-1 clades. We designate this property “volatility” and apply it to model evolution of features as a linear diffusion process that progresses with increasing genetic distance. Volatilities of different features are highly correlated with their divergence in longitudinally monitored patients. Volatilities of features also correlate highly with their population-level diversification. Using volatility indices measured from a small number of patient samples, we accurately predict the population diversity that developed for each feature over the course of 30 years. Amino acid variants that evolved at key antigenic sites are also predicted well. Therefore, small “fluctuations” in feature values measured in isolated patient samples accurately describe their potential for population-level diversification. These tools will likely contribute to the design of population-targeted AIDS vaccines by effectively capturing the diversity of currently circulating strains and addressing properties of variants expected to appear in the future. PMID:28384158

Population impact of familial and environmental risk factors for schizophrenia: a nationwide study.

PubMed

Sørensen, Holger J; Nielsen, Philip R; Pedersen, Carsten B; Benros, Michael E; Nordentoft, Merete; Mortensen, Preben B

2014-03-01

Although several studies have examined the relative contributions of familial and environmental risk factors for schizophrenia, few have additionally examined the predictive power on the individual level and simultaneously examined the population impact associated with a wide range of familial and environmental risk factors. The authors present rate ratios (IRR), population-attributable risks (PAR) and sex-specific cumulative incidences of the following risk factors: parental history of mental illness, urban place of birth, advanced paternal age, parental loss and immigration status. We established a population-based cohort of 2,486,646million persons born in Denmark between 1 January 1955 and 31 December 1993 using Danish registers. We found that PAR associated with urban birth was 11.73%; PAR associated with one, respectively 2, parent(s) with schizophrenia was 2.67% and 0.12%. PAR associated with second-generation immigration was 0.70%. Highest cumulative incidence (CI=20.23%; 95% CI=18.10-22.62) was found in male offspring of 2 parents with schizophrenia. Cumulative incidences for male offspring or female offspring of a parent with schizophrenia were 9.53% (95% CI=7.71-11.79), and 4.89%, (95% CI 4.50-5.31). The study showed that risk factors with highest predictive power on the individual level have a relatively low population impact. The challenge in future studies with direct genetic data is to examine gene-environmental interactions that can move research beyond current approaches and seek to achieve higher predictive power on the individual level and higher population impact. Copyright © 2014 Elsevier B.V. All rights reserved.

Validating prediction scales of type 2 diabetes mellitus in Spain: the SPREDIA-2 population-based prospective cohort study protocol

PubMed Central

Salinero-Fort, Miguel Ángel; de Burgos-Lunar, Carmen; Mostaza Prieto, José; Lahoz Rallo, Carlos; Abánades-Herranz, Juan Carlos; Gómez-Campelo, Paloma; Laguna Cuesta, Fernando; Estirado De Cabo, Eva; García Iglesias, Francisca; González Alegre, Teresa; Fernández Puntero, Belén; Montesano Sánchez, Luis; Vicent López, David; Cornejo Del Río, Víctor; Fernández García, Pedro J; Sabín Rodríguez, Concesa; López López, Silvia; Patrón Barandío, Pedro

2015-01-01

Introduction The incidence of type 2 diabetes mellitus (T2DM) is increasing worldwide. When diagnosed, many patients already have organ damage or advance subclinical atherosclerosis. An early diagnosis could allow the implementation of lifestyle changes and treatment options aimed at delaying the progression of the disease and to avoid cardiovascular complications. Different scores for identifying undiagnosed diabetes have been reported, however, their performance in populations of southern Europe has not been sufficiently evaluated. The main objectives of our study are: to evaluate the screening performance and cut-off points of the main scores that identify the risk of undiagnosed T2DM and prediabetes in a Spanish population, and to develop and validate our own predictive models of undiagnosed T2DM (screening model), and future T2DM (prediction risk model) after 5-year follow-up. As a secondary objective, we will evaluate the atherosclerotic burden of the population with undiagnosed T2DM. Methods and analysis Population-based prospective cohort study with baseline screening, to evaluate the performance of the FINDRISC, DANISH, DESIR, ARIC and QDScore, against the gold standard tests: Fasting plasma glucose, oral glucose tolerance and/or HbA1c. The sample size will include 1352 participants between the ages of 45 and 74 years. Analysis: sensitivity, specificity, positive predictive value, negative predictive value, likelihood ratio positive, likelihood ratio negative and receiver operating characteristic curves and area under curve. Binary logistic regression for the first 700 individuals (derivation) and last 652 (validation) will be performed. All analyses will be calculated with their 95% CI; statistical significance will be p<0.05. Ethics and dissemination The study protocol has been approved by the Research Ethics Committee of the Carlos III Hospital (Madrid). The score performance and predictive model will be presented in medical conferences, workshops, seminars and round table discussions. Furthermore, the predictive model will be published in a peer-reviewed medical journal to further increase the exposure of the scores. PMID:26220868

Simulating range-wide population and breeding habitat dynamics for an endangered woodland warbler in the face of uncertainty

USGS Publications Warehouse

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.

Leaf morphological and genetic differentiation between Quercus rubra L. and Q. ellipsoidalis E.J. Hill populations in contrasting environments

Treesearch

Oliver Gailing; Jennifer Lind; Erik Lilleskov

2012-01-01

Hybridization is considered to play an important role in speciation and evolution. Given the predicted northward tree migration in the eastern USA due to the impact of climate change, hybridization between related species is expected to become more frequent due to overlapping distribution ranges in the future. Oak species are "hot spots" of contemporary...

Forecasting the Range-wide Status of Polar Bears at Selected Times in the 21st Century

Treesearch

Steven C. Amstrup; Bruce G. Marcot; David C. Douglas

2007-01-01

To inform the U.S. Fish and Wildlife Service decision whether or not to list polar bears as threatened under the Endangered Species Act (ESA), we forecast the status of the world's polar bear (Ursus maritimus) populations 45, 75 and 100 years into the future. We applied the best available information about predicted changes in sea ice in the...

Global ice-core research: Understanding and applying environmental records of the past

USGS Publications Warehouse

Cecil, L. DeWayne; Green, Jaromy R.; Naftz, David L.

2000-01-01

Environmental changes are of major concern at low- or mid-latitude regions of our Earth simply because this is where 80 to 90 percent of the world’s human population live. Ice cores collected from isolated polar regions are, at best, proxy indicators of low- and mid-latitude environmental changes. Because polar icecore research is limiting in this sense, ice cores from low- and mid-latitude glaciers are being used to study past environmental changes in order to better understand and predict future environmental changes that may affect the populated regions of the world.

Spatial pattern formation facilitates eradication of infectious diseases

PubMed Central

Eisinger, Dirk; Thulke, Hans-Hermann

2008-01-01

Control of animal-born diseases is a major challenge faced by applied ecologists and public health managers. To improve cost-effectiveness, the effort required to control such pathogens needs to be predicted as accurately as possible. In this context, we reviewed the anti-rabies vaccination schemes applied around the world during the past 25 years. We contrasted predictions from classic approaches based on theoretical population ecology (which governs rabies control to date) with a newly developed individual-based model. Our spatially explicit approach allowed for the reproduction of pattern formation emerging from a pathogen's spread through its host population. We suggest that a much lower management effort could eliminate the disease than that currently in operation. This is supported by empirical evidence from historic field data. Adapting control measures to the new prediction would save one-third of resources in future control programmes. The reason for the lower prediction is the spatial structure formed by spreading infections in spatially arranged host populations. It is not the result of technical differences between models. Synthesis and applications. For diseases predominantly transmitted by neighbourhood interaction, our findings suggest that the emergence of spatial structures facilitates eradication. This may have substantial implications for the cost-effectiveness of existing disease management schemes, and suggests that when planning management strategies consideration must be given to methods that reflect the spatial nature of the pathogen–host system. PMID:18784795

Survey report; health needs of the 21st century.

PubMed

Raymond, S U

1989-01-01

Sustainability of development assistance programs depends greatly on the perceptions of priorities by recipient countries. A written survey was sent by the Catholic University of America's Institute for International Health and Development to 66 ministers of health in low-income and middle-income countries to assess their views of priority problems in health sector development. Response rate was 33%, coming from countries with highly diverse gross national products (GNPs), growth rates, mortality rates and life expectancies. Nevertheless, there was widespread agreement about priorities: 1) meeting costs of health care; 2) improving health care management and administration; and 3) extending communicable disease control. Communicable disease control and child health programs were more important to low-income countries than to middle-income countries. Costs, management and administration and the control of noncommunicable diseases were predicted to increase in importance. In demographics, urbanization, overall population growth and shift of workers from agriculture to industry and services were seen as the major problems of the past, and urbanization and the aging of populations accompanied by increasing life expectancies the major challenges of the future. Highest predicted training needs were for system managers and paramedical personnel. Government budgets, user fees and donor agencies were seen as the most important sources of past funding, with social security systems and fee-based payments increasing in importance in the future. The role of donor agencies would increase as would the need for more responsiveness. Future uncertainties include national economic growth, environmental problems, issues in ethics and changes in disease and technology.

Tryptophan Predicts the Risk for Future Type 2 Diabetes

PubMed Central

Chen, Tianlu; Zheng, Xiaojiao; Ma, Xiaojing; Bao, Yuqian; Ni, Yan; Hu, Cheng; Rajani, Cynthia; Huang, Fengjie; Zhao, Aihua; Jia, Weiping; Jia, Wei

2016-01-01

Recently, 5 amino acids were identified and verified as important metabolites highly associated with type 2 diabetes (T2D) development. This report aims to assess the association of tryptophan with the development of T2D and to evaluate its performance with existing amino acid markers. A total of 213 participants selected from a ten-year longitudinal Shanghai Diabetes Study (SHDS) were examined in two ways: 1) 51 subjects who developed diabetes and 162 individuals who remained metabolically healthy in 10 years; 2) the same 51 future diabetes and 23 strictly matched ones selected from the 162 healthy individuals. Baseline fasting serum tryptophan concentrations were quantitatively measured using ultra-performance liquid chromatography triple quadruple mass spectrometry. First, serum tryptophan level was found significantly higher in future T2D and was positively and independently associated with diabetes onset risk. Patients with higher tryptophan level tended to present higher degree of insulin resistance and secretion, triglyceride and blood pressure. Second, the prediction potential of tryptophan is non-inferior to the 5 existing amino acids. The predictive performance of the combined score improved after taking tryptophan into account. Our findings unveiled the potential of tryptophan as a new marker associated with diabetes risk in Chinese populations. The addition of tryptophan provided complementary value to the existing amino acid predictors. PMID:27598004

Applying Risk Prediction Models to Optimize Lung Cancer Screening: Current Knowledge, Challenges, and Future Directions.

PubMed

Sakoda, Lori C; Henderson, Louise M; Caverly, Tanner J; Wernli, Karen J; Katki, Hormuzd A

2017-12-01

Risk prediction models may be useful for facilitating effective and high-quality decision-making at critical steps in the lung cancer screening process. This review provides a current overview of published lung cancer risk prediction models and their applications to lung cancer screening and highlights both challenges and strategies for improving their predictive performance and use in clinical practice. Since the 2011 publication of the National Lung Screening Trial results, numerous prediction models have been proposed to estimate the probability of developing or dying from lung cancer or the probability that a pulmonary nodule is malignant. Respective models appear to exhibit high discriminatory accuracy in identifying individuals at highest risk of lung cancer or differentiating malignant from benign pulmonary nodules. However, validation and critical comparison of the performance of these models in independent populations are limited. Little is also known about the extent to which risk prediction models are being applied in clinical practice and influencing decision-making processes and outcomes related to lung cancer screening. Current evidence is insufficient to determine which lung cancer risk prediction models are most clinically useful and how to best implement their use to optimize screening effectiveness and quality. To address these knowledge gaps, future research should be directed toward validating and enhancing existing risk prediction models for lung cancer and evaluating the application of model-based risk calculators and its corresponding impact on screening processes and outcomes.

The Work Ability of Hong Kong Construction Workers in Relation to Individual and Work-Related Factors

PubMed Central

Ng, Jacky Y. K.

2018-01-01

The shortage in Hong Kong of construction workers is expected to worsen in future due to the aging population and increasing construction activity. Construction work is dangerous and to help reduce the premature loss of construction workers due to work-related disabilities, this study measured the work ability of 420 Hong Kong construction workers with a Work Ability Index (WAI) which can be used to predict present and future work performance. Given the importance of WAI, in this study the effects of individual and work-related factors on WAI were examined to develop and validate a WAI model to predict how individual and work-related factors affect work ability. The findings will be useful for formulating a pragmatic intervention program to improve the work ability of construction workers and keep them in the work force. PMID:29758018

Long-term forecasting of anesthesia workload in operating rooms from changes in a hospital's local population can be inaccurate.

PubMed

Masursky, Danielle; Dexter, Franklin; O'Leary, Colleen E; Applegeet, Carol; Nussmeier, Nancy A

2008-04-01

Anesthesia department planning depends on forecasting future demand for perioperative services. Little is known about long-range forecasting of anesthesia workload. We studied operating room (OR) times at Hospital A over 16 yr (1991-2006), anesthesia times at Hospital B over 26 yr (1981-2006), and cases at Hospital C over 13 yr (1994-2006). Each hospital is >100 yr old and is located in a US city with other hospitals that are >50 yr old. Hospitals A and B are the sole University hospitals in their metropolitan statistical areas (and many counties beyond). Hospital C is the sole tertiary hospital for >375 km. Each hospital's choice of a measure of anesthesia work to be analyzed was likely unimportant, as the annual hours of anesthesia correlated highly both with annual numbers of cases (r = 0.98) and with American Society of Anesthesiologist's Relative Value Guide units of work (r = 0.99). Despite a 2% decline in the local population, the hours of OR time at Hospital A increased overall (Pearson r = -0.87, P < 0.001) and for children (r = -0.84). At Hospital B, there was a strong positive correlation between population and hours of anesthesia (r = 0.97, P < 0.001), but not between annual increases in population and workload (r = -0.18). At Hospital C, despite a linear increase in population, the annual numbers of cases increased, declined with opening of two outpatient surgery facilities, and then stabilized. The predictive value of local personal income was low. In contrast, the annual increases in the hours of OR time and anesthesia could be modeled using simple time series methods. Although growth of the elderly population is a simple justification for building more ORs, managers should be cautious in arguing for strategic changes in capacity at individual hospitals based on future changes in the national age-adjusted population. Local population can provide little value in forecasting future anesthesia workloads at individual hospitals. In addition, anesthesia groups and hospital administrators should not focus on quarterly changes in workload, because workload can vary widely, despite consistent patterns over decades. To facilitate long-range planning, anesthesia groups and hospitals should save their billing and OR time data, display it graphically over years, and supplement with corresponding forecasting methods (e.g., staff an additional OR when an upper prediction bound of workload per OR exceeds a threshold).

Measuring the effectiveness of conservation: a novel framework to quantify the benefits of sage-grouse conservation policy and easements in Wyoming.

PubMed

Copeland, Holly E; Pocewicz, Amy; Naugle, David E; Griffiths, Tim; Keinath, Doug; Evans, Jeffrey; Platt, James

2013-01-01

Increasing energy and housing demands are impacting wildlife populations throughout western North America. Greater sage-grouse (Centrocercus urophasianus), a species known for its sensitivity to landscape-scale disturbance, inhabits the same low elevation sage-steppe in which much of this development is occurring. Wyoming has committed to maintain sage-grouse populations through conservation easements and policy changes that conserves high bird abundance "core" habitat and encourages development in less sensitive landscapes. In this study, we built new predictive models of oil and gas, wind, and residential development and applied build-out scenarios to simulate future development and measure the efficacy of conservation actions for maintaining sage-grouse populations. Our approach predicts sage-grouse population losses averted through conservation action and quantifies return on investment for different conservation strategies. We estimate that without conservation, sage-grouse populations in Wyoming will decrease under our long-term scenario by 14-29% (95% CI: 4-46%). However, a conservation strategy that includes the "core area" policy and $250 million in targeted easements could reduce these losses to 9-15% (95% CI: 3-32%), cutting anticipated losses by roughly half statewide and nearly two-thirds within sage-grouse core breeding areas. Core area policy is the single most important component, and targeted easements are complementary to the overall strategy. There is considerable uncertainty around the magnitude of our estimates; however, the relative benefit of different conservation scenarios remains comparable because potential biases and assumptions are consistently applied regardless of the strategy. There is early evidence based on a 40% reduction in leased hectares inside core areas that Wyoming policy is reducing potential for future fragmentation inside core areas. Our framework using build-out scenarios to anticipate species declines provides estimates that could be used by decision makers to determine if expected population losses warrant ESA listing.

Measuring the Effectiveness of Conservation: A Novel Framework to Quantify the Benefits of Sage-Grouse Conservation Policy and Easements in Wyoming

PubMed Central

Copeland, Holly E.; Pocewicz, Amy; Naugle, David E.; Griffiths, Tim; Keinath, Doug; Evans, Jeffrey; Platt, James

2013-01-01

Increasing energy and housing demands are impacting wildlife populations throughout western North America. Greater sage-grouse (Centrocercus urophasianus), a species known for its sensitivity to landscape-scale disturbance, inhabits the same low elevation sage-steppe in which much of this development is occurring. Wyoming has committed to maintain sage-grouse populations through conservation easements and policy changes that conserves high bird abundance “core” habitat and encourages development in less sensitive landscapes. In this study, we built new predictive models of oil and gas, wind, and residential development and applied build-out scenarios to simulate future development and measure the efficacy of conservation actions for maintaining sage-grouse populations. Our approach predicts sage-grouse population losses averted through conservation action and quantifies return on investment for different conservation strategies. We estimate that without conservation, sage-grouse populations in Wyoming will decrease under our long-term scenario by 14–29% (95% CI: 4–46%). However, a conservation strategy that includes the “core area” policy and $250 million in targeted easements could reduce these losses to 9–15% (95% CI: 3–32%), cutting anticipated losses by roughly half statewide and nearly two-thirds within sage-grouse core breeding areas. Core area policy is the single most important component, and targeted easements are complementary to the overall strategy. There is considerable uncertainty around the magnitude of our estimates; however, the relative benefit of different conservation scenarios remains comparable because potential biases and assumptions are consistently applied regardless of the strategy. There is early evidence based on a 40% reduction in leased hectares inside core areas that Wyoming policy is reducing potential for future fragmentation inside core areas. Our framework using build-out scenarios to anticipate species declines provides estimates that could be used by decision makers to determine if expected population losses warrant ESA listing. PMID:23826250

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions

PubMed Central

Lawley, Mark A.; Siscovick, David S.; Zhang, Donglan; Pagán, José A.

2016-01-01

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions. PMID:27236380

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions.

PubMed

Li, Yan; Lawley, Mark A; Siscovick, David S; Zhang, Donglan; Pagán, José A

2016-05-26

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions.

Adaptive harvest management of North American waterfowl populations - recent successes and future prospects

USGS Publications Warehouse

Nichols, J.D.; Runge, M.C.; Johnson, F.A.; Williams, B.K.; Schodde, Richard; Hannon, Susan; Scheiffarth, Gregor; Bairlein, Franz

2006-01-01

The history of North American waterfowl harvest management has been characterized by attempts to use population monitoring data to make informed harvest management decisions. Early attempts can be characterized as intuitive decision processes, and later efforts were guided increasingly by population models and associated predictions. In 1995, a formal adaptive management process was implemented, and annual decisions about duck harvest regulations in the United States are still based on this process. This formal decision process is designed to deal appropriately with the various forms of uncertainty that characterize management decisions, environmental uncertainty, structural uncertainty, partial controllability and partial observability. The key components of the process are (1) objectives, (2) potential management actions, (3) model(s) of population response to management actions, (4) credibility measures for these models, and (5) a monitoring program. The operation of this iterative process is described, and a brief history of a decade of its use is presented. Future challenges range from social and political issues such as appropriate objectives and management actions, to technical issues such as multispecies management, geographic allocation of harvest, and incorporation of actions that include habitat acquisition and management.

Determining the drivers of population structure in a highly urbanized landscape to inform conservation planning.

PubMed

Thomassen, Henri A; Harrigan, Ryan J; Semple Delaney, Kathleen; Riley, Seth P D; Serieys, Laurel E K; Pease, Katherine; Wayne, Robert K; Smith, Thomas B

2018-02-01

Understanding the environmental contributors to population structure is of paramount importance for conservation in urbanized environments. We used spatially explicit models to determine genetic population structure under current and future environmental conditions across a highly fragmented, human-dominated environment in Southern California to assess the effects of natural ecological variation and urbanization. We focused on 7 common species with diverse habitat requirements, home-range sizes, and dispersal abilities. We quantified the relative roles of potential barriers, including natural environmental characteristics and an anthropogenic barrier created by a major highway, in shaping genetic variation. The ability to predict genetic variation in our models differed among species: 11-81% of intraspecific genetic variation was explained by environmental variables. Although an anthropogenically induced barrier (a major highway) severely restricted gene flow and movement at broad scales for some species, genetic variation seemed to be primarily driven by natural environmental heterogeneity at a local level. Our results show how assessing environmentally associated variation for multiple species under current and future climate conditions can help identify priority regions for maximizing population persistence under environmental change in urbanized regions. © 2017 Society for Conservation Biology.

The Use of Telemedicine and Mobile Technology to Promote Population Health and Population Management for Psychiatric Disorders.

PubMed

Turvey, Carolyn; Fortney, John

2017-10-16

This article discusses recent applications in telemedicine to promote the goals of population health and population management for people suffering psychiatric disorders. The use of telemedicine to promote collaborative care, self-monitoring and chronic disease management, and population screening has demonstrated broad applicability and effectiveness. Collaborative care using videoconferencing to facilitate mental health specialty consults has demonstrated effectiveness in the treatment of depression, PTSD, and also ADHD in pediatric populations. Mobile health is currently being harnessed to monitor patient symptom trajectories with the goal of using machine learning algorithms to predict illness relapse. Patient portals serve as a bridge between patients and providers. They provide an electronically secure shared space for providers and patients to collaborate and optimize care. To date, research has supported the effectiveness of telemedicine in promoting population health. Future endeavors should focus on developing the most effective clinical protocols for using these technologies to ensure long-term use and maximum effectiveness in reducing population burden of mental health.

The Predicted Influence of Climate Change on Lesser Prairie-Chicken Reproductive Parameters

PubMed Central

Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, Dawn M.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001–2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter’s linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival. PMID:23874549

Using population viability analysis, genomics, and habitat suitability to forecast future population patterns of Little Owl Athene noctua across Europe.

PubMed

Andersen, Line Holm; Sunde, Peter; Pellegrino, Irene; Loeschcke, Volker; Pertoldi, Cino

2017-12-01

The agricultural scene has changed over the past decades, resulting in a declining population trend in many species. It is therefore important to determine the factors that the individual species depend on in order to understand their decline. The landscape changes have also resulted in habitat fragmentation, turning once continuous populations into metapopulations. It is thus increasingly important to estimate both the number of individuals it takes to create a genetically viable population and the population trend. Here, population viability analysis and habitat suitability modeling were used to estimate population viability and future prospects across Europe of the Little Owl Athene noctua , a widespread species associated with agricultural landscapes. The results show a high risk of population declines over the coming 100 years, especially toward the north of Europe, whereas populations toward the southeastern part of Europe have a greater probability of persistence. In order to be considered genetically viable, individual populations must count 1,000-30,000 individuals. As Little Owl populations of several countries count <30,000, and many isolated populations in northern Europe count <1,000 individuals, management actions resulting in exchange of individuals between populations or even countries are probably necessary to prevent losing <1% genetic diversity over a 100-year period. At a continental scale, a habitat suitability analysis suggested Little Owl to be affected positively by increasing temperatures and urban areas, whereas an increased tree cover, an increasing annual rainfall, grassland, and sparsely vegetated areas affect the presence of the owl negatively. However, the low predictive power of the habitat suitability model suggests that habitat suitability might be better explained at a smaller scale.

Research on the food security condition and food supply capacity of Egypt.

PubMed

Deng, Jian; Xiang, Youzhen; Hao, Wenhui; Feng, Yongzhong; Yang, Gaihe; Ren, Guangxin; Han, Xinhui

2014-01-01

Food security is chronically guaranteed in Egypt because of the food subsidy policy of the country. However, the increasing Egyptian population is straining the food supply. To study changes in Egyptian food security and future food supply capacity, we analysed the historical grain production, yield per unit, grain-cultivated area, and per capita grain possession of Egypt. The GM (1,1) model of the grey system was used to predict the future population. Thereafter, the result was combined with scenario analysis to forecast the grain possession and population carrying capacity of Egypt under different scenarios. Results show that the increasing population and limitations in cultivated land will strain Egyptian food security. Only in high cultivated areas and high grain yield scenarios before 2020, or in high cultivated areas and mid grain yield scenarios before 2015, can food supply be basically satisfied (assurance rate ≥ 80%) under a standard of 400 kg per capita. Population carrying capacity in 2030 is between 51.45 and 89.35 million. Thus, we propose the use of advanced technologies in agriculture and the adjustment of plant structure and cropping systems to improve land utilization efficiency. Furthermore, urbanization and other uses of cultivated land should be strictly controlled to ensure the planting of grains.

Comparing Climate Change and Species Invasions as Drivers of Coldwater Fish Population Extirpations

PubMed Central

Sharma, Sapna; Vander Zanden, M. Jake; Magnuson, John J.; Lyons, John

2011-01-01

Species are influenced by multiple environmental stressors acting simultaneously. Our objective was to compare the expected effects of climate change and invasion of non-indigenous rainbow smelt (Osmerus mordax) on cisco (Coregonus artedii) population extirpations at a regional level. We assembled a database of over 13,000 lakes in Wisconsin, USA, summarising fish occurrence, lake morphology, water chemistry, and climate. We used A1, A2, and B1 scenarios from the Intergovernmental Panel on Climate Change (IPCC) of future temperature conditions for 15 general circulation models in 2046–2065 and 2081–2100 totalling 78 projections. Logistic regression indicated that cisco tended to occur in cooler, larger, and deeper lakes. Depending upon the amount of warming, 25–70% of cisco populations are predicted to be extirpated by 2100. In addition, cisco are influenced by the invasion of rainbow smelt, which prey on young cisco. Projecting current estimates of rainbow smelt spread and impact into the future will result in the extirpation of about 1% of cisco populations by 2100 in Wisconsin. Overall, the effect of climate change is expected to overshadow that of species invasion as a driver of coldwater fish population extirpations. Our results highlight the potentially dominant role of climate change as a driver of biotic change. PMID:21860661

Comparing climate change and species invasions as drivers of coldwater fish population extirpations.

PubMed

Sharma, Sapna; Vander Zanden, M Jake; Magnuson, John J; Lyons, John

2011-01-01

Species are influenced by multiple environmental stressors acting simultaneously. Our objective was to compare the expected effects of climate change and invasion of non-indigenous rainbow smelt (Osmerus mordax) on cisco (Coregonus artedii) population extirpations at a regional level. We assembled a database of over 13,000 lakes in Wisconsin, USA, summarising fish occurrence, lake morphology, water chemistry, and climate. We used A1, A2, and B1 scenarios from the Intergovernmental Panel on Climate Change (IPCC) of future temperature conditions for 15 general circulation models in 2046-2065 and 2081-2100 totalling 78 projections. Logistic regression indicated that cisco tended to occur in cooler, larger, and deeper lakes. Depending upon the amount of warming, 25-70% of cisco populations are predicted to be extirpated by 2100. In addition, cisco are influenced by the invasion of rainbow smelt, which prey on young cisco. Projecting current estimates of rainbow smelt spread and impact into the future will result in the extirpation of about 1% of cisco populations by 2100 in Wisconsin. Overall, the effect of climate change is expected to overshadow that of species invasion as a driver of coldwater fish population extirpations. Our results highlight the potentially dominant role of climate change as a driver of biotic change.

Pleural mesothelioma and lung cancer risks in relation to occupational history and asbestos lung burden

PubMed Central

Gilham, Clare; Rake, Christine; Burdett, Garry; Nicholson, Andrew G; Davison, Leslie; Franchini, Angelo; Carpenter, James; Hodgson, John; Darnton, Andrew; Peto, Julian

2016-01-01

Background We have conducted a population-based study of pleural mesothelioma patients with occupational histories and measured asbestos lung burdens in occupationally exposed workers and in the general population. The relationship between lung burden and risk, particularly at environmental exposure levels, will enable future mesothelioma rates in people born after 1965 who never installed asbestos to be predicted from their asbestos lung burdens. Methods Following personal interview asbestos fibres longer than 5 µm were counted by transmission electron microscopy in lung samples obtained from 133 patients with mesothelioma and 262 patients with lung cancer. ORs for mesothelioma were converted to lifetime risks. Results Lifetime mesothelioma risk is approximately 0.02% per 1000 amphibole fibres per gram of dry lung tissue over a more than 100-fold range, from 1 to 4 in the most heavily exposed building workers to less than 1 in 500 in most of the population. The asbestos fibres counted were amosite (75%), crocidolite (18%), other amphiboles (5%) and chrysotile (2%). Conclusions The approximate linearity of the dose–response together with lung burden measurements in younger people will provide reasonably reliable predictions of future mesothelioma rates in those born since 1965 whose risks cannot yet be seen in national rates. Burdens in those born more recently will indicate the continuing occupational and environmental hazards under current asbestos control regulations. Our results confirm the major contribution of amosite to UK mesothelioma incidence and the substantial contribution of non-occupational exposure, particularly in women. PMID:26715106

Wildlife habitat connectivity in the changing climate of New York's Hudson Valley.

PubMed

Howard, Timothy G; Schlesinger, Matthew D

2013-09-01

Maintaining and restoring connectivity are key adaptation strategies for biodiversity conservation under climate change. We present a novel combination of species distribution and connectivity modeling using current and future climate regimes to prioritize connections among populations of 26 rare species in New York's Hudson Valley. We modeled patches for each species for each time period and modeled potential connections among habitat patches by finding the least-cost path for every patch-to-patch connection. Finally, we aggregated these patches and paths to the tax parcel, commonly the primary unit of conservation action. Under future climate regimes, suitable habitat was predicted to contract or appear upslope and farther north. On average, predicted patches were nine times smaller and paths were twice as long under future climate. Parcels within the Hudson Highlands, Shawangunk Ridge, Catskill Mountains, and Harlem Valley had high species overlap, with areas upslope and northward increasing in importance over time. We envision that land managers and conservation planners can use these results to help prioritize parcel-level conservation and management and thus support biodiversity adaptation to climate change. © 2013 New York Academy of Sciences.

Wolf population dynamics in the U.S. Northern Rocky Mountains are affected by recruitment and human-caused mortality

USGS Publications Warehouse

Gude, J.A.; Mitchell, M.S.; Russell, R.E.; Sime, C.A.; Bangs, E.E.; Mech, L.D.; Ream, R.R.

2012-01-01

Reliable analyses can help wildlife managers make good decisions, which are particularly critical for controversial decisions such as wolf (Canis lupus) harvest. Creel and Rotella (2010) recently predicted substantial population declines in Montana wolf populations due to harvest, in contrast to predictions made by Montana Fish, Wildlife and Parks (MFWP). We replicated their analyses considering only those years in which field monitoring was consistent, and we considered the effect of annual variation in recruitment on wolf population growth. Rather than assuming constant rates, we used model selection methods to evaluate and incorporate models of factors driving recruitment and human-caused mortality rates in wolf populations in the Northern Rocky Mountains. Using data from 27 area-years of intensive wolf monitoring, we show that variation in both recruitment and human-caused mortality affect annual wolf population growth rates and that human-caused mortality rates have increased with the sizes of wolf populations. We document that recruitment rates have decreased over time, and we speculate that rates have decreased with increasing population sizes and/or that the ability of current field resources to document recruitment rates has recently become less successful as the number of wolves in the region has increased. Estimates of positive wolf population growth in Montana from our top models are consistent with field observations and estimates previously made by MFWP for 2008-2010, whereas the predictions for declining wolf populations of Creel and Rotella (2010) are not. Familiarity with limitations of raw data, obtained first-hand or through consultation with scientists who collected the data, helps generate more reliable inferences and conclusions in analyses of publicly available datasets. Additionally, development of efficient monitoring methods for wolves is a pressing need, so that analyses such as ours will be possible in future years when fewer resources will be available for monitoring. ?? 2011 The Wildlife Society. Copyright ?? The Wildlife Society, 2011.

Predicting mortality with biomarkers: a population-based prospective cohort study for elderly Costa Ricans

PubMed Central

2012-01-01

Background Little is known about adult health and mortality relationships outside high-income nations, partly because few datasets have contained biomarker data in representative populations. Our objective is to determine the prognostic value of biomarkers with respect to total and cardiovascular mortality in an elderly population of a middle-income country, as well as the extent to which they mediate the effects of age and sex on mortality. Methods This is a prospective population-based study in a nationally representative sample of elderly Costa Ricans. Baseline interviews occurred mostly in 2005 and mortality follow-up went through December 2010. Sample size after excluding observations with missing values: 2,313 individuals and 564 deaths. Main outcome: prospective death rate ratios for 22 baseline biomarkers, which were estimated with hazard regression models. Results Biomarkers significantly predict future death above and beyond demographic and self-reported health conditions. The studied biomarkers account for almost half of the effect of age on mortality. However, the sex gap in mortality became several times wider after controlling for biomarkers. The most powerful predictors were simple physical tests: handgrip strength, pulmonary peak flow, and walking speed. Three blood tests also predicted prospective mortality: C-reactive protein (CRP), glycated hemoglobin (HbA1c), and dehydroepiandrosterone sulfate (DHEAS). Strikingly, high blood pressure (BP) and high total cholesterol showed little or no predictive power. Anthropometric measures also failed to show significant mortality effects. Conclusions This study adds to the growing evidence that blood markers for CRP, HbA1c, and DHEAS, along with organ-specific functional reserve indicators (handgrip, walking speed, and pulmonary peak flow), are valuable tools for identifying vulnerable elderly. The results also highlight the need to better understand an anomaly noted previously in other settings: despite the continued medical focus on drugs for BP and cholesterol, high levels of BP and cholesterol have little predictive value of mortality in this elderly population. PMID:22694922

Integrating physiology, population dynamics and climate to make multi-scale predictions for the spread of an invasive insect: the Argentine ant at Haleakala National Park, Hawaii

USGS Publications Warehouse

Hartley, Stephen; Krushelnycky, Paul D.; Lester, Philip J.

2010-01-01

Mechanistic models for predicting species’ distribution patterns present particular advantages and challenges relative to models developed from statistical correlations between distribution and climate. They can be especially useful for predicting the range of invasive species whose distribution has not yet reached equilibrium. Here, we illustrate how a physiological model of development for the invasive Argentine ant can be connected to differences in micro-site suitability, population dynamics and climatic gradients; processes operating at quite different spatial scales. Our study is located in the subalpine shrubland of Haleakala National Park, Hawaii, where the spread of Argentine ants Linepithema humile has been documented for the past twenty-five years. We report four main results. First, at a microsite level, the accumulation of degree-days recorded in potential ant nest sites under bare ground or rocks was significantly greater than under a groundcover of grassy vegetation. Second, annual degree-days measured where population boundaries have not expanded (456-521 degree-days), were just above the developmental requirements identified from earlier laboratory studies (445 degree-days above 15.98C). Third, rates of population expansion showed a strong linear relationship with annual degree-days. Finally, an empirical relationship between soil degree-days and climate variables mapped at a broader scale predicts the potential for future range expansion of Argentine ants at Haleakala, particularly to the west of the lower colony and the east of the upper colony. Variation in the availability of suitable microsites, driven by changes in vegetation cover and ultimately climate, provide a hierarchical understanding of the distribution of Argentine ants close to their cold-wet limit of climatic tolerances. We conclude that the integration of physiology, population dynamics and climate mapping holds much promise for making more robust predictions about the potential spread of invasive species.

Characterizing the impact of projected changes in climate and air quality on human exposures to ozone.

PubMed

Dionisio, Kathie L; Nolte, Christopher G; Spero, Tanya L; Graham, Stephen; Caraway, Nina; Foley, Kristen M; Isaacs, Kristin K

2017-05-01

The impact of climate change on human and environmental health is of critical concern. Population exposures to air pollutants both indoors and outdoors are influenced by a wide range of air quality, meteorological, behavioral, and housing-related factors, many of which are also impacted by climate change. An integrated methodology for modeling changes in human exposures to tropospheric ozone (O 3 ) owing to potential future changes in climate and demographics was implemented by linking existing modeling tools for climate, weather, air quality, population distribution, and human exposure. Human exposure results from the Air Pollutants Exposure Model (APEX) for 12 US cities show differences in daily maximum 8-h (DM8H) exposure patterns and levels by sex, age, and city for all scenarios. When climate is held constant and population demographics are varied, minimal difference in O 3 exposures is predicted even with the most extreme demographic change scenario. In contrast, when population is held constant, we see evidence of substantial changes in O 3 exposure for the most extreme change in climate. Similarly, we see increases in the percentage of the population in each city with at least one O 3 exposure exceedance above 60 p.p.b and 70 p.p.b thresholds for future changes in climate. For these climate and population scenarios, the impact of projected changes in climate and air quality on human exposure to O 3 are much larger than the impacts of changing demographics. These results indicate the potential for future changes in O 3 exposure as a result of changes in climate that could impact human health.

Modeling the role of environmental variables on the population dynamics of the malaria vector Anopheles gambiae sensu stricto

PubMed Central

2012-01-01

Background The impact of weather and climate on malaria transmission has attracted considerable attention in recent years, yet uncertainties around future disease trends under climate change remain. Mathematical models provide powerful tools for addressing such questions and understanding the implications for interventions and eradication strategies, but these require realistic modeling of the vector population dynamics and its response to environmental variables. Methods Published and unpublished field and experimental data are used to develop new formulations for modeling the relationships between key aspects of vector ecology and environmental variables. These relationships are integrated within a validated deterministic model of Anopheles gambiae s.s. population dynamics to provide a valuable tool for understanding vector response to biotic and abiotic variables. Results A novel, parsimonious framework for assessing the effects of rainfall, cloudiness, wind speed, desiccation, temperature, relative humidity and density-dependence on vector abundance is developed, allowing ease of construction, analysis, and integration into malaria transmission models. Model validation shows good agreement with longitudinal vector abundance data from Tanzania, suggesting that recent malaria reductions in certain areas of Africa could be due to changing environmental conditions affecting vector populations. Conclusions Mathematical models provide a powerful, explanatory means of understanding the role of environmental variables on mosquito populations and hence for predicting future malaria transmission under global change. The framework developed provides a valuable advance in this respect, but also highlights key research gaps that need to be resolved if we are to better understand future malaria risk in vulnerable communities. PMID:22877154

Response of Groundwater Recharge to Potential Future Climate Change in the Grand River Watershed

NASA Astrophysics Data System (ADS)

Jyrkama, M. I.; Sykes, J. F.

2004-05-01

The Grand River watershed is situated in south-western Ontario, draining an area of nearly 7000 square kilometres into Lake Erie. Approximately eighty percent of the population in the watershed derive their drinking water from groundwater sources. Quantifying the recharge input to the groundwater system and the impact of climate variability due to climate change is, therefore, essential for ensuring the quantity and sustainability of the watershed's drinking water resources in the future. The primary goal of this study is to investigate the impact of potential future climate changes on groundwater recharge in the Grand River watershed. The physically based hydrologic model HELP3 is used in conjunction with GIS to simulate the past conditions and future changes in evapotranspiration, potential surface runoff, and groundwater recharge rates as a result of projected changes in the regions climate. The climate change projections are based on the general predictions reported by the Intergovernmental Panel on Climate Change (IPCC) in 2001. Forty years of daily historical weather data are used as the reference condition. The impact of climate change on the hydrologic cycle over a forty year study period is modelled by perturbing the HELP3 model input parameters using predicted future changes in precipitation, temperature, and solar radiation. The changes in land use and vegetation cover over time were not considered in the study. The results of the study indicate that the overall simulated rate of groundwater recharge is predicted to increase in the watershed as a result of the projected future climate change. Warmer winter temperatures will reduce the extent and duration of ground frost and shift the springmelt from spring toward winter months, allowing more water to infiltrate into the ground. This results in decreased surface runoff, higher infiltration, and subsequently increased groundwater recharge. The predicted higher intensity and frequency of future precipitation will not only contribute significantly to increased surface runoff, but also results in higher evapotranspiration and groundwater recharge rates due to increased amounts of available water. Changes in the incoming solar radiation have a minimal impact on the simulated hydrologic processes. The overall simulated average annual recharge in the watershed is predicted to increase by approximately 100 mm/year over the next forty years from 189 mm/year to 289 mm/year.

The impacts of climate, land use, and demography on fires during the 21st century simulated by CLM-CN

NASA Astrophysics Data System (ADS)

Kloster, S.; Mahowald, N. M.; Randerson, J. T.; Lawrence, P. J.

2012-01-01

Landscape fires during the 21st century are expected to change in response to multiple agents of global change. Important controlling factors include climate controls on the length and intensity of the fire season, fuel availability, and fire management, which are already anthropogenically perturbed today and are predicted to change further in the future. An improved understanding of future fires will contribute to an improved ability to project future anthropogenic climate change, as changes in fire activity will in turn impact climate. In the present study we used a coupled-carbon-fire model to investigate how changes in climate, demography, and land use may alter fire emissions. We used climate projections following the SRES A1B scenario from two different climate models (ECHAM5/MPI-OM and CCSM) and changes in population. Land use and harvest rates were prescribed according to the RCP 45 scenario. In response to the combined effect of all these drivers, our model estimated, depending on our choice of climate projection, an increase in future (2075-2099) fire carbon emissions by 17 and 62% compared to present day (1985-2009). The largest increase in fire emissions was predicted for Southern Hemisphere South America for both climate projections. For Northern Hemisphere Africa, a region that contributed significantly to the global total fire carbon emissions, the response varied between a decrease and an increase depending on the climate projection. We disentangled the contribution of the single forcing factors to the overall response by conducting an additional set of simulations in which each factor was individually held constant at pre-industrial levels. The two different projections of future climate change evaluated in this study led to increases in global fire carbon emissions by 22% (CCSM) and 66% (ECHAM5/MPI-OM). The RCP 45 projection of harvest and land use led to a decrease in fire carbon emissions by -5%. The RCP 26 and RCP 60 harvest and landuse projections caused decreases around -20%. Changes in human ignition led to an increase of 20%. When we also included changes in fire management efforts to suppress fires in densely populated areas, global fire carbon emission decreased by -6% in response to changes in population density. We concluded from this study that changes in fire emissions in the future are controlled by multiple interacting factors. Although changes in climate led to an increase in future fire emissions this could be globally counterbalanced by coupled changes in land use, harvest, and demography.

Changing climate in Hungary and trends in the annual number of heat stress days

NASA Astrophysics Data System (ADS)

Solymosi, Norbert; Torma, Csaba; Kern, Anikó; Maróti-Agóts, Ákos; Barcza, Zoltán; Könyves, László; Berke, Olaf; Reiczigel, Jenő

2010-07-01

Global climate change can have serious direct effects on animal health and production through heat stress. In Hungary, the number of heat stress days per year (YNHD), i.e., days when the temperature humidity index (THI) is above a specific comfort threshold, has increased in recent years based on observed meteorological data. Between 1973 and 2008, the countrywide average increase in YNHD was 4.1% per year. Climate scenarios based on regional climate models (RCM) were used to predict possible changes in YNHD for the near future (2021-2050) relative to the reference period (1961-1990). This comparison shows that, in Hungary, the 30-year mean of YNHD is expected to increase by between 1 and 27 days, depending on the RCM used. Half of the scenarios investigated in this study predicted that, in large parts of Hungary, YNHD will increase by at least 1 week. However, the increase observed in the past, and that predicted for the near future, is spatially heterogeneous, and areas that currently have large cattle populations are expected to be affected more severely than other regions.

Non-additive Effects in Genomic Selection

PubMed Central

Varona, Luis; Legarra, Andres; Toro, Miguel A.; Vitezica, Zulma G.

2018-01-01

In the last decade, genomic selection has become a standard in the genetic evaluation of livestock populations. However, most procedures for the implementation of genomic selection only consider the additive effects associated with SNP (Single Nucleotide Polymorphism) markers used to calculate the prediction of the breeding values of candidates for selection. Nevertheless, the availability of estimates of non-additive effects is of interest because: (i) they contribute to an increase in the accuracy of the prediction of breeding values and the genetic response; (ii) they allow the definition of mate allocation procedures between candidates for selection; and (iii) they can be used to enhance non-additive genetic variation through the definition of appropriate crossbreeding or purebred breeding schemes. This study presents a review of methods for the incorporation of non-additive genetic effects into genomic selection procedures and their potential applications in the prediction of future performance, mate allocation, crossbreeding, and purebred selection. The work concludes with a brief outline of some ideas for future lines of that may help the standard inclusion of non-additive effects in genomic selection. PMID:29559995

Non-additive Effects in Genomic Selection.

PubMed

Varona, Luis; Legarra, Andres; Toro, Miguel A; Vitezica, Zulma G

2018-01-01

In the last decade, genomic selection has become a standard in the genetic evaluation of livestock populations. However, most procedures for the implementation of genomic selection only consider the additive effects associated with SNP (Single Nucleotide Polymorphism) markers used to calculate the prediction of the breeding values of candidates for selection. Nevertheless, the availability of estimates of non-additive effects is of interest because: (i) they contribute to an increase in the accuracy of the prediction of breeding values and the genetic response; (ii) they allow the definition of mate allocation procedures between candidates for selection; and (iii) they can be used to enhance non-additive genetic variation through the definition of appropriate crossbreeding or purebred breeding schemes. This study presents a review of methods for the incorporation of non-additive genetic effects into genomic selection procedures and their potential applications in the prediction of future performance, mate allocation, crossbreeding, and purebred selection. The work concludes with a brief outline of some ideas for future lines of that may help the standard inclusion of non-additive effects in genomic selection.

The Deterministic Information Bottleneck

NASA Astrophysics Data System (ADS)

Strouse, D. J.; Schwab, David

2015-03-01

A fundamental and ubiquitous task that all organisms face is prediction of the future based on past sensory experience. Since an individual's memory resources are limited and costly, however, there is a tradeoff between memory cost and predictive payoff. The information bottleneck (IB) method (Tishby, Pereira, & Bialek 2000) formulates this tradeoff as a mathematical optimization problem using an information theoretic cost function. IB encourages storing as few bits of past sensory input as possible while selectively preserving the bits that are most predictive of the future. Here we introduce an alternative formulation of the IB method, which we call the deterministic information bottleneck (DIB). First, we argue for an alternative cost function, which better represents the biologically-motivated goal of minimizing required memory resources. Then, we show that this seemingly minor change has the dramatic effect of converting the optimal memory encoder from stochastic to deterministic. Next, we propose an iterative algorithm for solving the DIB problem. Additionally, we compare the IB and DIB methods on a variety of synthetic datasets, and examine the performance of retinal ganglion cell populations relative to the optimal encoding strategy for each problem.

Applying landscape genomic tools to forest management and restoration of Hawaiian koa (Acacia koa) in a changing environment.

PubMed

Gugger, Paul F; Liang, Christina T; Sork, Victoria L; Hodgskiss, Paul; Wright, Jessica W

2018-02-01

Identifying and quantifying the importance of environmental variables in structuring population genetic variation can help inform management decisions for conservation, restoration, or reforestation purposes, in both current and future environmental conditions. Landscape genomics offers a powerful approach for understanding the environmental factors that currently associate with genetic variation, and given those associations, where populations may be most vulnerable under future environmental change. Here, we applied genotyping by sequencing to generate over 11,000 single nucleotide polymorphisms from 311 trees and then used nonlinear, multivariate environmental association methods to examine spatial genetic structure and its association with environmental variation in an ecologically and economically important tree species endemic to Hawaii, Acacia koa . Admixture and principal components analyses showed that trees from different islands are genetically distinct in general, with the exception of some genotypes that match other islands, likely as the result of recent translocations. Gradient forest and generalized dissimilarity models both revealed a strong association between genetic structure and mean annual rainfall. Utilizing a model for projected future climate on the island of Hawaii, we show that predicted changes in rainfall patterns may result in genetic offset, such that trees no longer may be genetically matched to their environment. These findings indicate that knowledge of current and future rainfall gradients can provide valuable information for the conservation of existing populations and also help refine seed transfer guidelines for reforestation or replanting of koa throughout the state.

Threats to coastal communities of Mahanadi delta due to imminent consequences of erosion - Present and near future.

PubMed

Mukhopadhyay, Anirban; Ghosh, Pramit; Chanda, Abhra; Ghosh, Amit; Ghosh, Subhajit; Das, Shouvik; Ghosh, Tuhin; Hazra, Sugata

2018-05-11

Coastal erosion is a natural hazard which causes significant loss to properties as well as coastal habitats. Coastal districts of Mahanadi delta, one of the most populated deltas of the Indian subcontinent, are suffering from the ill effects of coastal erosion. An important amount of assets is being lost every year along with forced migration of huge portions of coastal communities due to erosion. An attempt has been made in this study to predict the future coastline of the Mahanadi Delta based on historical trends. Historical coastlines of the delta have been extracted using semi-automated Tasselled Cap technique from the LANDSAT satellite imageries of the year 1990, 1995, 2000, 2006 and 2010. Using Digital Shoreline Assessment System (DSAS) tool of USGS, the trend of the coastline has been assessed in the form of End Point Rate (EPR) and Linear Regression Rate (LRR). A hybrid methodology has been adopted using statistical (EPR) and trigonometric functions to predict the future positions of the coastlines of the years 2020, 2035 and 2050. The result showed that most of the coastline (≈65%) is facing erosion at present. The predicted outcome shows that by the end of year 2050 the erosion scenario will worsen which in turn would lead to very high erosion risk for 30% of the total coastal mouzas (small administrative blocks). This study revealed the coastal erosion trend of Mahanadi delta and based on the predicted coastlines it can be inferred that the coastal communities in near future would be facing substantial threat due to erosion particularly in areas surrounding Puri (a renowned tourist pilgrimage) and Paradwip (one of the busiest ports and harbours of the country). Copyright © 2018 Elsevier B.V. All rights reserved.

Accuracy of Genomic Prediction in Switchgrass (Panicum virgatum L.) Improved by Accounting for Linkage Disequilibrium

PubMed Central

Ramstein, Guillaume P.; Evans, Joseph; Kaeppler, Shawn M.; Mitchell, Robert B.; Vogel, Kenneth P.; Buell, C. Robin; Casler, Michael D.

2016-01-01

Switchgrass is a relatively high-yielding and environmentally sustainable biomass crop, but further genetic gains in biomass yield must be achieved to make it an economically viable bioenergy feedstock. Genomic selection (GS) is an attractive technology to generate rapid genetic gains in switchgrass, and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. In this study, we empirically assessed prediction procedures for genomic selection in two different populations, consisting of 137 and 110 half-sib families of switchgrass, tested in two locations in the United States for three agronomic traits: dry matter yield, plant height, and heading date. Marker data were produced for the families’ parents by exome capture sequencing, generating up to 141,030 polymorphic markers with available genomic-location and annotation information. We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data were preprocessed to account for redundancy in marker information. More complex genomic prediction procedures were generally not significantly more accurate than the simplest procedure, likely due to limited population sizes. Nevertheless, a highly significant gain in prediction accuracy was achieved by transforming the marker data through a marker correlation matrix. Our results suggest that marker-data transformations and, more generally, the account of linkage disequilibrium among markers, offer valuable opportunities for improving prediction procedures in GS. Some of the achieved prediction accuracies should motivate implementation of GS in switchgrass breeding programs. PMID:26869619

Sick Leave within 5 Years of Whiplash Trauma Predicts Recovery: A Prospective Cohort and Register-Based Study

PubMed Central

Carstensen, Tina Birgitte Wisbech; Fink, Per; Oernboel, Eva; Kasch, Helge; Jensen, Troels Staehelin; Frostholm, Lisbeth

2015-01-01

Background 10–22% of individuals sustaining whiplash trauma develop persistent symptoms resulting in reduced working ability and decreased quality of life, but it is poorly understood why some people do not recover. Various collision and post-collision risk factors have been studied, but little is known about pre-collision risk factors. In particular, the impact of sickness and socioeconomic factors before the collision on recovery is sparsely explored. The aim of this study was to examine if welfare payments received within five years pre-collision predict neck pain and negative change in provisional situation one year post-collision. Methods and Findings 719 individuals with acute whiplash trauma consecutively recruited from emergency departments or primary care after car accidents in Denmark completed questionnaires on socio-demographic and health factors immediately after the collision. After 12 months, a visual analogue scale on neck pain intensity was completed. 3595 matched controls in the general population were sampled, and national public register data on social benefits and any other welfare payments were obtained for participants with acute whiplash trauma and controls from five years pre-collision to 15 months after. Participants with acute whiplash trauma who had received sickness benefit for more than 12 weeks pre-collision had increased odds for negative change in future provisional situation (Odds Ratio (OR) (95% Confidence Interval (CI) = 3.8 (2.1;7.1)) and future neck pain (OR (95%CI) = 3.3 (1.8;6.3)), controlling for other known risk factors. Participants with acute whiplash trauma had weaker attachment to labour market (more weeks of sick leave (χ2(2) = 36.7, p < 0.001) and unemployment (χ2(2) = 12.5, p = 0.002)) pre-collision compared with controls. Experiencing a whiplash trauma raised the odds for future negative change in provisional situation (OR (95%CI) = 3.1 (2.3;4.4)) compared with controls. Conclusions Sick leave before the collision strongly predicted prolonged recovery following whiplash trauma. Participants with acute whiplash trauma had weaker attachment to labour market pre-collision compared with the general population. Neck pain at inclusion predicted future neck pain. Acute whiplash trauma may trigger pre-existing vulnerabilities increasing risk of developing whiplash-associated disorders. PMID:26098860

Forest management under uncertainty for multiple bird population objectives

USGS Publications Warehouse

Moore, C.T.; Plummer, W.T.; Conroy, M.J.; Ralph, C. John; Rich, Terrell D.

2005-01-01

We advocate adaptive programs of decision making and monitoring for the management of forest birds when responses by populations to management, and particularly management trade-offs among populations, are uncertain. Models are necessary components of adaptive management. Under this approach, uncertainty about the behavior of a managed system is explicitly captured in a set of alternative models. The models generate testable predictions about the response of populations to management, and monitoring data provide the basis for assessing these predictions and informing future management decisions. To illustrate these principles, we examine forest management at the Piedmont National Wildlife Refuge, where management attention is focused on the recovery of the Red-cockaded Woodpecker (Picoides borealis) population. However, managers are also sensitive to the habitat needs of many non-target organisms, including Wood Thrushes (Hylocichla mustelina) and other forest interior Neotropical migratory birds. By simulating several management policies on a set of-alternative forest and bird models, we found a decision policy that maximized a composite response by woodpeckers and Wood Thrushes despite our complete uncertainty regarding system behavior. Furthermore, we used monitoring data to update our measure of belief in each alternative model following one cycle of forest management. This reduction of uncertainty translates into a reallocation of model influence on the choice of optimal decision action at the next decision opportunity.

Small artery elasticity predicts future cardiovascular events in chinese patients with angiographic coronary artery disease.

PubMed

Wan, Zhaofei; Liu, Xiaojun; Wang, Xinhong; Liu, Fuqiang; Liu, Weimin; Wu, Yue; Pei, Leilei; Yuan, Zuyi

2014-04-01

Arterial elasticity has been shown to predict cardiovascular disease (CVD) in apparently healthy populations. The present study aimed to explore whether arterial elasticity could predict CVD events in Chinese patients with angiographic coronary artery disease (CAD). Arterial elasticity of 365 patients with angiographic CAD was measured. During follow-up (48 months; range 6-65), 140 CVD events occurred (including 34 deaths). Univariate Cox analysis demonstrated that both large arterial elasticity and small arterial elasticity were significant predictors of CVD events. Multivariate Cox analysis indicated that small arterial elasticity remained significant. Kaplan-Meier analysis showed that the probability of having a CVD event/CVD death increased with a decrease of small arterial elasticity (P < .001, respectively). Decreased small arterial elasticity independently predicts the risk of CVD events in Chinese patients with angiographic CAD.

The Roles of Dispersal, Fecundity, and Predation in the Population Persistence of an Oak (Quercus engelmannii) under Global Change

PubMed Central

Conlisk, Erin; Lawson, Dawn; Syphard, Alexandra D.; Franklin, Janet; Flint, Lorraine; Flint, Alan; Regan, Helen M.

2012-01-01

A species’ response to climate change depends on the interaction of biotic and abiotic factors that define future habitat suitability and species’ ability to migrate or adapt. The interactive effects of processes such as fire, dispersal, and predation have not been thoroughly addressed in the climate change literature. Our objective was to examine how life history traits, short-term global change perturbations, and long-term climate change interact to affect the likely persistence of an oak species - Quercus engelmannii (Engelmann oak). Specifically, we combined dynamic species distribution models, which predict suitable habitat, with stochastic, stage-based metapopulation models, which project population trajectories, to evaluate the effects of three global change factors – climate change, land use change, and altered fire frequency – emphasizing the roles of dispersal and seed predation. Our model predicted dramatic reduction in Q. engelmannii abundance, especially under drier climates and increased fire frequency. When masting lowers seed predation rates, decreased masting frequency leads to large abundance decreases. Current rates of dispersal are not likely to prevent these effects, although increased dispersal could mitigate population declines. The results suggest that habitat suitability predictions by themselves may under-estimate the impact of climate change for other species and locations. PMID:22623955

The relevance of cultural factors in predicting condom-use intentions among immigrants from the Netherlands Antilles.

PubMed

Kocken, Pl; van Dorst, Ag; Schaalma, H

2006-04-01

A study into the relevance of cultural factors in predicting condom-use intentions among Antillean migrants in the Netherlands is described in this article. The association between the intention to use condoms with a new sexual partner and a perceived taboo on discussing sex, beliefs about sex education and machismo beliefs on gender and power relationships is addressed. The study was conducted among 346 Dutch Antilleans from a random sample of an Antillean population aged 15-50 years. The response rate was 37.8%. The results showed that condom-use intentions were primarily determined by perceived subjective norms, the perceived taboo on discussing sex, machismo attitudes, gender, age and educational background. Moreover, the respondent's opinion regarding machismo was an effect modificator for the association between condom-use intentions and subjective social norm. It is concluded that, in predicting condom-use intentions, factors specific to the culture of a population contribute significantly to the determinants drawn from the general social-cognition models. It is recommended that future research should use measurement instruments that are adapted to culture-specific beliefs, and should explore the influence of cultural factors on actual condom use. Moreover, interventions promoting condom use among migrant populations should target the cultural correlates of condom use.

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach-A Case Study for the City of Wuhan in China.

PubMed

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-06-15

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study-simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.

A predictive framework to understand forest responses to global change.

PubMed

McMahon, Sean M; Dietze, Michael C; Hersh, Michelle H; Moran, Emily V; Clark, James S

2009-04-01

Forests are one of Earth's critical biomes. They have been shown to respond strongly to many of the drivers that are predicted to change natural systems over this century, including climate, introduced species, and other anthropogenic influences. Predicting how different tree species might respond to this complex of forces remains a daunting challenge for forest ecologists. Yet shifts in species composition and abundance can radically influence hydrological and atmospheric systems, plant and animal ranges, and human populations, making this challenge an important one to address. Forest ecologists have gathered a great deal of data over the past decades and are now using novel quantitative and computational tools to translate those data into predictions about the fate of forests. Here, after a brief review of the threats to forests over the next century, one of the more promising approaches to making ecological predictions is described: using hierarchical Bayesian methods to model forest demography and simulating future forests from those models. This approach captures complex processes, such as seed dispersal and mortality, and incorporates uncertainty due to unknown mechanisms, data problems, and parameter uncertainty. After describing the approach, an example by simulating drought for a southeastern forest is offered. Finally, there is a discussion of how this approach and others need to be cast within a framework of prediction that strives to answer the important questions posed to environmental scientists, but does so with a respect for the challenges inherent in predicting the future of a complex biological system.

A Golden Ticket to Future Occupational and Environmental Health Monitoring

DTIC Science & Technology

2015-10-01

by the BE career field, an assessment of the regulatory monitoring requirements and current detection capabilities was critical . The next step in...research criteria due to the inability to predict the cost of production for these detection systems. Until a standardization of mass scale production...the health risk assessment process and is critical to keeping the base population safe from occupational and environmental exposures. The predominant

Near-future carbon dioxide levels alter fish behaviour by interfering with neurotransmitter function

NASA Astrophysics Data System (ADS)

Nilsson, Göran E.; Dixson, Danielle L.; Domenici, Paolo; McCormick, Mark I.; Sørensen, Christina; Watson, Sue-Ann; Munday, Philip L.

2012-03-01

Predicted future CO2 levels have been found to alter sensory responses and behaviour of marine fishes. Changes include increased boldness and activity, loss of behavioural lateralization, altered auditory preferences and impaired olfactory function. Impaired olfactory function makes larval fish attracted to odours they normally avoid, including ones from predators and unfavourable habitats. These behavioural alterations have significant effects on mortality that may have far-reaching implications for population replenishment, community structure and ecosystem function. However, the underlying mechanism linking high CO2 to these diverse responses has been unknown. Here we show that abnormal olfactory preferences and loss of behavioural lateralization exhibited by two species of larval coral reef fish exposed to high CO2 can be rapidly and effectively reversed by treatment with an antagonist of the GABA-A receptor. GABA-A is a major neurotransmitter receptor in the vertebrate brain. Thus, our results indicate that high CO2 interferes with neurotransmitter function, a hitherto unrecognized threat to marine populations and ecosystems. Given the ubiquity and conserved function of GABA-A receptors, we predict that rising CO2 levels could cause sensory and behavioural impairment in a wide range of marine species, especially those that tightly control their acid-base balance through regulatory changes in HCO3- and Cl- levels.

The Pediatric Anesthesiology Workforce: Projecting Supply and Trends 2015-2035.

PubMed

Muffly, Matthew K; Singleton, Mark; Agarwal, Rita; Scheinker, David; Miller, Daniel; Muffly, Tyler M; Honkanen, Anita

2018-02-01

A workforce analysis was conducted to predict whether the projected future supply of pediatric anesthesiologists is balanced with the requirements of the inpatient pediatric population. The specific aims of our analysis were to (1) project the number of pediatric anesthesiologists in the future workforce; (2) project pediatric anesthesiologist-to-pediatric population ratios (0-17 years); (3) project the mean number of inpatient pediatric procedures per pediatric anesthesiologist; and (4) evaluate the effect of alternative projections of individual variables on the model projections through 2035. The future number of pediatric anesthesiologists is determined by the current supply, additions to the workforce, and departures from the workforce. We previously compiled a database of US pediatric anesthesiologists in the base year of 2015. The historical linear growth rate for pediatric anesthesiology fellowship positions was determined using the Accreditation Council for Graduate Medical Education Data Resource Books from 2002 to 2016. The future number of pediatric anesthesiologists in the workforce was projected given growth of pediatric anesthesiology fellowship positions at the historical linear growth rate, modeling that 75% of graduating fellows remain in the pediatric anesthesiology workforce, and anesthesiologists retire at the current mean retirement age of 64 years old. The baseline model projections were accompanied by age- and gender-adjusted anesthesiologist supply, and sensitivity analyses of potential variations in fellowship position growth, retirement, pediatric population, inpatient surgery, and market share to evaluate the effect of each model variable on the baseline model. The projected ratio of pediatric anesthesiologists to pediatric population was determined using the 2012 US Census pediatric population projections. The projected number of inpatient pediatric procedures per pediatric anesthesiologist was determined using the Kids' Inpatient Database historical data to project the future number of inpatient procedures (including out of operating room procedures). In 2015, there were 5.4 pediatric anesthesiologists per 100,000 pediatric population and a mean (±standard deviation [SD]) of 262 ±8 inpatient procedures per pediatric anesthesiologist. If historical trends continue, there will be an estimated 7.4 pediatric anesthesiologists per 100,000 pediatric population and a mean (±SD) 193 ±6 inpatient procedures per pediatric anesthesiologist in 2035. If pediatric anesthesiology fellowship positions plateau at 2015 levels, there will be an estimated 5.7 pediatric anesthesiologists per 100,000 pediatric population and a mean (±SD) 248 ±7 inpatient procedures per pediatric anesthesiologist in 2035. If historical trends continue, the growth in pediatric anesthesiologist supply may exceed the growth in both the pediatric population and inpatient procedures in the 20-year period from 2015 to 2035.

Adaptive and plastic responses of Quercus petraea populations to climate across Europe.

PubMed

Sáenz-Romero, Cuauhtémoc; Lamy, Jean-Baptiste; Ducousso, Alexis; Musch, Brigitte; Ehrenmann, François; Delzon, Sylvain; Cavers, Stephen; Chałupka, Władysław; Dağdaş, Said; Hansen, Jon Kehlet; Lee, Steve J; Liesebach, Mirko; Rau, Hans-Martin; Psomas, Achilleas; Schneck, Volker; Steiner, Wilfried; Zimmermann, Niklaus E; Kremer, Antoine

2017-07-01

How temperate forests will respond to climate change is uncertain; projections range from severe decline to increased growth. We conducted field tests of sessile oak (Quercus petraea), a widespread keystone European forest tree species, including more than 150 000 trees sourced from 116 geographically diverse populations. The tests were planted on 23 field sites in six European countries, in order to expose them to a wide range of climates, including sites reflecting future warmer and drier climates. By assessing tree height and survival, our objectives were twofold: (i) to identify the source of differential population responses to climate (genetic differentiation due to past divergent climatic selection vs. plastic responses to ongoing climate change) and (ii) to explore which climatic variables (temperature or precipitation) trigger the population responses. Tree growth and survival were modeled for contemporary climate and then projected using data from four regional climate models for years 2071-2100, using two greenhouse gas concentration trajectory scenarios each. Overall, results indicated a moderate response of tree height and survival to climate variation, with changes in dryness (either annual or during the growing season) explaining the major part of the response. While, on average, populations exhibited local adaptation, there was significant clinal population differentiation for height growth with winter temperature at the site of origin. The most moderate climate model (HIRHAM5-EC; rcp4.5) predicted minor decreases in height and survival, while the most extreme model (CCLM4-GEM2-ES; rcp8.5) predicted large decreases in survival and growth for southern and southeastern edge populations (Hungary and Turkey). Other nonmarginal populations with continental climates were predicted to be severely and negatively affected (Bercé, France), while populations at the contemporary northern limit (colder and humid maritime regions; Denmark and Norway) will probably not show large changes in growth and survival in response to climate change. © 2017 John Wiley & Sons Ltd.

Patient Similarity in Prediction Models Based on Health Data: A Scoping Review

PubMed Central

Sharafoddini, Anis; Dubin, Joel A

2017-01-01

Background Physicians and health policy makers are required to make predictions during their decision making in various medical problems. Many advances have been made in predictive modeling toward outcome prediction, but these innovations target an average patient and are insufficiently adjustable for individual patients. One developing idea in this field is individualized predictive analytics based on patient similarity. The goal of this approach is to identify patients who are similar to an index patient and derive insights from the records of similar patients to provide personalized predictions.. Objective The aim is to summarize and review published studies describing computer-based approaches for predicting patients’ future health status based on health data and patient similarity, identify gaps, and provide a starting point for related future research. Methods The method involved (1) conducting the review by performing automated searches in Scopus, PubMed, and ISI Web of Science, selecting relevant studies by first screening titles and abstracts then analyzing full-texts, and (2) documenting by extracting publication details and information on context, predictors, missing data, modeling algorithm, outcome, and evaluation methods into a matrix table, synthesizing data, and reporting results. Results After duplicate removal, 1339 articles were screened in abstracts and titles and 67 were selected for full-text review. In total, 22 articles met the inclusion criteria. Within included articles, hospitals were the main source of data (n=10). Cardiovascular disease (n=7) and diabetes (n=4) were the dominant patient diseases. Most studies (n=18) used neighborhood-based approaches in devising prediction models. Two studies showed that patient similarity-based modeling outperformed population-based predictive methods. Conclusions Interest in patient similarity-based predictive modeling for diagnosis and prognosis has been growing. In addition to raw/coded health data, wavelet transform and term frequency-inverse document frequency methods were employed to extract predictors. Selecting predictors with potential to highlight special cases and defining new patient similarity metrics were among the gaps identified in the existing literature that provide starting points for future work. Patient status prediction models based on patient similarity and health data offer exciting potential for personalizing and ultimately improving health care, leading to better patient outcomes. PMID:28258046

The potential effect of population development, smoking and antioxidant supplementation on the future epidemiology of age-related macular degeneration in Switzerland.

PubMed

Bauer, P; Barthelmes, D; Kurz, M; Fleischhauer, J C; Sutter, F K

2008-05-01

Due to the predicted age shift of the population an increase in the number of patients with late AMD is expected. At present smoking represents the only modifiable risk factor. Supplementation of antioxidants in patients at risk is the sole effective pharmacological prevention. The aim of this study is to estimate the future epidemiological development of late AMD in Switzerland and to quantify the potential effects of smoking and antioxidants supplementation. The modelling of the future development of late AMD cases in Switzerland was based on a meta-analysis of the published data on AMD-prevalence and on published Swiss population development scenarios until 2050. Three different scenarios were compared: low, mean and high. The late AMD cases caused by smoking were calculated using the "population attributable fraction" formula and data on the current smoking habits of the Swiss population. The number of potentially preventable cases was estimated using the data of the Age-Related Eye Disease Study (AREDS). According to the mean population development scenario, late AMD cases in Switzerland will rise from 37 200 cases in 2005 to 52 500 cases in 2020 and to 93 200 cases in 2050. Using the "low" and the "high" scenarios the late AMD cases may range from 49 500 to 56 000 in 2020 and from 73 700 to 118 400 in 2050, respectively. Smoking is responsible for approximately 7 % of all late AMD cases, i. e., 2600 cases in 2005, 3800 cases in 2020, 6600 cases in 2050 ("mean scenario"). With future antioxidant supplementation to all patients at risk another 3100 cases would be preventable until 2020 and possibly 23 500 cases until 2050. Due to age shift in the population a 2.5-fold increase in late AMD cases until 2050 is expected, representing a socioeconomic challenge. Cessation of smoking and supplementation of antioxidants to all patients at risk has the potential to reduce this number. Unfortunately, public awareness is low. These data may support health-care providers and public opinion leaders when developing public education and prevention strategies.

Tracking climate change in a dispersal-limited species: reduced spatial and genetic connectivity in a montane salamander.

PubMed

Velo-Antón, G; Parra, J L; Parra-Olea, G; Zamudio, K R

2013-06-01

Tropical montane taxa are often locally adapted to very specific climatic conditions, contributing to their lower dispersal potential across complex landscapes. Climate and landscape features in montane regions affect population genetic structure in predictable ways, yet few empirical studies quantify the effects of both factors in shaping genetic structure of montane-adapted taxa. Here, we considered temporal and spatial variability in climate to explain contemporary genetic differentiation between populations of the montane salamander, Pseudoeurycea leprosa. Specifically, we used ecological niche modelling (ENM) and measured spatial connectivity and gene flow (using both mtDNA and microsatellite markers) across extant populations of P. leprosa in the Trans-Mexican Volcanic Belt (TVB). Our results indicate significant spatial and genetic isolation among populations, but we cannot distinguish between isolation by distance over time or current landscape barriers as mechanisms shaping population genetic divergences. Combining ecological niche modelling, spatial connectivity analyses, and historical and contemporary genetic signatures from different classes of genetic markers allows for inference of historical evolutionary processes and predictions of the impacts future climate change will have on the genetic diversity of montane taxa with low dispersal rates. Pseudoeurycea leprosa is one montane species among many endemic to this region and thus is a case study for the continued persistence of spatially and genetically isolated populations in the highly biodiverse TVB of central Mexico. © 2013 John Wiley & Sons Ltd.

Experimental evidence that density dependence strongly influences plant invasions through fragmented landscapes.

PubMed

Williams, Jennifer L; Levine, Jonathan M

2018-04-01

Populations of range expanding species encounter patches of both favorable and unfavorable habitat as they spread across landscapes. Theory shows that increasing patchiness slows the spread of populations modeled with continuously varying population density when dispersal is not influence by the environment or individual behavior. However, as is found in uniformly favorable landscapes, spread remains driven by fecundity and dispersal from low density individuals at the invasion front. In contrast, when modeled populations are composed of discrete individuals, patchiness causes populations to build up to high density before dispersing past unsuitable habitat, introducing an important influence of density dependence on spread velocity. To test the hypothesized interaction between habitat patchiness and density dependence, we simultaneously manipulated these factors in a greenhouse system of annual plants spreading through replicated experimental landscapes. We found that increasing the size of gaps and amplifying the strength of density dependence both slowed spread velocity, but contrary to predictions, the effect of amplified density dependence was similar across all landscape types. Our results demonstrate that the discrete nature of individuals in spreading populations has a strong influence on how both landscape patchiness and density dependence influence spread through demographic and dispersal stochasticity. Both finiteness and landscape structure should be critical components to theoretical predictions of future spread for range expanding native species or invasive species colonizing new habitat. © 2018 by the Ecological Society of America.

Modelling of land use change in Indramayu District, West Java Province

NASA Astrophysics Data System (ADS)

Handayani, L. D. W.; Tejaningrum, M. A.; Damrah, F.

2017-01-01

Indramayu District into a strategic area for a stopover and overseas from East Java area because Indramayu District passed the north coast main lane, which is the first as the economic lifeblood of the Java Island. Indramayu District is part of mainstream economic Java pathways so that physical development of the area and population density as well as community activities grew by leaps and bounds. Growth acceleration raised the level of land use change. Land use change and population activities in coastal area would reduce the carrying capacity and impact on environmental quality. This research aim to analyse landuse change of years 2000 and 2011 in Indramayu District. Using this land use change map, we can predict the condition of landuse change of year 2022 in Indramayu District. Cellular Automata Markov (Markov CA) Method is used to create a spatial model of land use changes. The results of this study are predictive of land use in 2022 and the suitability with Spatial Plan (RTRW). A settlement increase predicted to continue in the future the designation of the land according to the spatial plan should be maintained.

Predicting population survival under future climate change: density dependence, drought and extraction in an insular bighorn sheep.

PubMed

Colchero, Fernando; Medellin, Rodrigo A; Clark, James S; Lee, Raymond; Katul, Gabriel G

2009-05-01

1. Our understanding of the interplay between density dependence, climatic perturbations, and conservation practices on the dynamics of small populations is still limited. This can result in uninformed strategies that put endangered populations at risk. Moreover, the data available for a large number of populations in such circumstances are sparse and mined with missing data. Under the current climate change scenarios, it is essential to develop appropriate inferential methods that can make use of such data sets. 2. We studied a population of desert bighorn sheep introduced to Tiburon Island, Mexico in 1975 and subjected to irregular extractions for the last 10 years. The unique attributes of this population are absence of predation and disease, thereby permitting us to explore the combined effect of density dependence, environmental variability and extraction in a 'controlled setting.' Using a combination of nonlinear discrete models with long-term field data, we constructed three basic Bayesian state space models with increasing density dependence (DD), and the same three models with the addition of summer drought effects. 3. We subsequently used Monte Carlo simulations to evaluate the combined effect of drought, DD, and increasing extractions on the probability of population survival under two climate change scenarios (based on the Intergovernmental Panel on Climate Change predictions): (i) increase in drought variability; and (ii) increase in mean drought severity. 4. The population grew from 16 individuals introduced in 1975 to close to 700 by 1993. Our results show that the population's growth was dominated by DD, with drought having a secondary but still relevant effect on its dynamics. 5. Our predictions suggest that under climate change scenario (i), extraction dominates the fate of the population, while for scenario (ii), an increase in mean drought affects the population's probability of survival in an equivalent magnitude as extractions. Thus, for the long-term survival of the population, our results stress that a more variable environment is less threatening than one in which the mean conditions become harsher. Current climate change scenarios and their underlying uncertainty make studies such as this one crucial for understanding the dynamics of ungulate populations and their conservation.

Predicting the Timing of Maturational Spurts in Skeletal Age

PubMed Central

Nahhas, Ramzi W.; Sherwood, Richard J.; Chumlea, Wm. Cameron; Towne, Bradford; Duren, Dana L.

2014-01-01

Measures of maturity provide windows into the timing and tempo of childhood growth and maturation. Delayed maturation in a single child, or systemically in a population, can result from either genetic or environmental factors. In terms of the skeleton, delayed maturation may result in short stature or indicate another underlying issue. Thus, prediction of the timing of a maturational spurt is often desirable in order to determine the likelihood that a child will catch up to their chronological age peers. Serial data from the Fels Longitudinal Study were used to predict future skeletal age conditional on current skeletal age and to predict the timing of maturational spurts. For children who were delayed relative to their chronological age peers, the like-lihood of catch-up maturation increased through the average age of onset of puberty and decreased prior to the average age of peak height velocity. For boys, the probability of an imminent maturational spurt was higher for those who were less mature. For girls aged 11 to 13 years, however, this probability was higher for those who were more mature, potentially indicating the presence of a skeletal maturation plateau between multiple spurts. The prediction model, available on the web, is most relevant to children of European ancestry living in the Midwestern US. Our model may also provide insight into the tempo of maturation for children in other populations, but must be applied with caution if those populations are known to have high burdens of environmental stressors not typical of the Midwestern US. Am J Phys Anthropol 150:68–75, 2013. PMID:23283666

Population dynamics can be more important than physiological limits for determining range shifts under climate change.

PubMed

Fordham, Damien A; Mellin, Camille; Russell, Bayden D; Akçakaya, Reşit H; Bradshaw, Corey J A; Aiello-Lammens, Matthew E; Caley, Julian M; Connell, Sean D; Mayfield, Stephen; Shepherd, Scoresby A; Brook, Barry W

2013-10-01

Evidence is accumulating that species' responses to climate changes are best predicted by modelling the interaction of physiological limits, biotic processes and the effects of dispersal-limitation. Using commercially harvested blacklip (Haliotis rubra) and greenlip abalone (Haliotis laevigata) as case studies, we determine the relative importance of accounting for interactions among physiology, metapopulation dynamics and exploitation in predictions of range (geographical occupancy) and abundance (spatially explicit density) under various climate change scenarios. Traditional correlative ecological niche models (ENM) predict that climate change will benefit the commercial exploitation of abalone by promoting increased abundances without any reduction in range size. However, models that account simultaneously for demographic processes and physiological responses to climate-related factors result in future (and present) estimates of area of occupancy (AOO) and abundance that differ from those generated by ENMs alone. Range expansion and population growth are unlikely for blacklip abalone because of important interactions between climate-dependent mortality and metapopulation processes; in contrast, greenlip abalone should increase in abundance despite a contraction in AOO. The strongly non-linear relationship between abalone population size and AOO has important ramifications for the use of ENM predictions that rely on metrics describing change in habitat area as proxies for extinction risk. These results show that predicting species' responses to climate change often require physiological information to understand climatic range determinants, and a metapopulation model that can make full use of this data to more realistically account for processes such as local extirpation, demographic rescue, source-sink dynamics and dispersal-limitation. © 2013 John Wiley & Sons Ltd.

Distress or no distress, that's the question: A cutoff point for distress in a working population

PubMed Central

van Rhenen, Willem; van Dijk, Frank JH; Schaufeli, Wilmar B; Blonk, Roland WB

2008-01-01

Background The objective of the present study is to establish an optimal cutoff point for distress measured with the corresponding scale of the 4DSQ, using the prediction of sickness absence as a criterion. The cutoff point should result in a measure that can be used as a credible selection instrument for sickness absence in occupational health practice and in future studies on distress and mental disorders. Methods Distress is measured using the Four Dimensional Symptom Questionnaire (4DSQ), a 50-item self-report questionnaire, in a working population with and without sickness absence due to distress. Sensitivity and specificity were compared for various potential cutoff points, and a receiver operating characteristics analysis was conducted. Results and conclusion A distress cutoff point of ≥11 was defined. The choice was based on a challenging specificity and negative predictive value and indicates a distress level at which an employee is presumably at risk for subsequent sick leave on psychological grounds. The defined distress cutoff point is appropriate for use in occupational health practice and in studies of distress in working populations. PMID:18205912

Distress or no distress, that's the question: A cutoff point for distress in a working population.

PubMed

van Rhenen, Willem; van Dijk, Frank Jh; Schaufeli, Wilmar B; Blonk, Roland Wb

2008-01-18

The objective of the present study is to establish an optimal cutoff point for distress measured with the corresponding scale of the 4DSQ, using the prediction of sickness absence as a criterion. The cutoff point should result in a measure that can be used as a credible selection instrument for sickness absence in occupational health practice and in future studies on distress and mental disorders. Distress is measured using the Four Dimensional Symptom Questionnaire (4DSQ), a 50-item self-report questionnaire, in a working population with and without sickness absence due to distress. Sensitivity and specificity were compared for various potential cutoff points, and a receiver operating characteristics analysis was conducted. A distress cutoff point of >/=11 was defined. The choice was based on a challenging specificity and negative predictive value and indicates a distress level at which an employee is presumably at risk for subsequent sick leave on psychological grounds. The defined distress cutoff point is appropriate for use in occupational health practice and in studies of distress in working populations.

Summarising and validating test accuracy results across multiple studies for use in clinical practice.

PubMed

Riley, Richard D; Ahmed, Ikhlaaq; Debray, Thomas P A; Willis, Brian H; Noordzij, J Pieter; Higgins, Julian P T; Deeks, Jonathan J

2015-06-15

Following a meta-analysis of test accuracy studies, the translation of summary results into clinical practice is potentially problematic. The sensitivity, specificity and positive (PPV) and negative (NPV) predictive values of a test may differ substantially from the average meta-analysis findings, because of heterogeneity. Clinicians thus need more guidance: given the meta-analysis, is a test likely to be useful in new populations, and if so, how should test results inform the probability of existing disease (for a diagnostic test) or future adverse outcome (for a prognostic test)? We propose ways to address this. Firstly, following a meta-analysis, we suggest deriving prediction intervals and probability statements about the potential accuracy of a test in a new population. Secondly, we suggest strategies on how clinicians should derive post-test probabilities (PPV and NPV) in a new population based on existing meta-analysis results and propose a cross-validation approach for examining and comparing their calibration performance. Application is made to two clinical examples. In the first example, the joint probability that both sensitivity and specificity will be >80% in a new population is just 0.19, because of a low sensitivity. However, the summary PPV of 0.97 is high and calibrates well in new populations, with a probability of 0.78 that the true PPV will be at least 0.95. In the second example, post-test probabilities calibrate better when tailored to the prevalence in the new population, with cross-validation revealing a probability of 0.97 that the observed NPV will be within 10% of the predicted NPV. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

The many faces of precision (Replies to commentaries on “Whatever next? Neural prediction, situated agents, and the future of cognitive science”)

PubMed Central

Clark, Andy

2013-01-01

An appreciation of the many roles of “precision-weighting” (upping the gain on select populations of prediction error units) opens the door to better accounts of planning and “offline simulation,” makes suggestive contact with large bodies of work on embodied and situated cognition, and offers new perspectives on the “active brain”. Combined with the complex affordances of language and culture, and operating against the essential backdrop of a variety of more biologically basic ploys and stratagems, the result is a maximally context-sensitive, restless, constantly self-reconfiguring architecture. PMID:23734133

Time Frame and Justice Motive: Future Perspective Moderates the Adaptive Function of General Belief in a Just World

PubMed Central

Wu, Michael Shengtao; Sutton, Robbie M.; Yan, Xiaodan; Zhou, Chan; Chen, Yiwen; Zhu, Zhuohong; Han, Buxin

2013-01-01

Background The human ability to envision the future, that is, to take a future perspective (FP), plays a key role in the justice motive and its function in transcending disadvantages and misfortunes. The present research investigated whether individual (Study 1) and situational (Study 2) differences in FP moderated the association of general belief in a just world (GBJW) with psychological resilience. Methodology/Principal Findings We investigated FP, GBJW, and resilience in sample of adolescents (n = 223) and disaster survivors (n = 218) in China. In Study 1, adolescents revealed stronger GBJW than PBJW, and GBJW uniquely predicted resilience in the daily lives of those with high FP (but not those with low FP). In Study 2, natural priming of FP (vs. no FP) facilitated the association of GBJW with resilience after disaster. Conclusions/Significance Supporting predictions, participants endorsed GBJW more strongly than PBJW. Further, GBJW interacted with FP in both studies, such that there was an association between GBJW and resilience at high but not low levels of FP. The results corroborate recent findings suggesting that GBJW may be more psychologically adaptive than PBJW among some populations. They also confirm that focusing on the future is an important aspect of the adaptive function of just-world beliefs. PMID:24312235

Water Resource Assessment in KRS Reservoir Using Remote Sensing and GIS Modelling

NASA Astrophysics Data System (ADS)

Manubabu, V. H.; Gouda, K. C.; Bhat, N.; Reddy, A.

2014-12-01

In the recent time the fresh water resource becomes very important because of various reasons like population growth, pollution, over exploitation of the ground water resources etc. As there is no efficient and proper measures for recharging ground water exists and also the climatological impacts on water resources like global warming exacerbating water shortages, growing populations and rising demand for freshwater in agriculture, industry, and energy production. There is a need and challenging task for analyzing the future changes in regional water availability and it is also very much necessary to asses and predict the fresh water present in a lake or reservoir to make better decision making in the optimal usage of surface water. In the present study is intended to provide a practical discussion of methodology that deals with how to asses and predict amount of surface water available in the future using Remote Sensing(RS) data , Geographical Information System(GIS) techniques, and GCM (Global Circulation Model). Basically the study emphasized over one of the biggest reservoir i.e. the Krishna Raja Sagara (KRS) reservoir situated in the state of Karnataka in India. Multispectral satellite images like IRS LISS III and Landsat L8 from different open source web portals like NRSC-Bhuvan and NASA Earth Explorer respectively are used for the present analysis. The multispectral satellite images are used to identify the temporal changes of the water quantity in the reservoir for the period 2000 to 2014. Also the water volume are being calculated using Advances Space born Thermal Emission and Reflection Radiometer (ASTER) Global DEM over the reservoir basin. The hydro meteorological parameters are also studied using multi-source observed data and the empirical water budget models for the reservoir in terms of rainfall, temperature, run off, water inflow and outflow etc. are being developed and analyzed. Statistical analysis are also carried out to quantify the relation between reservoir water volume and the hydrological parameters (Figure 1). A general circulation model (GCM) is used for the prediction of major hydro meteorological parameters like rainfall and using the GCM predictions the water availability in terms of water volume in future are simulated using the empirical water budget model.

Religiosity and Risky Sexual Behaviors among an African American Church-based Population

PubMed Central

Hawes, Starlyn M.; Berkley-Patton, Jannette Y.

2014-01-01

African Americans are disproportionately burdened by STDs and HIV in the US. This study examined the relationships between demographics, religiosity, and sexual risk behaviors among 255 adult African American church-based participants. Although participants were highly religious, they reported an average of seven lifetime sex partners and most inconsistently used condoms. Several demographic variables and religiosity significantly predicted lifetime HIV-related risk factors. Taken together, findings indicated that this population is at risk for HIV. Future research should continue to identify correlates of risky sexual behavior among African American parishioners to facilitate the development of HIV risk reduction interventions in their church settings. PMID:23054481

Quantifying the past and future impact of climate on outbreak patterns of bank voles (Myodes glareolus).

PubMed

Imholt, Christian; Reil, Daniela; Eccard, Jana A; Jacob, Daniela; Hempelmann, Nils; Jacob, Jens

2015-02-01

Central European outbreak populations of the bank vole (Myodes glareolus Schreber) are known to cause damage in forestry and to transmit the most common type of Hantavirus (Puumala virus, PUUV) to humans. A sound estimation of potential effects of future climate scenarios on population dynamics is a prerequisite for long-term management strategies. Historic abundance time series were used to identify the key weather conditions associated with bank vole abundance, and were extrapolated to future climate scenarios to derive potential long-term changes in bank vole abundance dynamics. Classification and regression tree analysis revealed the most relevant weather parameters associated with high and low bank vole abundances. Summer temperatures 2 years prior to trapping had the highest impact on abundance fluctuation. Extrapolation of the identified parameters to future climate conditions revealed an increase in years with high vole abundance. Key weather patterns associated with vole abundance reflect the importance of superabundant food supply through masting to the occurrence of bank vole outbreaks. Owing to changing climate, these outbreaks are predicted potentially to increase in frequency 3-4-fold by the end of this century. This may negatively affect damage patterns in forestry and the risk of human PUUV infection in the long term. © 2014 Society of Chemical Industry.

Indexing sensory plasticity: Evidence for distinct Predictive Coding and Hebbian learning mechanisms in the cerebral cortex.

PubMed

Spriggs, M J; Sumner, R L; McMillan, R L; Moran, R J; Kirk, I J; Muthukumaraswamy, S D

2018-04-30

The Roving Mismatch Negativity (MMN), and Visual LTP paradigms are widely used as independent measures of sensory plasticity. However, the paradigms are built upon fundamentally different (and seemingly opposing) models of perceptual learning; namely, Predictive Coding (MMN) and Hebbian plasticity (LTP). The aim of the current study was to compare the generative mechanisms of the MMN and visual LTP, therefore assessing whether Predictive Coding and Hebbian mechanisms co-occur in the brain. Forty participants were presented with both paradigms during EEG recording. Consistent with Predictive Coding and Hebbian predictions, Dynamic Causal Modelling revealed that the generation of the MMN modulates forward and backward connections in the underlying network, while visual LTP only modulates forward connections. These results suggest that both Predictive Coding and Hebbian mechanisms are utilized by the brain under different task demands. This therefore indicates that both tasks provide unique insight into plasticity mechanisms, which has important implications for future studies of aberrant plasticity in clinical populations. Copyright © 2018 Elsevier Inc. All rights reserved.

Model-based prediction of nephropathia epidemica outbreaks based on climatological and vegetation data and bank vole population dynamics.

PubMed

Haredasht, S Amirpour; Taylor, C J; Maes, P; Verstraeten, W W; Clement, J; Barrios, M; Lagrou, K; Van Ranst, M; Coppin, P; Berckmans, D; Aerts, J-M

2013-11-01

Wildlife-originated zoonotic diseases in general are a major contributor to emerging infectious diseases. Hantaviruses more specifically cause thousands of human disease cases annually worldwide, while understanding and predicting human hantavirus epidemics pose numerous unsolved challenges. Nephropathia epidemica (NE) is a human infection caused by Puumala virus, which is naturally carried and shed by bank voles (Myodes glareolus). The objective of this study was to develop a method that allows model-based predicting 3 months ahead of the occurrence of NE epidemics. Two data sets were utilized to develop and test the models. These data sets were concerned with NE cases in Finland and Belgium. In this study, we selected the most relevant inputs from all the available data for use in a dynamic linear regression (DLR) model. The number of NE cases in Finland were modelled using data from 1996 to 2008. The NE cases were predicted based on the time series data of average monthly air temperature (°C) and bank voles' trapping index using a DLR model. The bank voles' trapping index data were interpolated using a related dynamic harmonic regression model (DHR). Here, the DLR and DHR models used time-varying parameters. Both the DHR and DLR models were based on a unified state-space estimation framework. For the Belgium case, no time series of the bank voles' population dynamics were available. Several studies, however, have suggested that the population of bank voles is related to the variation in seed production of beech and oak trees in Northern Europe. Therefore, the NE occurrence pattern in Belgium was predicted based on a DLR model by using remotely sensed phenology parameters of broad-leaved forests, together with the oak and beech seed categories and average monthly air temperature (°C) using data from 2001 to 2009. Our results suggest that even without any knowledge about hantavirus dynamics in the host population, the time variation in NE outbreaks in Finland could be predicted 3 months ahead with a 34% mean relative prediction error (MRPE). This took into account solely the population dynamics of the carrier species (bank voles). The time series analysis also revealed that climate change, as represented by the vegetation index, changes in forest phenology derived from satellite images and directly measured air temperature, may affect the mechanics of NE transmission. NE outbreaks in Belgium were predicted 3 months ahead with a 40% MRPE, based only on the climatological and vegetation data, in this case, without any knowledge of the bank vole's population dynamics. In this research, we demonstrated that NE outbreaks can be predicted using climate and vegetation data or the bank vole's population dynamics, by using dynamic data-based models with time-varying parameters. Such a predictive modelling approach might be used as a step towards the development of new tools for the prevention of future NE outbreaks. © 2012 Blackwell Verlag GmbH.

A Framework Predicting Water Availability in a Rapidly Growing, Semi-Arid Region under Future Climate Change

NASA Astrophysics Data System (ADS)

Han, B.; Benner, S. G.; Glenn, N. F.; Lindquist, E.; Dahal, K. R.; Bolte, J.; Vache, K. B.; Flores, A. N.

2014-12-01

Climate change can lead to dramatic variations in hydrologic regime, affecting both surface water and groundwater supply. This effect is most significant in populated semi-arid regions where water availability are highly sensitive to climate-induced outcomes. However, predicting water availability at regional scales, while resolving some of the key internal variability and structure in semi-arid regions is difficult due to the highly non-linearity relationship between rainfall and runoff. In this study, we describe the development of a modeling framework to evaluate future water availability that captures elements of the coupled response of the biophysical system to climate change and human systems. The framework is built under the Envision multi-agent simulation tool, characterizing the spatial patterns of water demand in the semi-arid Treasure Valley area of Southwest Idaho - a rapidly developing socio-ecological system where urban growth is displacing agricultural production. The semi-conceptual HBV model, a population growth and allocation model (Target), a vegetation state and transition model (SSTM), and a statistically based fire disturbance model (SpatialAllocator) are integrated to simulate hydrology, population and land use. Six alternative scenarios are composed by combining two climate change scenarios (RCP4.5 and RCP8.5) with three population growth and allocation scenarios (Status Quo, Managed Growth, and Unconstrained Growth). Five-year calibration and validation performances are assessed with Nash-Sutcliffe efficiency. Irrigation activities are simulated using local water rights. Results show that in all scenarios, annual mean stream flow decreases as the projected rainfall increases because the projected warmer climate also enhances water losses to evapotranspiration. Seasonal maximum stream flow tends to occur earlier than in current conditions due to the earlier peak of snow melting. The aridity index and water deficit generally increase in the irrigated area. The most sensitive area is along the Boise Foothill which is the transitioning zone from water deficit to water abundant. However, these trends vary significantly between scenarios in space and time. The outcome of the study will serve as a reference for local stakeholders to make decisions on future land use.

Comparison of Intrinsic Rate of Different House Fly Densities in a Simulated Condition: A Prediction for House Fly Population and Control Threshold.

PubMed

Ong, Song-Quan; Ahmad, Hamdan; Jaal, Zairi; Rus, Adanan; Fadzlah, Fadhlina Hazwani Mohd

2017-01-01

Determining the control threshold for a pest is common prior to initiating a pest control program; however, previous studies related to the house fly control threshold for a poultry farm are insufficient for determining such a threshold. This study aimed to predict the population changes of house fly population by comparing the intrinsic rate of increase (r m ) for different house fly densities in a simulated system. This study first defined the knee points of a known population growth curve as a control threshold by comparing the r m of five densities of house flies in a simulated condition. Later, to understand the interactions between the larval and adult populations, the correlation between larval and adult capacity rate (r c ) was studied. The r m values of 300- and 500-fly densities were significantly higher compared with the r m values at densities of 50 and 100 flies. This result indicated their representative indices as candidates for a control threshold. The r c of larval and adult populations were negatively correlated with densities of fewer than 300 flies; this implicated adult populations with fewer than 300 flies as declining while the larval population was growing; therefore, control approaches should focus on the immature stages. The results in the present study suggest a control threshold for house fly populations. Future works should focus on calibrating the threshold indices in field conditions. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Multilevel landscape utilization of the Siberian flying squirrel: Scale effects on species habitat use.

PubMed

Remm, Jaanus; Hanski, Ilpo K; Tuominen, Sakari; Selonen, Vesa

2017-10-01

Animals use and select habitat at multiple hierarchical levels and at different spatial scales within each level. Still, there is little knowledge on the scale effects at different spatial levels of species occupancy patterns. The objective of this study was to examine nonlinear effects and optimal-scale landscape characteristics that affect occupancy of the Siberian flying squirrel, Pteromys volans , in South- and Mid-Finland. We used presence-absence data ( n  = 10,032 plots of 9 ha) and novel approach to separate the effects on site-, landscape-, and regional-level occupancy patterns. Our main results were: landscape variables predicted the placement of population patches at least twice as well as they predicted the occupancy of particular sites; the clear optimal value of preferred habitat cover for species landscape-level abundance is a surprisingly low value (10% within a 4 km buffer); landscape metrics exert different effects on species occupancy and abundance in high versus low population density regions of our study area. We conclude that knowledge of regional variation in landscape utilization will be essential for successful conservation of the species. The results also support the view that large-scale landscape variables have high predictive power in explaining species abundance. Our study demonstrates the complex response of species occurrence at different levels of population configuration on landscape structure. The study also highlights the need for data in large spatial scale to increase the precision of biodiversity mapping and prediction of future trends.

What predictors matter: Risk factors for late adolescent outcomes.

PubMed

Wall-Wieler, Elizabeth; Roos, Leslie L; Chateau, Dan G; Rosella, Laura C

2016-06-27

A life course approach and linked Manitoba data from birth to age 18 were used to facilitate comparisons of two important outcomes: high school graduation and Attention-Deficit/Hyperactivity Disorder (ADHD). With a common set of variables, we sought to answer the following questions: Do the measures predicting high school graduation differ from those that predict ADHD? Which factors are most important? How well do the models fit each outcome? Administrative data from the Population Health Research Data Repository at the Manitoba Centre for Health Policy were used to conduct one of the strongest observational designs: multilevel modelling of large population (n = 62,739) and sibling (n = 29,444) samples. Variables included are neighbourhood characteristics, measures of family stability, and mental and physical health conditions in childhood and adolescence. The adverse childhood experiences important for each outcome differ. While family instability and economic adversity more strongly affect failing to graduate from high school, adverse health events in childhood and early adolescence have a greater effect on late adolescent ADHD. The variables included in the model provided excellent accuracy and discrimination. These results offer insights on the role of several family and social variables and can serve as the basis for reliable, valid prediction tools that can identify high-risk individuals. Applying such a tool at the population level would provide insight into the future burden of these outcomes in an entire region or nation and further quantify the burden of risk in the population.

Assessment of climate change impact on water diversion strategies of Melamchi Water Supply Project in Nepal

NASA Astrophysics Data System (ADS)

Shrestha, Sangam; Shrestha, Manish; Babel, Mukand S.

2017-04-01

This paper analyzes the climate change impact on water diversion plan of Melamchi Water Supply Project (MWSP) in Nepal. The MWSP is an interbasin water transfer project aimed at diverting water from the Melamchi River of the Indrawati River basin to Kathmandu Valley for drinking water purpose. Future temperature and precipitation of the basin were predicted using the outputs of two regional climate models (RCMs) and two general circulation models (GCMs) under two representative concentration pathway (RCP) scenarios which were then used as inputs to Soil and Water Assessment Tool (SWAT) to predict the water availability and evaluate the water diversion strategies in the future. The average temperature of the basin is projected to increase by 2.35 to 4.25 °C under RCP 4.5 and RCP 8.5, respectively, by 2085s. The average precipitation in the basin is projected to increase by 6-18 % in the future. The annual water availability is projected to increase in the future; however, the variability is observed in monthly water availability in the basin. The water supply and demand scenarios of Kathmandu Valley was also examined by considering the population increase, unaccounted for water and water diversion from MWSP in the future. It is observed that even with the additional supply of water from MWSP and reduction of unaccounted for water, the Kathmandu Valley will be still under water scarcity in the future. The findings of this study can be helpful to formulate water supply and demand management strategies in Kathmandu Valley in the context of climate change in the future.

Climate change likely to reduce orchid bee abundance even in climatic suitable sites.

PubMed

Faleiro, Frederico Valtuille; Nemésio, André; Loyola, Rafael

2018-06-01

Studies have tested whether model predictions based on species' occurrence can predict the spatial pattern of population abundance. The relationship between predicted environmental suitability and population abundance varies in shape, strength and predictive power. However, little attention has been paid to the congruence in predictions of different models fed with occurrence or abundance data, in particular when comparing metrics of climate change impact. Here, we used the ecological niche modeling fit with presence-absence and abundance data of orchid bees to predict the effect of climate change on species and assembly level distribution patterns. In addition, we assessed whether predictions of presence-absence models can be used as a proxy to abundance patterns. We obtained georeferenced abundance data of orchid bees (Hymenoptera: Apidae: Euglossina) in the Brazilian Atlantic Forest. Sampling method consisted in attracting male orchid bees to baits of at least five different aromatic compounds and collecting the individuals with entomological nets or bait traps. We limited abundance data to those obtained by similar standard sampling protocol to avoid bias in abundance estimation. We used boosted regression trees to model ecological niches and project them into six climate models and two Representative Concentration Pathways. We found that models based on species occurrences worked as a proxy for changes in population abundance when the output of the models were continuous; results were very different when outputs were discretized to binary predictions. We found an overall trend of diminishing abundance in the future, but a clear retention of climatically suitable sites too. Furthermore, geographic distance to gained climatic suitable areas can be very short, although it embraces great variation. Changes in species richness and turnover would be concentrated in western and southern Atlantic Forest. Our findings offer support to the ongoing debate of suitability-abundance models and can be used to support spatial conservation prioritization schemes and species triage in Atlantic Forest. © 2018 John Wiley & Sons Ltd.

Addressing potential local adaptation in species distribution models: implications for conservation under climate change

USGS Publications Warehouse

Hällfors, Maria Helena; Liao, Jishan; Dzurisin, Jason D. K.; Grundel, Ralph; Hyvärinen, Marko; Towle, Kevin; Wu, Grace C.; Hellmann, Jessica J.

2016-01-01

Species distribution models (SDMs) have been criticized for involving assumptions that ignore or categorize many ecologically relevant factors such as dispersal ability and biotic interactions. Another potential source of model error is the assumption that species are ecologically uniform in their climatic tolerances across their range. Typically, SDMs to treat a species as a single entity, although populations of many species differ due to local adaptation or other genetic differentiation. Not taking local adaptation into account, may lead to incorrect range prediction and therefore misplaced conservation efforts. A constraint is that we often do not know the degree to which populations are locally adapted, however. Lacking experimental evidence, we still can evaluate niche differentiation within a species' range to promote better conservation decisions. We explore possible conservation implications of making type I or type II errors in this context. For each of two species, we construct three separate MaxEnt models, one considering the species as a single population and two of disjunct populations. PCA analyses and response curves indicate different climate characteristics in the current environments of the populations. Model projections into future climates indicate minimal overlap between areas predicted to be climatically suitable by the whole species versus population-based models. We present a workflow for addressing uncertainty surrounding local adaptation in SDM application and illustrate the value of conducting population-based models to compare with whole-species models. These comparisons might result in more cautious management actions when alternative range outcomes are considered.

In ecoregions across western USA streamflow increases during post-wildfire recovery

NASA Astrophysics Data System (ADS)

Wine, Michael L.; Cadol, Daniel; Makhnin, Oleg

2018-01-01

Continued growth of the human population on Earth will increase pressure on already stressed terrestrial water resources required for drinking water, agriculture, and industry. This stress demands improved understanding of critical controls on water resource availability, particularly in water-limited regions. Mechanistic predictions of future water resource availability are needed because non-stationary conditions exist in the form of changing climatic conditions, land management paradigms, and ecological disturbance regimes. While historically ecological disturbances have been small and could be neglected relative to climatic effects, evidence is accumulating that ecological disturbances, particularly wildfire, can increase regional water availability. However, wildfire hydrologic impacts are typically estimated locally and at small spatial scales, via disparate measurement methods and analysis techniques, and outside the context of climate change projections. Consequently, the relative importance of climate change driven versus wildfire driven impacts on streamflow remains unknown across the western USA. Here we show that considering wildfire in modeling streamflow significantly improves model predictions. Mixed effects modeling attributed 2%-14% of long-term annual streamflow to wildfire effects. The importance of this wildfire-linked streamflow relative to predicted climate change-induced streamflow reductions ranged from 20%-370% of the streamflow decrease predicted to occur by 2050. The rate of post-wildfire vegetation recovery and the proportion of watershed area burned controlled the wildfire effect. Our results demonstrate that in large areas of the western USA affected by wildfire, regional predictions of future water availability are subject to greater structural uncertainty than previously thought. These results suggest that future streamflows may be underestimated in areas affected by increased prevalence of hydrologically relevant ecological disturbances such as wildfire.

Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (Myocastor coypus)

USGS Publications Warehouse

Jarnevich, Catherine S.; Young, Nicholas E; Sheffels, Trevor R.; Carter, Jacoby; Systma, Mark D.; Talbert, Colin

2017-01-01

Invasive species provide a unique opportunity to evaluate factors controlling biogeographic distributions; we can consider introduction success as an experiment testing suitability of environmental conditions. Predicting potential distributions of spreading species is not easy, and forecasting potential distributions with changing climate is even more difficult. Using the globally invasive coypu (Myocastor coypus [Molina, 1782]), we evaluate and compare the utility of a simplistic ecophysiological based model and a correlative model to predict current and future distribution. The ecophysiological model was based on winter temperature relationships with nutria survival. We developed correlative statistical models using the Software for Assisted Habitat Modeling and biologically relevant climate data with a global extent. We applied the ecophysiological based model to several global circulation model (GCM) predictions for mid-century. We used global coypu introduction data to evaluate these models and to explore a hypothesized physiological limitation, finding general agreement with known coypu distribution locally and globally and support for an upper thermal tolerance threshold. Global circulation model based model results showed variability in coypu predicted distribution among GCMs, but had general agreement of increasing suitable area in the USA. Our methods highlighted the dynamic nature of the edges of the coypu distribution due to climate non-equilibrium, and uncertainty associated with forecasting future distributions. Areas deemed suitable habitat, especially those on the edge of the current known range, could be used for early detection of the spread of coypu populations for management purposes. Combining approaches can be beneficial to predicting potential distributions of invasive species now and in the future and in exploring hypotheses of factors controlling distributions.

Adapting environmental management to uncertain but inevitable change.

PubMed

Nicol, Sam; Fuller, Richard A; Iwamura, Takuya; Chadès, Iadine

2015-06-07

Implementation of adaptation actions to protect biodiversity is limited by uncertainty about the future. One reason for this is the fear of making the wrong decisions caused by the myriad future scenarios presented to decision-makers. We propose an adaptive management (AM) method for optimally managing a population under uncertain and changing habitat conditions. Our approach incorporates multiple future scenarios and continually learns the best management strategy from observations, even as conditions change. We demonstrate the performance of our AM approach by applying it to the spatial management of migratory shorebird habitats on the East Asian-Australasian flyway, predicted to be severely impacted by future sea-level rise. By accounting for non-stationary dynamics, our solution protects 25,000 more birds per year than the current best stationary approach. Our approach can be applied to many ecological systems that require efficient adaptation strategies for an uncertain future. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Wavelet modeling and prediction of the stability of states: the Roman Empire and the European Union

NASA Astrophysics Data System (ADS)

Yaroshenko, Tatyana Y.; Krysko, Dmitri V.; Dobriyan, Vitalii; Zhigalov, Maksim V.; Vos, Hendrik; Vandenabeele, Peter; Krysko, Vadim A.

2015-09-01

How can the stability of a state be quantitatively determined and its future stability predicted? The rise and collapse of empires and states is very complex, and it is exceedingly difficult to understand and predict it. Existing theories are usually formulated as verbal models and, consequently, do not yield sharply defined, quantitative prediction that can be unambiguously validated with data. Here we describe a model that determines whether the state is in a stable or chaotic condition and predicts its future condition. The central model, which we test, is that growth and collapse of states is reflected by the changes of their territories, populations and budgets. The model was simulated within the historical societies of the Roman Empire (400 BC to 400 AD) and the European Union (1957-2007) by using wavelets and analysis of the sign change of the spectrum of Lyapunov exponents. The model matches well with the historical events. During wars and crises, the state becomes unstable; this is reflected in the wavelet analysis by a significant increase in the frequency ω (t) and wavelet coefficients W (ω, t) and the sign of the largest Lyapunov exponent becomes positive, indicating chaos. We successfully reconstructed and forecasted time series in the Roman Empire and the European Union by applying artificial neural network. The proposed model helps to quantitatively determine and forecast the stability of a state.

The X-Ray Luminosity Functions of Field Low-Mass X-Ray Binaries in Early-Type Galaxies: Evidence for a Stellar Age Dependence

NASA Technical Reports Server (NTRS)

Lehmer, B. D.; Berkeley, M.; Zezas, A.; Alexander, D. M.; Basu-Zych, A.; Bauer, F. E.; Brandt, W. N.; Fragos, T.; Hornschemeier, A. E.; Kalogera, V.;

Depression as sickness behavior? A test of the host defense hypothesis in a high pathogen population.

PubMed

Stieglitz, Jonathan; Trumble, Benjamin C; Thompson, Melissa Emery; Blackwell, Aaron D; Kaplan, Hillard; Gurven, Michael

2015-10-01

Sadness is an emotion universally recognized across cultures, suggesting it plays an important functional role in regulating human behavior. Numerous adaptive explanations of persistent sadness interfering with daily functioning (hereafter "depression") have been proposed, but most do not explain frequent bidirectional associations between depression and greater immune activation. Here we test several predictions of the host defense hypothesis, which posits that depression is part of a broader coordinated evolved response to infection or tissue injury (i.e. "sickness behavior") that promotes energy conservation and reallocation to facilitate immune activation. In a high pathogen population of lean and relatively egalitarian Bolivian forager-horticulturalists, we test whether depression and its symptoms are associated with greater baseline concentration of immune biomarkers reliably associated with depression in Western populations (i.e. tumor necrosis factor alpha [TNF-α], interleukin-1 beta [IL-1β], interleukin-6 [IL-6], and C-reactive protein [CRP]). We also test whether greater pro-inflammatory cytokine responses to ex vivo antigen stimulation are associated with depression and its symptoms, which is expected if depression facilitates immune activation. These predictions are largely supported in a sample of older adult Tsimane (mean±SD age=53.2±11.0, range=34-85, n=649) after adjusting for potential confounders. Emotional, cognitive and somatic symptoms of depression are each associated with greater immune activation, both at baseline and in response to ex vivo stimulation. The association between depression and greater immune activation is therefore not unique to Western populations. While our findings are not predicted by other adaptive hypotheses of depression, they are not incompatible with those hypotheses and future research is necessary to isolate and test competing predictions. Copyright © 2015 Elsevier Inc. All rights reserved.

A population-based survey in Australia of men's and women's perceptions of genetic risk and predictive genetic testing and implications for primary care.

PubMed

Taylor, S

2011-01-01

Community attitudes research regarding genetic issues is important when contemplating the potential value and utilisation of predictive testing for common diseases in mainstream health services. This article aims to report population-based attitudes and discuss their relevance to integrating genetic services in primary health contexts. Men's and women's attitudes were investigated via population-based omnibus telephone survey in Queensland, Australia. Randomly selected adults (n = 1,230) with a mean age of 48.8 years were interviewed regarding perceptions of genetic determinants of health; benefits of genetic testing that predict 'certain' versus 'probable' future illness; and concern, if any, regarding potential misuse of genetic test information. Most (75%) respondents believed genetic factors significantly influenced health status; 85% regarded genetic testing positively although attitudes varied with age. Risk-based information was less valued than certainty-based information, but women valued risk information significantly more highly than men. Respondents reported 'concern' (44%) and 'no concern' (47%) regarding potential misuse of genetic information. This study contributes important population-based data as most research has involved selected individuals closely impacted by genetic disorders. While community attitudes were positive regarding genetic testing, genetic literacy is important to establish. The nature of gender differences regarding risk perception merits further study and has policy and service implications. Community concern about potential genetic discrimination must be addressed if health benefits of testing are to be maximised. Larger questions remain in scientific, policy, service delivery, and professional practice domains before predictive testing for common disorders is efficacious in mainstream health care. Copyright © 2011 S. Karger AG, Basel.

Code-based Diagnostic Algorithms for Idiopathic Pulmonary Fibrosis. Case Validation and Improvement.

PubMed

Ley, Brett; Urbania, Thomas; Husson, Gail; Vittinghoff, Eric; Brush, David R; Eisner, Mark D; Iribarren, Carlos; Collard, Harold R

2017-06-01

Population-based studies of idiopathic pulmonary fibrosis (IPF) in the United States have been limited by reliance on diagnostic code-based algorithms that lack clinical validation. To validate a well-accepted International Classification of Diseases, Ninth Revision, code-based algorithm for IPF using patient-level information and to develop a modified algorithm for IPF with enhanced predictive value. The traditional IPF algorithm was used to identify potential cases of IPF in the Kaiser Permanente Northern California adult population from 2000 to 2014. Incidence and prevalence were determined overall and by age, sex, and race/ethnicity. A validation subset of cases (n = 150) underwent expert medical record and chest computed tomography review. A modified IPF algorithm was then derived and validated to optimize positive predictive value. From 2000 to 2014, the traditional IPF algorithm identified 2,608 cases among 5,389,627 at-risk adults in the Kaiser Permanente Northern California population. Annual incidence was 6.8/100,000 person-years (95% confidence interval [CI], 6.1-7.7) and was higher in patients with older age, male sex, and white race. The positive predictive value of the IPF algorithm was only 42.2% (95% CI, 30.6 to 54.6%); sensitivity was 55.6% (95% CI, 21.2 to 86.3%). The corrected incidence was estimated at 5.6/100,000 person-years (95% CI, 2.6-10.3). A modified IPF algorithm had improved positive predictive value but reduced sensitivity compared with the traditional algorithm. A well-accepted International Classification of Diseases, Ninth Revision, code-based IPF algorithm performs poorly, falsely classifying many non-IPF cases as IPF and missing a substantial proportion of IPF cases. A modification of the IPF algorithm may be useful for future population-based studies of IPF.

Forecasting Tunisian type 2 diabetes prevalence to 2027: validation of a simple model.

PubMed

Saidi, Olfa; O'Flaherty, Martin; Mansour, Nadia Ben; Aissi, Wafa; Lassoued, Olfa; Capewell, Simon; Critchley, Julia A; Malouche, Dhafer; Romdhane, Habiba Ben

2015-02-07

Most projections of type 2 diabetes (T2D) prevalence are simply based on demographic change (i.e. ageing). We developed a model to predict future trends in T2D prevalence in Tunisia, explicitly taking into account trends in major risk factors (obesity and smoking). This could improve assessment of policy options for prevention and health service planning. The IMPACT T2D model uses a Markov approach to integrate population, obesity and smoking trends to estimate future T2D prevalence. We developed a model for the Tunisian population from 1997 to 2027, and validated the model outputs by comparing with a subsequent T2D prevalence survey conducted in 2005. The model estimated that the prevalence of T2D among Tunisians aged over 25 years was 12.0% in 1997 (95% confidence intervals 9.6%-14.4%), increasing to 15.1% (12.5%-17.4%) in 2005. Between 1997 and 2005, observed prevalence in men increased from 13.5% to 16.1% and in women from 12.9% to 14.1%. The model forecast for a dramatic rise in prevalence by 2027 (26.6% overall, 28.6% in men and 24.7% in women). However, if obesity prevalence declined by 20% in the 10 years from 2013, and if smoking decreased by 20% over 10 years from 2009, a 3.3% reduction in T2D prevalence could be achieved in 2027 (2.5% in men and 4.1% in women). This innovative model provides a reasonably close estimate of T2D prevalence for Tunisia over the 1997-2027 period. Diabetes burden is now a significant public health challenge. Our model predicts that this burden will increase significantly in the next two decades. Tackling obesity, smoking and other T2D risk factors thus needs urgent action. Tunisian decision makers have therefore defined two strategies: obesity reduction and tobacco control. Responses will be evaluated in future population surveys.

Morphological and Genetic Variation along a North-to-South Transect in Stipa purpurea, a Dominant Grass on the Qinghai-Tibetan Plateau: Implications for Response to Climate Change

PubMed Central

You, Jianling; Qi, Danhui; Zhou, Yin; Chen, Jiakuan; Song, Zhiping

2016-01-01

Estimating the potential of species to cope with rapid environmental climatic modifications is of vital importance for determining their future viability and conservation. The variation between existing populations along a climatic gradient may predict how a species will respond to future climate change. Stipa purpurea is a dominant grass species in the alpine steppe and meadow of the Qinghai-Tibetan Plateau (QTP). Ecological niche modelling was applied to S. purpurea, and its distribution was found to be most strongly correlated with the annual precipitation and the mean temperature of the warmest quarter. We established a north-to-south transect over 2000 km long on the QTP reflecting the gradients of temperature and precipitation, and then we estimated the morphological by sampling fruited tussocks and genetic divergence by using 11 microsatellite markers between 20 populations along the transect. Reproductive traits (the number of seeds and reproductive shoots), the reproductive-vegetative growth ratio and the length of roots in the S. purpurea populations varied significantly with climate variables. S. purpurea has high genetic diversity (He = 0.585), a large effective population size (Ne >1,000), and a considerable level of gene flow between populations. The S. purpurea populations have a mosaic genetic structure: some distant populations (over 1000 km apart) clustered genetically, whereas closer populations (< 100 km apart) had diverged significantly, suggesting local adaptation. Asymmetrical long-distance inter-population gene flow occurs along the sampling transect and might be mediated by seed dispersal via migratory herbivores, such as the chiru (Pantholops hodgsonii). These findings suggest that population performance variation and gene flow both facilitate the response of S. purpurea to climate change. PMID:27580056

Morphological and Genetic Variation along a North-to-South Transect in Stipa purpurea, a Dominant Grass on the Qinghai-Tibetan Plateau: Implications for Response to Climate Change.

PubMed

Liu, Wensheng; Zhao, Yao; You, Jianling; Qi, Danhui; Zhou, Yin; Chen, Jiakuan; Song, Zhiping

2016-01-01

Estimating the potential of species to cope with rapid environmental climatic modifications is of vital importance for determining their future viability and conservation. The variation between existing populations along a climatic gradient may predict how a species will respond to future climate change. Stipa purpurea is a dominant grass species in the alpine steppe and meadow of the Qinghai-Tibetan Plateau (QTP). Ecological niche modelling was applied to S. purpurea, and its distribution was found to be most strongly correlated with the annual precipitation and the mean temperature of the warmest quarter. We established a north-to-south transect over 2000 km long on the QTP reflecting the gradients of temperature and precipitation, and then we estimated the morphological by sampling fruited tussocks and genetic divergence by using 11 microsatellite markers between 20 populations along the transect. Reproductive traits (the number of seeds and reproductive shoots), the reproductive-vegetative growth ratio and the length of roots in the S. purpurea populations varied significantly with climate variables. S. purpurea has high genetic diversity (He = 0.585), a large effective population size (Ne >1,000), and a considerable level of gene flow between populations. The S. purpurea populations have a mosaic genetic structure: some distant populations (over 1000 km apart) clustered genetically, whereas closer populations (< 100 km apart) had diverged significantly, suggesting local adaptation. Asymmetrical long-distance inter-population gene flow occurs along the sampling transect and might be mediated by seed dispersal via migratory herbivores, such as the chiru (Pantholops hodgsonii). These findings suggest that population performance variation and gene flow both facilitate the response of S. purpurea to climate change.

Predictability of state-level flood damage in the conterminous United States: the role of hazard, exposure and vulnerability

DOE PAGES

Zhou, Qianqian; Leng, Guoyong; Feng, Leyang

2017-07-13

Understanding historical changes in flood damage and the underlying mechanisms is critical for predicting future changes for better adaptations. In this study, a detailed assessment of flood damage for 1950–1999 is conducted at the state level in the conterminous United States (CONUS). Geospatial datasets on possible influencing factors are then developed by synthesizing natural hazards, population, wealth, cropland and urban area to explore the relations with flood damage. A considerable increase in flood damage in CONUS is recorded for the study period which is well correlated with hazards. Comparably, runoff indexed hazards simulated by the Variable Infiltration Capacity (VIC) modelmore » can explain a larger portion of flood damage variations than precipitation in 84% of the states. Cropland is identified as an important factor contributing to increased flood damage in central US while urbanland exhibits positive and negative relations with total flood damage and damage per unit wealth in 20 and 16 states, respectively. Altogether, flood damage in 34 out of 48 investigated states can be predicted at the 90% confidence level. In extreme cases, ~76% of flood damage variations can be explained in some states, highlighting the potential of future flood damage prediction based on climate change and socioeconomic scenarios.« less

Predictability of state-level flood damage in the conterminous United States: the role of hazard, exposure and vulnerability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Qianqian; Leng, Guoyong; Feng, Leyang

Understanding historical changes in flood damage and the underlying mechanisms is critical for predicting future changes for better adaptations. In this study, a detailed assessment of flood damage for 1950–1999 is conducted at the state level in the conterminous United States (CONUS). Geospatial datasets on possible influencing factors are then developed by synthesizing natural hazards, population, wealth, cropland and urban area to explore the relations with flood damage. A considerable increase in flood damage in CONUS is recorded for the study period which is well correlated with hazards. Comparably, runoff indexed hazards simulated by the Variable Infiltration Capacity (VIC) modelmore » can explain a larger portion of flood damage variations than precipitation in 84% of the states. Cropland is identified as an important factor contributing to increased flood damage in central US while urbanland exhibits positive and negative relations with total flood damage and damage per unit wealth in 20 and 16 states, respectively. Altogether, flood damage in 34 out of 48 investigated states can be predicted at the 90% confidence level. In extreme cases, ~76% of flood damage variations can be explained in some states, highlighting the potential of future flood damage prediction based on climate change and socioeconomic scenarios.« less

Should nuclear energy form part of the UK's energy future?

NASA Astrophysics Data System (ADS)

Campbell, Peter

2003-03-01

Energy policies are under review everywhere, as the world tries to meet targets for reducing climate change despite continuing population growth. A major change in energy patterns is needed, with the critical period for transition predictably happening when young people currently at school are in their middle years of their lives. This article describes one way of bringing the debate surrounding energy demand and supply to life in physics classrooms.

East Europe Report, Political, Sociological and Military Affairs, No. 2169.

DTIC Science & Technology

1983-07-20

laughed at Malthus’ predictions about food and population." The Domestic "New Philosophers" After 100 years the humanistic ideas of the classics of...is not pointless for us to reflect about the nonmaterial, ideological, but also existential offers of our self-managing Left, offers without the...but certainly humanistic future. People are familiar, then, with the commitments of Belgraders, they know the aims of Belgrade, and the means and

Air Quality and Health Impacts of Future Ethanol Production and Use in São Paulo State, Brazil.

PubMed

Scovronick, Noah; França, Daniela; Alonso, Marcelo; Almeida, Claudia; Longo, Karla; Freitas, Saulo; Rudorff, Bernardo; Wilkinson, Paul

2016-07-11

It is often argued that liquid biofuels are cleaner than fossil fuels, and therefore better for human health, however, the evidence on this issue is still unclear. Brazil's high uptake of ethanol and role as a major producer makes it the most appropriate case study to assess the merits of different biofuel policies. Accordingly, we modeled the impact on air quality and health of two future fuel scenarios in São Paulo State: a business-as-usual scenario where ethanol production and use proceeds according to government predictions and a counterfactual scenario where ethanol is frozen at 2010 levels and future transport fuel demand is met with gasoline. The population-weighted exposure to fine particulate matter (PM2.5) and ozone was 3.0 μg/m³ and 0.3 ppb lower, respectively, in 2020 in the scenario emphasizing gasoline compared with the business-as-usual (ethanol) scenario. The lower exposure to both pollutants in the gasoline scenario would result in the population living 1100 additional life-years in the first year, and if sustained, would increase to 40,000 life-years in year 20 and continue to rise. Without additional measures to limit emissions, increasing the use of ethanol in Brazil could lead to higher air pollution-related population health burdens when compared to policy that prioritizes gasoline.

Human-water interactions in Colorado: Evaluating the impacts of population growth, energy development and dynamic industries on water resource management

NASA Astrophysics Data System (ADS)

Hogue, Terri; Walker, Ella; Read, Laura

2016-04-01

The gap between water supply and demand is growing in the western U.S. due to climate change, rapid population growth, intensive agricultural production, wide-spread energy development and changing industrial use. Water conservation efforts among residential and industrial water users, recycling and reuse techniques, and innovative regulatory frameworks strive to mitigate this gap, however, the extent of these management strategies are often difficult to quantify and are typically not included in prediction of future water allocations. Water use on the eastern slope in Colorado (Denver-Metro region) is impacted by high-intensity activities, including unconventional energy development, large withdrawals for agriculture, and increasing demand for recreational industries. These demands are in addition to a projected population increase of 100% by 2050 in the South Platte River basin, which encompasses the Denver-Metro region. The current presentation focuses on the quantification of regional sector water use utilzing a range of observations and technologies (including remote sensing) and integration into a regional decision support system. We explore scenarios of future water use in the energy, agriculture, and municipal/industrial sectors, and discuss the potential water allocation tradeoffs to various stakeholders. We also employ climate projections to quantify the potential range of water availability under various scenarios and observe the extent to which future climate may influence regional management decisions.

Air Quality and Health Impacts of Future Ethanol Production and Use in São Paulo State, Brazil

PubMed Central

Scovronick, Noah; França, Daniela; Alonso, Marcelo; Almeida, Claudia; Longo, Karla; Freitas, Saulo; Rudorff, Bernardo; Wilkinson, Paul

2016-01-01

It is often argued that liquid biofuels are cleaner than fossil fuels, and therefore better for human health, however, the evidence on this issue is still unclear. Brazil’s high uptake of ethanol and role as a major producer makes it the most appropriate case study to assess the merits of different biofuel policies. Accordingly, we modeled the impact on air quality and health of two future fuel scenarios in São Paulo State: a business-as-usual scenario where ethanol production and use proceeds according to government predictions and a counterfactual scenario where ethanol is frozen at 2010 levels and future transport fuel demand is met with gasoline. The population-weighted exposure to fine particulate matter (PM2.5) and ozone was 3.0 μg/m3 and 0.3 ppb lower, respectively, in 2020 in the scenario emphasizing gasoline compared with the business-as-usual (ethanol) scenario. The lower exposure to both pollutants in the gasoline scenario would result in the population living 1100 additional life-years in the first year, and if sustained, would increase to 40,000 life-years in year 20 and continue to rise. Without additional measures to limit emissions, increasing the use of ethanol in Brazil could lead to higher air pollution-related population health burdens when compared to policy that prioritizes gasoline. PMID:27409628

Population growth of Yellowstone grizzly bears: Uncertainty and future monitoring

USGS Publications Warehouse

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.

Measuring Gambling Reinforcers, Over Consumption and Fallacies: The Psychometric Properties and Predictive Validity of the Jonsson-Abbott Scale.

PubMed

Jonsson, Jakob; Abbott, Max W; Sjöberg, Anders; Carlbring, Per

2017-01-01

Traditionally, gambling and problem gambling research relies on cross-sectional and retrospective designs. This has compromised identification of temporal relationships and causal inference. To overcome these problems a new questionnaire, the Jonsson-Abbott Scale (JAS), was developed and used in a large, prospective, general population study, The Swedish Longitudinal Gambling Study (Swelogs). The JAS has 11 items and seeks to identify early indicators, examine relationships between indicators and assess their capacity to predict future problem progression. The aims of the study were to examine psychometric properties of the JAS (internal consistency and dimensionality) and predictive validity with respect to increased gambling risk and problem gambling onset. The results are based on repeated interviews with 3818 participants. The response rate from the initial baseline wave was 74%. The original sample consisted of a random, stratified selection from the Swedish population register aged between 16 and 84. The results indicate an acceptable fit of a three-factor solution in a confirmatory factor analysis with 'Over consumption,' 'Gambling fallacies,' and 'Reinforcers' as factors. Reinforcers, Over consumption and Gambling fallacies were significant predictors of gambling risk potential and Gambling fallacies and Over consumption were significant predictors of problem gambling onset (incident cases) at 12 month follow up. When controlled for risk potential measured at baseline, the predictor Over consumption was not significant for gambling risk potential at follow up. For incident cases, Gambling fallacies and Over consumption remained significant when controlled for risk potential. Implications of the results for the development of problem gambling, early detection, prevention, and future research are discussed.

Parent Expectations Mediate Outcomes for Young Adults with Autism Spectrum Disorder.

PubMed

Kirby, Anne V

2016-05-01

Understanding the complex relationships among factors that may predict the outcomes of young adults with autism spectrum disorder (ASD) is of utmost importance given the increasing population undergoing and anticipating the transition to adulthood. With a sample of youth with ASD (n = 1170) from the National Longitudinal Transition Study-2, structural equation modeling techniques were used to test parent expectations as a mediator of young adult outcomes (i.e., employment, residential independence, social participation) in a longitudinal analysis. The mediation hypothesis was confirmed; family background and functional performance variables significantly predicted parent expectations which significantly predicted outcomes. These findings add context to previous studies examining the role of parent expectations on young adult outcomes and inform directions for family-centered interventions and future research.

Anticipating Their Future: Adolescent Values for the Future Predict Adult Behaviors

PubMed Central

Finlay, Andrea; Wray-Lake, Laura; Warren, Michael; Maggs, Jennifer L.

2014-01-01

Adolescent future values – beliefs about what will matter to them in the future – may shape their adult behavior. Utilizing a national longitudinal British sample, this study examined whether adolescent future values in six domains (i.e., family responsibility, full-time job, personal responsibility, autonomy, civic responsibility, and hedonistic privilege) predicted adult social roles, civic behaviors, and alcohol use. Future values positively predicted behaviors within the same domain; fewer cross-domain associations were evident. Civic responsibility positively predicted adult civic behaviors, but negatively predicted having children. Hedonistic privilege positively predicted adult alcohol use and negatively predicted civic behaviors. Results suggest that attention should be paid to how adolescents are thinking about their futures due to the associated links with long-term social and health behaviors. PMID:26279595

High intra-specific variation in avian body condition responses to climate limits generalisation across species

PubMed Central

van der Jeugd, Henk P.; van de Pol, Martijn

2018-01-01

It is generally assumed that populations of a species will have similar responses to climate change, and thereby that a single value of sensitivity will reflect species-specific responses. However, this assumption is rarely systematically tested. High intraspecific variation will have consequences for identifying species- or population-level traits that can predict differences in sensitivity, which in turn can affect the reliability of projections of future climate change impacts. We investigate avian body condition responses to changes in six climatic variables and how consistent and generalisable these responses are both across and within species, using 21 years of data from 46 common passerines across 80 Dutch sites. We show that body condition decreases with warmer spring/early summer temperatures and increases with higher humidity, but other climate variables do not show consistent trends across species. In the future, body condition is projected to decrease by 2050, mainly driven by temperature effects. Strikingly, populations of the same species generally responded just as differently as populations of different species implying that a single species signal is not meaningful. Consequently, species-level traits did not explain interspecific differences in sensitivities, rather population-level traits were more important. The absence of a clear species signal in body condition responses implies that generalisation and identifying species for conservation prioritisation is problematic, which sharply contrasts conclusions of previous studies on the climate sensitivity of phenology. PMID:29466460

Linking climate change projections for an Alaskan watershed to future coho salmon production.

PubMed

Leppi, Jason C; Rinella, Daniel J; Wilson, Ryan R; Loya, Wendy M

2014-06-01

Climate change is predicted to dramatically change hydrologic processes across Alaska, but estimates of how these impacts will influence specific watersheds and aquatic species are lacking. Here, we linked climate, hydrology, and habitat models within a coho salmon (Oncorhynchus kisutch) population model to assess how projected climate change could affect survival at each freshwater life stage and, in turn, production of coho salmon smolts in three subwatersheds of the Chuitna (Chuit) River watershed, Alaska. Based on future climate scenarios and projections from a three-dimensional hydrology model, we simulated coho smolt production over a 20-year span at the end of the century (2080-2100). The direction (i.e., positive vs. negative) and magnitude of changes in smolt production varied substantially by climate scenario and subwatershed. Projected smolt production decreased in all three subwatersheds under the minimum air temperature and maximum precipitation scenario due to elevated peak flows and a resulting 98% reduction in egg-to-fry survival. In contrast, the maximum air temperature and minimum precipitation scenario led to an increase in smolt production in all three subwatersheds through an increase in fry survival. Other climate change scenarios led to mixed responses, with projected smolt production increasing and decreasing in different subwatersheds. Our analysis highlights the complexity inherent in predicting climate-change-related impacts to salmon populations and demonstrates that population effects may depend on interactions between the relative magnitude of hydrologic and thermal changes and their interactions with features of the local habitat. © 2013 The Authors. Global Change Biology published by John Wiley & Sons Ltd.

Health Data Entanglement and artificial intelligence-based analysis: a brand new methodology to improve the effectiveness of healthcare services.

PubMed

Capone, A; Cicchetti, A; Mennini, F S; Marcellusi, A; Baio, G; Favato, G

2016-01-01

Healthcare expenses will be the most relevant policy issue for most governments in the EU and in the USA. This expenditure can be associated with two major key categories: demographic and economic drivers. Factors driving healthcare expenditure were rarely recognised, measured and comprehended. An improvement of health data generation and analysis is mandatory, and in order to tackle healthcare spending growth, it may be useful to design and implement an effective, advanced system to generate and analyse these data. A methodological approach relied upon the Health Data Entanglement (HDE) can be a suitable option. By definition, in the HDE a large amount of data sets having several sources are functionally interconnected and computed through learning machines that generate patterns of highly probable future health conditions of a population. Entanglement concept is borrowed from quantum physics and means that multiple particles (information) are linked together in a way such that the measurement of one particle's quantum state (individual health conditions and related economic requirements) determines the possible quantum states of other particles (population health forecasts to predict their impact). The value created by the HDE is based on the combined evaluation of clinical, economic and social effects generated by health interventions. To predict the future health conditions of a population, analyses of data are performed using self-learning AI, in which sequential decisions are based on Bayesian algorithmic probabilities. HDE and AI-based analysis can be adopted to improve the effectiveness of the health governance system in ways that also lead to better quality of care.

A Novel Application of Agent-based Modeling: Projecting Water Access and Availability Using a Coupled Hydrologic Agent-based Model in the Nzoia Basin, Kenya

NASA Astrophysics Data System (ADS)

Le, A.; Pricope, N. G.

2015-12-01

Projections indicate that increasing population density, food production, and urbanization in conjunction with changing climate conditions will place stress on water resource availability. As a result, a holistic understanding of current and future water resource distribution is necessary for creating strategies to identify the most sustainable means of accessing this resource. Currently, most water resource management strategies rely on the application of global climate predictions to physically based hydrologic models to understand potential changes in water availability. However, the need to focus on understanding community-level social behaviors that determine individual water usage is becoming increasingly evident, as predictions derived only from hydrologic models cannot accurately represent the coevolution of basin hydrology and human water and land usage. Models that are better equipped to represent the complexity and heterogeneity of human systems and satellite-derived products in place of or in conjunction with historic data significantly improve preexisting hydrologic model accuracy and application outcomes. We used a novel agent-based sociotechnical model that combines the Soil and Water Assessment Tool (SWAT) and Agent Analyst and applied it in the Nzoia Basin, an area in western Kenya that is becoming rapidly urbanized and industrialized. Informed by a combination of satellite-derived products and over 150 household surveys, the combined sociotechnical model provided unique insight into how populations self-organize and make decisions based on water availability. In addition, the model depicted how population organization and current management alter water availability currently and in the future.

The past as prelude to the future for understanding 21st-century climate effects on Rocky Mountain Trout

USGS Publications Warehouse

Isaak, Daniel J.; Muhlfeld, Clint C.; Todd, Andrew S.; Al-chokhachy, Robert; Roberts, James; Kershner, Jeffrey L.; Fausch, Kurt D.; Hostetler, Steven W.

2012-01-01

Bioclimatic models predict large reductions in native trout across the Rocky Mountains in the 21st century but lack details about how changes will occur. Through five case histories across the region, we explore how a changing climate has been affecting streams and the potential consequences for trout. Monitoring records show trends in temperature and hydrographs consistent with a warming climate in recent decades. Biological implications include upstream shifts in thermal habitats, risk of egg scour, increased wildfire disturbances, and declining summer habitat volumes. The importance of these factors depends on the context, but temperature increases are most relevant where population boundaries are mediated by thermal constraints. Summer flow declines and wildfires will be important where trout populations are fragmented and constrained to small refugia. A critical information gap is evidence documenting how populations are adjusting to long-term habitat trends, so biological monitoring is a priority. Biological, temperature, and discharge data from monitoring networks could be used to develop accurate vulnerability assessments that provide information regarding where conservation actions would best improve population resilience. Even with better information, future uncertainties will remain large due to unknowns regarding Earth's ultimate warming trajectory and how effects translate across scales. Maintaining or increasing the size of habitats could provide a buffer against these uncertainties.

Natural variation and the capacity to adapt to ocean acidification in the keystone sea urchin Strongylocentrotus purpuratus.

PubMed

Kelly, Morgan W; Padilla-Gamiño, Jacqueline L; Hofmann, Gretchen E

2013-08-01

A rapidly growing body of literature documents the potential negative effects of CO2 -driven ocean acidification (OA) on marine organisms. However, nearly all this work has focused on the effects of future conditions on modern populations, neglecting the role of adaptation. Rapid evolution can alter demographic responses to environmental change, ultimately affecting the likelihood of population persistence, but the capacity for adaptation will differ among populations and species. Here, we measure the capacity of the ecologically important purple sea urchin Strongylocentrotus purpuratus to adapt to OA, using a breeding experiment to estimate additive genetic variance for larval size (an important component of fitness) under future high-pCO2 /low-pH conditions. Although larvae reared under future conditions were smaller than those reared under present-day conditions, we show that there is also abundant genetic variation for body size under elevated pCO2 , indicating that this trait can evolve. The observed heritability of size was 0.40 ± 0.32 (95% CI) under low pCO2 , and 0.50 ± 0.30 under high-pCO2 conditions. Accounting for the observed genetic variation in models of future larval size and demographic rates substantially alters projections of performance for this species in the future ocean. Importantly, our model shows that after incorporating the effects of adaptation, the OA-driven decrease in population growth rate is up to 50% smaller, than that predicted by the 'no-adaptation' scenario. Adults used in the experiment were collected from two sites on the coast of the Northeast Pacific that are characterized by different pH regimes, as measured by autonomous sensors. Comparing results between sites, we also found subtle differences in larval size under high-pCO2 rearing conditions, consistent with local adaptation to carbonate chemistry in the field. These results suggest that spatially varying selection may help to maintain genetic variation necessary for adaptation to future OA. © 2013 John Wiley & Sons Ltd.

Stochastic analysis of future vehicle populations

DOT National Transportation Integrated Search

1979-05-01

The purpose of this study was to build a stochastic model of future vehicle populations. Such a model can be used to investigate the uncertainties inherent in Future Vehicle Populations. The model, which is called the Future Automobile Population Sto...

Population of Nuclei Via 7Li-Induced Binary Reactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clark, R M; Phair, L W; Descovich, M

2005-08-09

The authors have investigated the population of nuclei formed in binary reactions involving {sup 7}Li beams on targets of {sup 160}Gd and {sup 184}W. The {sup 7}Li + {sup 184}W data were taken in the first experiment using the LIBERACE Ge-array in combination with the STARS Si {Delta}E-E telescope system at the 88-Inch Cyclotron of the Lawrence Berkeley National Laboratory. By using the Wilczynski binary transfer model, in combination with a standard evaporation model, they are able to reproduce the experimental results. This is a useful method for predicting the population of neutron-rich heavy nuclei formed in binary reactions involvingmore » beams of weakly bound nuclei and will be of use in future spectroscopic studies.« less

Early warning signals detect critical impacts of experimental warming.

PubMed

Jarvis, Lauren; McCann, Kevin; Tunney, Tyler; Gellner, Gabriel; Fryxell, John M

2016-09-01

Earth's surface temperatures are projected to increase by ~1-4°C over the next century, threatening the future of global biodiversity and ecosystem stability. While this has fueled major progress in the field of physiological trait responses to warming, it is currently unclear whether routine population monitoring data can be used to predict temperature-induced population collapse. Here, we integrate trait performance theory with that of critical tipping points to test whether early warning signals can be reliably used to anticipate thermally induced extinction events. We find that a model parameterized by experimental growth rates exhibits critical slowing down in the vicinity of an experimentally tested critical threshold, suggesting that dynamical early warning signals may be useful in detecting the potentially precipitous onset of population collapse due to global climate change.

Mammographic density, breast cancer risk and risk prediction

PubMed Central

Vachon, Celine M; van Gils, Carla H; Sellers, Thomas A; Ghosh, Karthik; Pruthi, Sandhya; Brandt, Kathleen R; Pankratz, V Shane

2007-01-01

In this review, we examine the evidence for mammographic density as an independent risk factor for breast cancer, describe the risk prediction models that have incorporated density, and discuss the current and future implications of using mammographic density in clinical practice. Mammographic density is a consistent and strong risk factor for breast cancer in several populations and across age at mammogram. Recently, this risk factor has been added to existing breast cancer risk prediction models, increasing the discriminatory accuracy with its inclusion, albeit slightly. With validation, these models may replace the existing Gail model for clinical risk assessment. However, absolute risk estimates resulting from these improved models are still limited in their ability to characterize an individual's probability of developing cancer. Promising new measures of mammographic density, including volumetric density, which can be standardized using full-field digital mammography, will likely result in a stronger risk factor and improve accuracy of risk prediction models. PMID:18190724

Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models.

PubMed

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.

Development and validation of a cancer-specific swallowing assessment tool: MASA-C.

PubMed

Carnaby, Giselle D; Crary, Michael A

2014-03-01

We present data from a sample of patients receiving radiotherapy for head/neck cancer to define and measure the validity of a new clinical assessment measure for swallowing. Fifty-eight patients undergoing radiotherapy (±chemotherapy) for head/neck cancer (HNC) supported the development of a physiology-based assessment tool of swallowing (Mann Assessment of Swallowing Ability--Cancer: MASA-C) administered at two time points (baseline and following radiotherapy treatment). The new exam was evaluated for internal consistency of items using Cronbach's alpha. Reliability of measurement was evaluated with intraclass correlation (ICC) and the Kappa statistic between two independent raters. Concurrent validity was established through comparison with the original MASA examination and against the referent standard videofluoroscopic swallowing examination (VFE). Sensitivity, specificity, and likelihood ratios along with 95 % confidence intervals (CIs) were derived for comparison of the two evaluation forms (MASA vs. MASA-C). Accuracy of diagnostic precision was displayed using receiver operator characteristic curves. The new MASA-C tool demonstrated superior validity to the original MASA examination applied to a HNC population. In comparison to the VFE referent exam, the MASA-C revealed strong sensitivity and specificity (Se 83, Sp 96), predictive values (positive predictive value (PPV) 0.95, negative predictive value (NPV) 0.86), and likelihood ratios (21.6). In addition, it demonstrated good reliability (ICC = 0.96) between speech-language pathology raters. The MASA-C is a reliable and valid scale that is sensitive to differences in swallowing performance in HNC patients with and without dysphagia. Future longitudinal evaluation of this tool in larger samples is suggested. The development and refinement of this swallowing assessment tool for use in multidisciplinary HNC teams will facilitate earlier identification of patients with swallowing difficulties and enable more efficient allocation of resources to the management of dysphagia in this population. The MASA-C may also prove useful in future clinical HNC rehabilitation trials with this population.

Distributional dynamics of a vulnerable species in response to past and future climate change: a window for conservation prospects

PubMed Central

Bai, Yunjun; Wei, Xueping

2018-01-01

Background The ongoing change in climate is predicted to exert unprecedented effects on Earth’s biodiversity at all levels of organization. Biological conservation is important to prevent biodiversity loss, especially for species facing a high risk of extinction. Understanding the past responses of species to climate change is helpful for revealing response mechanisms, which will contribute to the development of effective conservation strategies in the future. Methods In this study, we modelled the distributional dynamics of a ‘Vulnerable’ species, Pseudolarix amabilis, in response to late Quaternary glacial-interglacial cycles and future 2080 climate change using an ecological niche model (MaxEnt). We also performed migration vector analysis to reveal the potential migration of the population over time. Results Historical modelling indicates that the range dynamics of P. amabilis is highly sensitive to climate change and that its long-distance dispersal ability and potential for evolutionary adaption are limited. Compared to the current climatically suitable areas for this species, future modelling showed significant migration northward towards future potential climatically suitable areas. Discussion In combination with the predicted future distribution, the mechanism revealed by the historical response suggests that this species will not be able to fully occupy the future expanded areas of suitable climate or adapt to the unsuitable climate across the future contraction regions. As a result, we suggest assisted migration as an effective supplementary means of conserving this vulnerable species in the face of the unprecedentedly rapid climate change of the 21st century. As a study case, this work highlights the significance of introducing historical perspectives while researching species conservation, especially for currently vulnerable or endangered taxa that once had a wider distribution in geological time. PMID:29362700

Distributional dynamics of a vulnerable species in response to past and future climate change: a window for conservation prospects.

PubMed

Bai, Yunjun; Wei, Xueping; Li, Xiaoqiang

2018-01-01

The ongoing change in climate is predicted to exert unprecedented effects on Earth's biodiversity at all levels of organization. Biological conservation is important to prevent biodiversity loss, especially for species facing a high risk of extinction. Understanding the past responses of species to climate change is helpful for revealing response mechanisms, which will contribute to the development of effective conservation strategies in the future. In this study, we modelled the distributional dynamics of a 'Vulnerable' species, Pseudolarix amabilis , in response to late Quaternary glacial-interglacial cycles and future 2080 climate change using an ecological niche model (MaxEnt). We also performed migration vector analysis to reveal the potential migration of the population over time. Historical modelling indicates that the range dynamics of P. amabilis is highly sensitive to climate change and that its long-distance dispersal ability and potential for evolutionary adaption are limited. Compared to the current climatically suitable areas for this species, future modelling showed significant migration northward towards future potential climatically suitable areas. In combination with the predicted future distribution, the mechanism revealed by the historical response suggests that this species will not be able to fully occupy the future expanded areas of suitable climate or adapt to the unsuitable climate across the future contraction regions. As a result, we suggest assisted migration as an effective supplementary means of conserving this vulnerable species in the face of the unprecedentedly rapid climate change of the 21st century. As a study case, this work highlights the significance of introducing historical perspectives while researching species conservation, especially for currently vulnerable or endangered taxa that once had a wider distribution in geological time.

Accuracy of genomic prediction in switchgrass ( Panicum virgatum L.) improved by accounting for linkage disequilibrium

DOE PAGES

Ramstein, Guillaume P.; Evans, Joseph; Kaeppler, Shawn M.; ...

2016-02-11

Switchgrass is a relatively high-yielding and environmentally sustainable biomass crop, but further genetic gains in biomass yield must be achieved to make it an economically viable bioenergy feedstock. Genomic selection (GS) is an attractive technology to generate rapid genetic gains in switchgrass, and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. In this study, we empirically assessed prediction procedures for genomic selection in two different populations, consisting of 137 and 110 half-sib families of switchgrass, tested in two locations in the United States for three agronomic traits: dry matter yield, plant height,more » and heading date. Marker data were produced for the families’ parents by exome capture sequencing, generating up to 141,030 polymorphic markers with available genomic-location and annotation information. We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data were preprocessed to account for redundancy in marker information. More complex genomic prediction procedures were generally not significantly more accurate than the simplest procedure, likely due to limited population sizes. Nevertheless, a highly significant gain in prediction accuracy was achieved by transforming the marker data through a marker correlation matrix. Our results suggest that marker-data transformations and, more generally, the account of linkage disequilibrium among markers, offer valuable opportunities for improving prediction procedures in GS. Furthermore, some of the achieved prediction accuracies should motivate implementation of GS in switchgrass breeding programs.« less

Accuracy of genomic prediction in switchgrass ( Panicum virgatum L.) improved by accounting for linkage disequilibrium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramstein, Guillaume P.; Evans, Joseph; Kaeppler, Shawn M.

Switchgrass is a relatively high-yielding and environmentally sustainable biomass crop, but further genetic gains in biomass yield must be achieved to make it an economically viable bioenergy feedstock. Genomic selection (GS) is an attractive technology to generate rapid genetic gains in switchgrass, and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. In this study, we empirically assessed prediction procedures for genomic selection in two different populations, consisting of 137 and 110 half-sib families of switchgrass, tested in two locations in the United States for three agronomic traits: dry matter yield, plant height,more » and heading date. Marker data were produced for the families’ parents by exome capture sequencing, generating up to 141,030 polymorphic markers with available genomic-location and annotation information. We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data were preprocessed to account for redundancy in marker information. More complex genomic prediction procedures were generally not significantly more accurate than the simplest procedure, likely due to limited population sizes. Nevertheless, a highly significant gain in prediction accuracy was achieved by transforming the marker data through a marker correlation matrix. Our results suggest that marker-data transformations and, more generally, the account of linkage disequilibrium among markers, offer valuable opportunities for improving prediction procedures in GS. Furthermore, some of the achieved prediction accuracies should motivate implementation of GS in switchgrass breeding programs.« less

Extending Theory-Based Quantitative Predictions to New Health Behaviors.

PubMed

Brick, Leslie Ann D; Velicer, Wayne F; Redding, Colleen A; Rossi, Joseph S; Prochaska, James O

2016-04-01

Traditional null hypothesis significance testing suffers many limitations and is poorly adapted to theory testing. A proposed alternative approach, called Testing Theory-based Quantitative Predictions, uses effect size estimates and confidence intervals to directly test predictions based on theory. This paper replicates findings from previous smoking studies and extends the approach to diet and sun protection behaviors using baseline data from a Transtheoretical Model behavioral intervention (N = 5407). Effect size predictions were developed using two methods: (1) applying refined effect size estimates from previous smoking research or (2) using predictions developed by an expert panel. Thirteen of 15 predictions were confirmed for smoking. For diet, 7 of 14 predictions were confirmed using smoking predictions and 6 of 16 using expert panel predictions. For sun protection, 3 of 11 predictions were confirmed using smoking predictions and 5 of 19 using expert panel predictions. Expert panel predictions and smoking-based predictions poorly predicted effect sizes for diet and sun protection constructs. Future studies should aim to use previous empirical data to generate predictions whenever possible. The best results occur when there have been several iterations of predictions for a behavior, such as with smoking, demonstrating that expected values begin to converge on the population effect size. Overall, the study supports necessity in strengthening and revising theory with empirical data.

Validation of a multifactorial risk factor model used for predicting future caries risk with Nevada adolescents.

PubMed

Ditmyer, Marcia M; Dounis, Georgia; Howard, Katherine M; Mobley, Connie; Cappelli, David

2011-05-20

The objective of this study was to measure the validity and reliability of a multifactorial Risk Factor Model developed for use in predicting future caries risk in Nevada adolescents in a public health setting. This study examined retrospective data from an oral health surveillance initiative that screened over 51,000 students 13-18 years of age, attending public/private schools in Nevada across six academic years (2002/2003-2007/2008). The Risk Factor Model included ten demographic variables: exposure to fluoridation in the municipal water supply, environmental smoke exposure, race, age, locale (metropolitan vs. rural), tobacco use, Body Mass Index, insurance status, sex, and sealant application. Multiple regression was used in a previous study to establish which significantly contributed to caries risk. Follow-up logistic regression ascertained the weight of contribution and odds ratios of the ten variables. Researchers in this study computed sensitivity, specificity, positive predictive value (PVP), negative predictive value (PVN), and prevalence across all six years of screening to assess the validity of the Risk Factor Model. Subjects' overall mean caries prevalence across all six years was 66%. Average sensitivity across all six years was 79%; average specificity was 81%; average PVP was 89% and average PVN was 67%. Overall, the Risk Factor Model provided a relatively constant, valid measure of caries that could be used in conjunction with a comprehensive risk assessment in population-based screenings by school nurses/nurse practitioners, health educators, and physicians to guide them in assessing potential future caries risk for use in prevention and referral practices.

Demographic models and IPCC climate projections predict the decline of an emperor penguin population.

PubMed

Jenouvrier, Stéphanie; Caswell, Hal; Barbraud, Christophe; Holland, Marika; Stroeve, Julienne; Weimerskirch, Henri

2009-02-10

Studies have reported important effects of recent climate change on Antarctic species, but there has been to our knowledge no attempt to explicitly link those results to forecasted population responses to climate change. Antarctic sea ice extent (SIE) is projected to shrink as concentrations of atmospheric greenhouse gases (GHGs) increase, and emperor penguins (Aptenodytes forsteri) are extremely sensitive to these changes because they use sea ice as a breeding, foraging and molting habitat. We project emperor penguin population responses to future sea ice changes, using a stochastic population model that combines a unique long-term demographic dataset (1962-2005) from a colony in Terre Adélie, Antarctica and projections of SIE from General Circulation Models (GCM) of Earth's climate included in the most recent Intergovernmental Panel on Climate Change (IPCC) assessment report. We show that the increased frequency of warm events associated with projected decreases in SIE will reduce the population viability. The probability of quasi-extinction (a decline of 95% or more) is at least 36% by 2100. The median population size is projected to decline from approximately 6,000 to approximately 400 breeding pairs over this period. To avoid extinction, emperor penguins will have to adapt, migrate or change the timing of their growth stages. However, given the future projected increases in GHGs and its effect on Antarctic climate, evolution or migration seem unlikely for such long lived species at the remote southern end of the Earth.

Characterizing the impact of projected changes in climate and ...

EPA Pesticide Factsheets

The impact of climate change on human and environmental health is of critical concern. Population exposures to air pollutants both indoors and outdoors are influenced by a wide range of air quality, meteorological, behavioral, and housing-related factors, many of which are also impacted by climate change. An integrated methodology for modeling changes in human exposures to tropospheric ozone (O3) owing to potential future changes in climate and demographics was implemented by linking existing modeling tools for climate, weather, air quality, population distribution, and human exposure. Human exposure results from the Air Pollutants Exposure Model (APEX) for 12 US cities show differences in daily maximum 8-h (DM8H) exposure patterns and levels by sex, age, and city for all scenarios. When climate is held constant and population demographics are varied, minimal difference in O3 exposures is predicted even with the most extreme demographic change scenario. In contrast, when population is held constant, we see evidence of substantial changes in O3 exposure for the most extreme change in climate. Similarly, we see increases in the percentage of the population in each city with at least one O3 exposure exceedance above 60 p.p.b and 70 p.p.b thresholds for future changes in climate. For these climate and population scenarios, the impact of projected changes in climate and air quality on human exposure to O3 are much larger than the impacts of changing demographics.

Demographic models and IPCC climate projections predict the decline of an emperor penguin population

PubMed Central

Jenouvrier, Stéphanie; Caswell, Hal; Barbraud, Christophe; Holland, Marika; Strœve, Julienne; Weimerskirch, Henri

2009-01-01

Studies have reported important effects of recent climate change on Antarctic species, but there has been to our knowledge no attempt to explicitly link those results to forecasted population responses to climate change. Antarctic sea ice extent (SIE) is projected to shrink as concentrations of atmospheric greenhouse gases (GHGs) increase, and emperor penguins (Aptenodytes forsteri) are extremely sensitive to these changes because they use sea ice as a breeding, foraging and molting habitat. We project emperor penguin population responses to future sea ice changes, using a stochastic population model that combines a unique long-term demographic dataset (1962–2005) from a colony in Terre Adélie, Antarctica and projections of SIE from General Circulation Models (GCM) of Earth's climate included in the most recent Intergovernmental Panel on Climate Change (IPCC) assessment report. We show that the increased frequency of warm events associated with projected decreases in SIE will reduce the population viability. The probability of quasi-extinction (a decline of 95% or more) is at least 36% by 2100. The median population size is projected to decline from ≈6,000 to ≈400 breeding pairs over this period. To avoid extinction, emperor penguins will have to adapt, migrate or change the timing of their growth stages. However, given the future projected increases in GHGs and its effect on Antarctic climate, evolution or migration seem unlikely for such long lived species at the remote southern end of the Earth. PMID:19171908

Species distributions models in wildlife planning: agricultural policy and wildlife management in the great plains

USGS Publications Warehouse

Fontaine, Joseph J.; Jorgensen, Christopher; Stuber, Erica F.; Gruber, Lutz F.; Bishop, Andrew A.; Lusk, Jeffrey J.; Zach, Eric S.; Decker, Karie L.

2017-01-01

We know economic and social policy has implications for ecosystems at large, but the consequences for a given geographic area or specific wildlife population are more difficult to conceptualize and communicate. Species distribution models, which extrapolate species-habitat relationships across ecological scales, are capable of predicting population changes in distribution and abundance in response to management and policy, and thus, are an ideal means for facilitating proactive management within a larger policy framework. To illustrate the capabilities of species distribution modeling in scenario planning for wildlife populations, we projected an existing distribution model for ring-necked pheasants (Phasianus colchicus) onto a series of alternative future landscape scenarios for Nebraska, USA. Based on our scenarios, we qualitatively and quantitatively estimated the effects of agricultural policy decisions on pheasant populations across Nebraska, in specific management regions, and at wildlife management areas. 

Impact of transient climate change upon Grouse population dynamics in the Italian Alps

NASA Astrophysics Data System (ADS)

Pirovano, Andrea; Bocchiola, Daniele

2010-05-01

Understanding the effect of short to medium term weather condition, and of transient global warming upon wildlife species life history is essential to predict the demographic consequences therein, and possibly develop adaptation strategies, especially in game species, where hunting mortality may play an important role in population dynamics. We carried out a preliminary investigation of observed impact of weather variables upon population dynamics indexes of three alpine Grouse species (i.e. Rock Ptarmigan, Lagopus Mutus, Black Grouse, Tetrao Tetrix, Rock Partridge, Alectoris Graeca), nested within central Italian Alps, based upon 15 years (1995-2009) of available censuses data, provided by the Sondrio Province authority. We used a set of climate variables already highlighted within recent literature for carrying considerable bearing on Grouse population dynamics, including e.g. temperature at hatching time and during winter, snow cover at nesting, and precipitation during nursing period. We then developed models of Grouses' population dynamics by explicitly driving population change according to their dependence upon the significant weather variables and population density and we evaluated objective indexes to assess the so obtained predictive power. Eventually, we develop projection of future local climate, based upon locally derived trends, and upon projections from GCMs (A2 IPCC storyline) already validated for the area, to project forward in time (until 2100 or so) the significant climatic variables, which we then use to force population dynamics models of the target species. The projected patterns obtained through this exercise are discussed and compared against those expected under stationary climate conditions at present, and preliminary conclusions are drawn.

Range shifts or extinction? Ancient DNA and distribution modelling reveal past and future responses to climate warming in cold-adapted birds.

PubMed

Lagerholm, Vendela K; Sandoval-Castellanos, Edson; Vaniscotte, Amélie; Potapova, Olga R; Tomek, Teresa; Bochenski, Zbigniew M; Shepherd, Paul; Barton, Nick; Van Dyck, Marie-Claire; Miller, Rebecca; Höglund, Jacob; Yoccoz, Nigel G; Dalén, Love; Stewart, John R

2017-04-01

Global warming is predicted to cause substantial habitat rearrangements, with the most severe effects expected to occur in high-latitude biomes. However, one major uncertainty is whether species will be able to shift their ranges to keep pace with climate-driven environmental changes. Many recent studies on mammals have shown that past range contractions have been associated with local extinctions rather than survival by habitat tracking. Here, we have used an interdisciplinary approach that combines ancient DNA techniques, coalescent simulations and species distribution modelling, to investigate how two common cold-adapted bird species, willow and rock ptarmigan (Lagopus lagopus and Lagopus muta), respond to long-term climate warming. Contrary to previous findings in mammals, we demonstrate a genetic continuity in Europe over the last 20 millennia. Results from back-casted species distribution models suggest that this continuity may have been facilitated by uninterrupted habitat availability and potentially also the greater dispersal ability of birds. However, our predictions show that in the near future, some isolated regions will have little suitable habitat left, implying a future decrease in local populations at a scale unprecedented since the last glacial maximum. © 2016 John Wiley & Sons Ltd.

Spatial Prediction of Coxiella burnetii Outbreak Exposure via Notified Case Counts in a Dose-Response Model.

PubMed

Brooke, Russell J; Kretzschmar, Mirjam E E; Hackert, Volker; Hoebe, Christian J P A; Teunis, Peter F M; Waller, Lance A

2017-01-01

We develop a novel approach to study an outbreak of Q fever in 2009 in the Netherlands by combining a human dose-response model with geostatistics prediction to relate probability of infection and associated probability of illness to an effective dose of Coxiella burnetii. The spatial distribution of the 220 notified cases in the at-risk population are translated into a smooth spatial field of dose. Based on these symptomatic cases, the dose-response model predicts a median of 611 asymptomatic infections (95% range: 410, 1,084) for the 220 reported symptomatic cases in the at-risk population; 2.78 (95% range: 1.86, 4.93) asymptomatic infections for each reported case. The low attack rates observed during the outbreak range from (Equation is included in full-text article.)to (Equation is included in full-text article.). The estimated peak levels of exposure extend to the north-east from the point source with an increasing proportion of asymptomatic infections further from the source. Our work combines established methodology from model-based geostatistics and dose-response modeling allowing for a novel approach to study outbreaks. Unobserved infections and the spatially varying effective dose can be predicted using the flexible framework without assuming any underlying spatial structure of the outbreak process. Such predictions are important for targeting interventions during an outbreak, estimating future disease burden, and determining acceptable risk levels.

Head Trauma with or without Mild Brain Injury Increases the Risk of Future Traumatic Death: A Controlled Prospective 15-Year Follow-Up Study.

PubMed

Vaaramo, Kalle; Puljula, Jussi; Tetri, Sami; Juvela, Seppo; Hillbom, Matti

2015-10-15

Patients who have recovered from traumatic brain injury (TBI) show an increased risk of premature death. To investigate long-term mortality rates in a population admitted to the hospital for head injury (HI), we conducted a population-based prospective case-control, record-linkage study, All subjects who were living in Northern Ostrobothnia, and who were admitted to Oulu University Hospital in 1999 because of HI (n=737), and 2196 controls matched by age, gender, and residence randomly drawn from the population of Northern Ostrobothnia were included. Death rate and causes of death in HI subjects during 15 years of follow-up was compared with the general population controls. The crude mortality rates were 56.9, 18.6, and 23.8% for subjects having moderate-to-severe traumatic brain injury (TBI), mild TBI, and head injury without TBI, respectively. The corresponding approximate annual mortality rates were 6.7%, 1.4%, and 1.9%. All types of index HI predicted a significant risk of traumatic death in the future. Subjects who had HI without TBI had an increased risk of both death from all causes (hazard ratio 2.00; 95% confidence interval 1.57-2.55) and intentional or unintentional traumatic death (4.01, 2.20-7.30), compared with controls. The main founding was that even HI without TBI carries an increased risk of future traumatic death. The reason for this remains unknown and further studies are needed. To prevent such premature deaths, post-traumatic therapy should include an interview focusing on lifestyle factors.

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach—A Case Study for the City of Wuhan in China

PubMed Central

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-01-01

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study—simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan. PMID:28617348

The Theory of Planned Behavior as a Predictor of Growth in Risky College Drinking*

PubMed Central

Collins, Susan E.; Witkiewitz, Katie; Larimer, Mary E.

2011-01-01

Objective: This study tested the Theory of Planned Behavior (TPB) as a predictor of growth in risky college drinking over a 3-month period. As predicted by the TPB model, it was hypothesized that attitudes, subjective norms, and perceived behavioral control would predict intention to engage in risky drinking, which would in turn predict growth in future risky drinking. Method: Participants were 837 college drinkers (64.2% female) who were randomly selected from two U.S. West Coast universities to participate in a larger study on college drinking norms. This study used latent growth analyses to test the ability of the TPB to predict baseline levels of as well as linear and quadratic growth in risky college drinking (i.e., heavy episodic drinking and peak drinking quantity). Results: Chi-square tests and fit indices indicated close fit for the final structural models. Self-efficacy, attitudes, and subjective norms significantly predicted baseline intention, which in turn predicted future heavy episodic drinking. Self-efficacy and attitudes were also related to intention in the model of peak drinking; however, subjective norms were not a significant predictor of intention in the peak drinking model. Mediation analyses showed that intention to engage in risky drinking mediated the effects of self-efficacy and attitudes on growth in risky drinking. Conclusions: Findings supported the TPB in predicting risky college drinking. Although the current findings should be replicated before definitive conclusions are drawn, results suggest that feedback on self-efficacy, attitudes, and intentions to engage in risky drinking may be a helpful addition to personalized feedback interventions for this population. PMID:21388605

The macular degeneration and aging study: Design and research protocol of a randomized trial for a psychosocial intervention with macular degeneration patients.

PubMed

Sörensen, Silvia; White, Katherine; Mak, Wingyun; Zanibbi, Katherine; Tang, Wan; O'Hearn, Amanda; Hegel, Mark T

2015-05-01

Age-related Macular Degeneration (AMD) is the leading cause of irreversible and predictable blindness among older adults with serious physical and mental health consequences. Visual impairment is associated with negative future outlook and depression and has serious consequences for older adults' quality of life and, by way of depression, on long-term survival. Psychosocial interventions have the potential to alleviate and prevent depression symptoms among older AMD patients. We describe the protocol of the Macular Degeneration and Aging Study, a randomized clinical trial of a psychosocial Preventive Problem-Solving Intervention. The intervention is aimed at enhancing well-being and future planning among older adults with macular degeneration by increasing preparation for future care. Adequate randomization and therapeutic fidelity were achieved. Current retention rates were acceptable, given the vulnerability of the population. Acceptability (adherence and satisfaction) was high. Given the high public health significance and impact on quality of life among older adults with vision loss, this protocol contributes a valid test of a promising intervention for maintaining mental and physical health in this population. Copyright © 2015 Elsevier Inc. All rights reserved.

Modelling drivers and distribution of lead and zinc concentrations in soils of an urban catchment (Sydney estuary, Australia).

PubMed

Johnson, L E; Bishop, T F A; Birch, G F

2017-11-15

The human population is increasing globally and land use is changing to accommodate for this growth. Soils within urban areas require closer attention as the higher population density increases the chance of human exposure to urban contaminants. One such example of an urban area undergoing an increase in population density is Sydney, Australia. The city also possesses a notable history of intense industrial activity. By integrating multiple soil surveys and covariates into a linear mixed model, it was possible to determine the main drivers and map the distribution of lead and zinc concentrations within the Sydney estuary catchment. The main drivers as derived from the model included elevation, distance to main roads, main road type, soil landscape, population density (lead only) and land use (zinc only). Lead concentrations predicted using the model exceeded the established guideline value of 300mgkg -1 over a large portion of the study area with concentrations exceeding 1000mgkg -1 in the south of the catchment. Predicted zinc did not exceed the established guideline value of 7400mgkg -1 ; however concentrations were higher to the south and west of the study area. Unlike many other studies we considered the prediction uncertainty when assessing the contamination risk. Although the predictions indicate contamination over a large area, the broadness of the prediction intervals suggests that in many of these areas we cannot be sure that the site is contaminated. More samples are required to determine the contaminant distribution with greater precision, especially in residential areas where contamination was highest. Managing sources and addressing areas of elevated lead and zinc concentrations in urban areas has the potential to reduce the impact of past human activities and improve the urban environment of the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Population-level genetic variation and climate change in a biodiversity hotspot

PubMed Central

2017-01-01

Introduction Estimated future climate scenarios can be used to predict where hotspots of endemism may occur over the next century, but life history, ecological and genetic traits will be important in informing the varying responses within myriad taxa. Essential to predicting the consequences of climate change to individual species will be an understanding of the factors that drive genetic structure within and among populations. Here, I review the factors that influence the genetic structure of plant species in California, but are applicable elsewhere; existing levels of genetic variation, life history and ecological characteristics will affect the ability of an individual taxon to persist in the presence of anthropogenic change. Factors influencing the distribution of genetic variation Persistence in the face of climate change is likely determined by life history characteristics: dispersal ability, generation time, reproductive ability, degree of habitat specialization, plant–insect interactions, existing genetic diversity and availability of habitat or migration corridors. Existing levels of genetic diversity in plant populations vary based on a number of evolutionary scenarios that include endemism, expansion since the last glacial maximum, breeding system and current range sizes. Regional priorities and examples A number of well-documented examples are provided from the California Floristic Province. Some predictions can be made for the responses of plant taxa to rapid environmental changes based on geographic position, evolutionary history, existing genetic variation, and ecological amplitude. Conclusions, Solutions and Recommendations The prediction of how species will respond to climate change will require a synthesis drawing from population genetics, geography, palaeontology and ecology. The important integration of the historical factors that have shaped the distribution and existing genetic structure of California’s plant taxa will enable us to predict and prioritize the conservation of species and areas most likely to be impacted by rapid climate change, human disturbance and invasive species. PMID:28069633

Population-level genetic variation and climate change in a biodiversity hotspot.

PubMed

Schierenbeck, Kristina A

2017-01-01

Estimated future climate scenarios can be used to predict where hotspots of endemism may occur over the next century, but life history, ecological and genetic traits will be important in informing the varying responses within myriad taxa. Essential to predicting the consequences of climate change to individual species will be an understanding of the factors that drive genetic structure within and among populations. Here, I review the factors that influence the genetic structure of plant species in California, but are applicable elsewhere; existing levels of genetic variation, life history and ecological characteristics will affect the ability of an individual taxon to persist in the presence of anthropogenic change. Persistence in the face of climate change is likely determined by life history characteristics: dispersal ability, generation time, reproductive ability, degree of habitat specialization, plant-insect interactions, existing genetic diversity and availability of habitat or migration corridors. Existing levels of genetic diversity in plant populations vary based on a number of evolutionary scenarios that include endemism, expansion since the last glacial maximum, breeding system and current range sizes. A number of well-documented examples are provided from the California Floristic Province. Some predictions can be made for the responses of plant taxa to rapid environmental changes based on geographic position, evolutionary history, existing genetic variation, and ecological amplitude. The prediction of how species will respond to climate change will require a synthesis drawing from population genetics, geography, palaeontology and ecology. The important integration of the historical factors that have shaped the distribution and existing genetic structure of California's plant taxa will enable us to predict and prioritize the conservation of species and areas most likely to be impacted by rapid climate change, human disturbance and invasive species. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Information about the US racial demographic shift triggers concerns about anti-White discrimination among the prospective White “minority”

PubMed Central

Richeson, Jennifer A.

2017-01-01

The United States is undergoing a demographic shift in which White Americans are predicted to comprise less than 50% of the US population by mid-century. The present research examines how exposure to information about this racial shift affects perceptions of the extent to which different racial groups face discrimination. In four experiments, making the growing national racial diversity salient led White Americans to predict that Whites will face increasing discrimination in the future, compared with control information. Conversely, regardless of experimental condition, Whites estimated that discrimination against various racial minority groups will decline. Explorations of several psychological mechanisms potentially underlying the effect of the racial shift information on perceived anti-White discrimination suggested a mediating role of concerns about American culture fundamentally changing. Taken together, these findings suggest that reports about the changing national demographics enhance concerns among Whites that they will be the victims of racial discrimination in the future. PMID:28953971

Information about the US racial demographic shift triggers concerns about anti-White discrimination among the prospective White "minority".

PubMed

Craig, Maureen A; Richeson, Jennifer A

2017-01-01

The United States is undergoing a demographic shift in which White Americans are predicted to comprise less than 50% of the US population by mid-century. The present research examines how exposure to information about this racial shift affects perceptions of the extent to which different racial groups face discrimination. In four experiments, making the growing national racial diversity salient led White Americans to predict that Whites will face increasing discrimination in the future, compared with control information. Conversely, regardless of experimental condition, Whites estimated that discrimination against various racial minority groups will decline. Explorations of several psychological mechanisms potentially underlying the effect of the racial shift information on perceived anti-White discrimination suggested a mediating role of concerns about American culture fundamentally changing. Taken together, these findings suggest that reports about the changing national demographics enhance concerns among Whites that they will be the victims of racial discrimination in the future.

The future of Arctic benthos: Expansion, invasion, and biodiversity

NASA Astrophysics Data System (ADS)

Renaud, Paul E.; Sejr, Mikael K.; Bluhm, Bodil A.; Sirenko, Boris; Ellingsen, Ingrid H.

2015-12-01

One of the logical predictions for a future Arctic characterized by warmer waters and reduced sea-ice is that new taxa will expand or invade Arctic seafloor habitats. Specific predictions regarding where this will occur and which taxa are most likely to become established or excluded are lacking, however. We synthesize recent studies and conduct new analyses in the context of climate forecasts and a paleontological perspective to make concrete predictions as to relevant mechanisms, regions, and functional traits contributing to future biodiversity changes. Historically, a warmer Arctic is more readily invaded or transited by boreal taxa than it is during cold periods. Oceanography of an ice-free Arctic Ocean, combined with life-history traits of invading taxa and availability of suitable habitat, determine expansion success. It is difficult to generalize as to which taxonomic groups or locations are likely to experience expansion, however, since species-specific, and perhaps population-specific autecologies, will determine success or failure. Several examples of expansion into the Arctic have been noted, and along with the results from the relatively few Arctic biological time-series suggest inflow shelves (Barents and Chukchi Seas), as well as West Greenland and the western Kara Sea, are most likely locations for expansion. Apparent temperature thresholds were identified for characteristic Arctic and boreal benthic fauna suggesting strong potential for range constrictions of Arctic, and expansions of boreal, fauna in the near future. Increasing human activities in the region could speed introductions of boreal fauna and reduce the value of a planktonic dispersal stage. Finally, shelf regions are likely to experience a greater impact, and also one with greater potential consequences, than the deep Arctic basin. Future research strategies should focus on monitoring as well as compiling basic physiological and life-history information of Arctic and boreal taxa, and integrate that with projections of human activities and likely ecosystem consequences to facilitate development of management strategies now and in the future.

Mammographic density and breast cancer risk: current understanding and future prospects

PubMed Central

2011-01-01

Variations in percent mammographic density (PMD) reflect variations in the amounts of collagen and number of epithelial and non-epithelial cells in the breast. Extensive PMD is associated with a markedly increased risk of invasive breast cancer. The PMD phenotype is important in the context of breast cancer prevention because extensive PMD is common in the population, is strongly associated with risk of the disease, and, unlike most breast cancer risk factors, can be changed. Work now in progress makes it likely that measurement of PMD will be improved in the near future and that understanding of the genetics and biological basis of the association of PMD with breast cancer risk will also improve. Future prospects for the application of PMD include mammographic screening, risk prediction in individuals, breast cancer prevention research, and clinical decision making. PMID:22114898

Body composition indices and predicted cardiovascular disease risk profile among urban dwellers in Malaysia.

PubMed

Su, Tin Tin; Amiri, Mohammadreza; Mohd Hairi, Farizah; Thangiah, Nithiah; Dahlui, Maznah; Majid, Hazreen Abdul

2015-01-01

This study aims to compare various body composition indices and their association with a predicted cardiovascular disease (CVD) risk profile in an urban population in Kuala Lumpur, Malaysia. A cross-sectional survey was conducted in metropolitan Kuala Lumpur, Malaysia, in 2012. Households were selected using a simple random-sampling method, and adult members were invited for medical screening. The Framingham Risk Scoring algorithm was used to predict CVD risk, which was then analyzed in association with body composition measurements, including waist circumference, waist-hip ratio, waist-height ratio, body fat percentage, and body mass index. Altogether, 882 individuals were included in our analyses. Indices that included waist-related measurements had the strongest association with CVD risk in both genders. After adjusting for demographic and socioeconomic variables, waist-related measurements retained the strongest correlations with predicted CVD risk in males. However, body mass index, waist-height ratio, and waist circumference had the strongest correlation with CVD risk in females. The waist-related indicators of abdominal obesity are important components of CVD risk profiles. As waist-related parameters can quickly and easily be measured, they should be routinely obtained in primary care settings and population health screens in order to assess future CVD risk profiles and design appropriate interventions.

Body Composition Indices and Predicted Cardiovascular Disease Risk Profile among Urban Dwellers in Malaysia

PubMed Central

Su, Tin Tin; Amiri, Mohammadreza; Mohd Hairi, Farizah; Thangiah, Nithiah; Dahlui, Maznah; Majid, Hazreen Abdul

2015-01-01

Objectives. This study aims to compare various body composition indices and their association with a predicted cardiovascular disease (CVD) risk profile in an urban population in Kuala Lumpur, Malaysia. Methods. A cross-sectional survey was conducted in metropolitan Kuala Lumpur, Malaysia, in 2012. Households were selected using a simple random-sampling method, and adult members were invited for medical screening. The Framingham Risk Scoring algorithm was used to predict CVD risk, which was then analyzed in association with body composition measurements, including waist circumference, waist-hip ratio, waist-height ratio, body fat percentage, and body mass index. Results. Altogether, 882 individuals were included in our analyses. Indices that included waist-related measurements had the strongest association with CVD risk in both genders. After adjusting for demographic and socioeconomic variables, waist-related measurements retained the strongest correlations with predicted CVD risk in males. However, body mass index, waist-height ratio, and waist circumference had the strongest correlation with CVD risk in females. Conclusions. The waist-related indicators of abdominal obesity are important components of CVD risk profiles. As waist-related parameters can quickly and easily be measured, they should be routinely obtained in primary care settings and population health screens in order to assess future CVD risk profiles and design appropriate interventions. PMID:25710002

Predicting performance and injury resilience from movement quality and fitness scores in a basketball team over 2 years.

PubMed

McGill, Stuart M; Andersen, Jordan T; Horne, Arthur D

2012-07-01

The purpose of this study was to see if specific tests of fitness and movement quality could predict injury resilience and performance in a team of basketball players over 2 years (2 playing seasons). It was hypothesized that, in a basketball population, movement and fitness scores would predict performance scores and that movement and fitness scores would predict injury resilience. A basketball team from a major American university (N = 14) served as the test population in this longitudinal trial. Variables linked to fitness, movement ability, speed, strength, and agility were measured together with some National Basketball Association (NBA) combine tests. Dependent variables of performance indicators (such as games and minutes played, points scored, assists, rebounds, steal, and blocks) and injury reports were tracked for the subsequent 2 years. Results showed that better performance was linked with having a stiffer torso, more mobile hips, weaker left grip strength, and a longer standing long jump, to name a few. Of the 3 NBA combine tests administered here, only a faster lane agility time had significant links with performance. Some movement qualities and torso endurance were not linked. No patterns with injury emerged. These observations have implications for preseason testing and subsequent training programs in an attempt to reduce future injury and enhance playing performance.

Adaptive potential of northernmost tree populations to climate change, with emphasis on Scots pine (Pinus sylvestris L.).

PubMed

Savolainen, Outi; Kujala, Sonja T; Sokol, Catherina; Pyhäjärvi, Tanja; Avia, Komlan; Knürr, Timo; Kärkkäinen, Katri; Hicks, Sheila

2011-01-01

The adaptive potential of the northernmost Pinus sylvestris L. (and other northern tree) populations is considered by examining first the current patterns of quantitative genetic adaptive traits, which show high population differentiation and clines. We then consider the postglacial history of the populations using both paleobiological and genetic data. The current patterns of diversity at nuclear genes suggest that the traces of admixture are mostly visible in mitochondrial DNA variation patterns. There is little evidence of increased diversity due to admixture between an eastern and western colonization lineage, but no signal of reduced diversity (due to sequential bottlenecks) either. Quantitative trait variation in the north is not associated with the colonizing lineages. The current clines arose rapidly and may be based on standing genetic variation. The initial phenotypic response of Scots pine in the north is predicted to be increased survival and growth. The genetic responses are examined based on quantitative genetic predictions of sustained selection response and compared with earlier simulation results that have aimed at more ecological realism. The phenotypic responses of increased growth and survival reduce the opportunity for selection and delay the evolutionary responses. The lengthening of the thermal growing period also causes selection on the critical photoperiod in the different populations. Future studies should aim at including multiple ecological and genetic factors in evaluating potential responses.

Past and estimated future impact of invasive alien mammals on insular threatened vertebrate populations

PubMed Central

McCreless, Erin E.; Huff, David D.; Croll, Donald A.; Tershy, Bernie R.; Spatz, Dena R.; Holmes, Nick D.; Butchart, Stuart H. M.; Wilcox, Chris

2016-01-01

Invasive mammals on islands pose severe, ongoing threats to global biodiversity. However, the severity of threats from different mammals, and the role of interacting biotic and abiotic factors in driving extinctions, remain poorly understood at a global scale. Here we model global extirpation patterns for island populations of threatened and extinct vertebrates. Extirpations are driven by interacting factors including invasive rats, cats, pigs, mustelids and mongooses, native species taxonomic class and volancy, island size, precipitation and human presence. We show that controlling or eradicating the relevant invasive mammals could prevent 41–75% of predicted future extirpations. The magnitude of benefits varies across species and environments; for example, managing invasive mammals on small, dry islands could halve the extirpation risk for highly threatened birds and mammals, while doing so on large, wet islands may have little benefit. Our results provide quantitative estimates of conservation benefits and, when combined with costs in a return-on-investment framework, can guide efficient conservation strategies. PMID:27535095

Atmospheric dispersion modelling over complex terrain at small scale

NASA Astrophysics Data System (ADS)

Nosek, S.; Janour, Z.; Kukacka, L.; Jurcakova, K.; Kellnerova, R.; Gulikova, E.

2014-03-01

Previous study concerned of qualitative modelling neutrally stratified flow over open-cut coal mine and important surrounding topography at meso-scale (1:9000) revealed an important area for quantitative modelling of atmospheric dispersion at small-scale (1:3300). The selected area includes a necessary part of the coal mine topography with respect to its future expansion and surrounding populated areas. At this small-scale simultaneous measurement of velocity components and concentrations in specified points of vertical and horizontal planes were performed by two-dimensional Laser Doppler Anemometry (LDA) and Fast-Response Flame Ionization Detector (FFID), respectively. The impact of the complex terrain on passive pollutant dispersion with respect to the prevailing wind direction was observed and the prediction of the air quality at populated areas is discussed. The measured data will be used for comparison with another model taking into account the future coal mine transformation. Thus, the impact of coal mine transformation on pollutant dispersion can be observed.

Sperm competition risk generates phenotypic plasticity in ovum fertilizability

PubMed Central

Firman, Renée C.; Simmons, Leigh W.

2013-01-01

Theory predicts that sperm competition will generate sexual conflict that favours increased ovum defences against polyspermy. A recent study on house mice has shown that ovum resistance to fertilization coevolves in response to increased sperm fertilizing capacity. However, the capacity for the female gamete to adjust its fertilizability as a strategic response to sperm competition risk has never, to our knowledge, been studied. We sourced house mice (Mus domesticus) from natural populations that differ in the level of sperm competition and sperm fertilizing capacity, and manipulated the social experience of females during their sexual development to simulate conditions of either a future ‘risk’ or ‘no risk’ of sperm competition. Consistent with coevolutionary predictions, we found lower fertilization rates in ova produced by females from a high sperm competition population compared with ova from a low sperm competition population, indicating that these populations are divergent in the fertilizability of their ova. More importantly, females exposed to a ‘risk’ of sperm competition produced ova that had greater resistance to fertilization than ova produced by females reared in an environment with ‘no risk’. Consequently, we show that variation in sperm competition risk during development generates phenotypic plasticity in ova fertilizability, which allows females to prepare for prevailing conditions during their reproductive life. PMID:24132308

Sperm competition risk generates phenotypic plasticity in ovum fertilizability.

PubMed

Firman, Renée C; Simmons, Leigh W

2013-12-07

Theory predicts that sperm competition will generate sexual conflict that favours increased ovum defences against polyspermy. A recent study on house mice has shown that ovum resistance to fertilization coevolves in response to increased sperm fertilizing capacity. However, the capacity for the female gamete to adjust its fertilizability as a strategic response to sperm competition risk has never, to our knowledge, been studied. We sourced house mice (Mus domesticus) from natural populations that differ in the level of sperm competition and sperm fertilizing capacity, and manipulated the social experience of females during their sexual development to simulate conditions of either a future 'risk' or 'no risk' of sperm competition. Consistent with coevolutionary predictions, we found lower fertilization rates in ova produced by females from a high sperm competition population compared with ova from a low sperm competition population, indicating that these populations are divergent in the fertilizability of their ova. More importantly, females exposed to a 'risk' of sperm competition produced ova that had greater resistance to fertilization than ova produced by females reared in an environment with 'no risk'. Consequently, we show that variation in sperm competition risk during development generates phenotypic plasticity in ova fertilizability, which allows females to prepare for prevailing conditions during their reproductive life.

Support for viral persistence in bats from age-specific serology and models of maternal immunity.

PubMed

Peel, Alison J; Baker, Kate S; Hayman, David T S; Broder, Christopher C; Cunningham, Andrew A; Fooks, Anthony R; Garnier, Romain; Wood, James L N; Restif, Olivier

2018-03-01

Spatiotemporally-localised prediction of virus emergence from wildlife requires focused studies on the ecology and immunology of reservoir hosts in their native habitat. Reliable predictions from mathematical models remain difficult in most systems due to a dearth of appropriate empirical data. Our goal was to study the circulation and immune dynamics of zoonotic viruses in bat populations and investigate the effects of maternally-derived and acquired immunity on viral persistence. Using rare age-specific serological data from wild-caught Eidolon helvum fruit bats as a case study, we estimated viral transmission parameters for a stochastic infection model. We estimated mean durations of around 6 months for maternally-derived immunity to Lagos bat virus and African henipavirus, whereas acquired immunity was long-lasting (Lagos bat virus: mean 12 years, henipavirus: mean 4 years). In the presence of a seasonal birth pulse, the effect of maternally-derived immunity on virus persistence within modelled bat populations was highly dependent on transmission characteristics. To explain previous reports of viral persistence within small natural and captive E. helvum populations, we hypothesise that some bats must experience prolonged infectious periods or within-host latency. By further elucidating plausible mechanisms of virus persistence in bat populations, we contribute to guidance of future field studies.

Environmental effects on the structure of the G-matrix.

PubMed

Wood, Corlett W; Brodie, Edmund D

2015-11-01

Genetic correlations between traits determine the multivariate response to selection in the short term, and thereby play a causal role in evolutionary change. Although individual studies have documented environmentally induced changes in genetic correlations, the nature and extent of environmental effects on multivariate genetic architecture across species and environments remain largely uncharacterized. We reviewed the literature for estimates of the genetic variance-covariance (G) matrix in multiple environments, and compared differences in G between environments to the divergence in G between conspecific populations (measured in a common garden). We found that the predicted evolutionary trajectory differed as strongly between environments as it did between populations. Between-environment differences in the underlying structure of G (total genetic variance and the relative magnitude and orientation of genetic correlations) were equal to or greater than between-population differences. Neither environmental novelty, nor the difference in mean phenotype predicted these differences in G. Our results suggest that environmental effects on multivariate genetic architecture may be comparable to the divergence that accumulates over dozens or hundreds of generations between populations. We outline avenues of future research to address the limitations of existing data and characterize the extent to which lability in genetic correlations shapes evolution in changing environments. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

A new approach on seismic mortality estimations based on average population density

NASA Astrophysics Data System (ADS)

Zhu, Xiaoxin; Sun, Baiqing; Jin, Zhanyong

2016-12-01

This study examines a new methodology to predict the final seismic mortality from earthquakes in China. Most studies established the association between mortality estimation and seismic intensity without considering the population density. In China, however, the data are not always available, especially when it comes to the very urgent relief situation in the disaster. And the population density varies greatly from region to region. This motivates the development of empirical models that use historical death data to provide the path to analyze the death tolls for earthquakes. The present paper employs the average population density to predict the final death tolls in earthquakes using a case-based reasoning model from realistic perspective. To validate the forecasting results, historical data from 18 large-scale earthquakes occurred in China are used to estimate the seismic morality of each case. And a typical earthquake case occurred in the northwest of Sichuan Province is employed to demonstrate the estimation of final death toll. The strength of this paper is that it provides scientific methods with overall forecast errors lower than 20 %, and opens the door for conducting final death forecasts with a qualitative and quantitative approach. Limitations and future research are also analyzed and discussed in the conclusion.

Predictive Biomarkers of Gastroesophageal Reflux Disease and Barrett's Esophagus in World Trade Center Exposed Firefighters: a 15 Year Longitudinal Study.

PubMed

Haider, Syed H; Kwon, Sophia; Lam, Rachel; Lee, Audrey K; Caraher, Erin J; Crowley, George; Zhang, Liqun; Schwartz, Theresa M; Zeig-Owens, Rachel; Liu, Mengling; Prezant, David J; Nolan, Anna

2018-02-15

Gastroesophageal reflux disease (GERD) and Barrett's Esophagus (BE), which are prevalent in the World Trade Center (WTC) exposed and general populations, negatively impact quality of life and cost of healthcare. GERD, a risk factor of BE, is linked to obstructive airways disease (OAD). We aim to identify serum biomarkers of GERD/BE, and assess the respiratory and clinical phenotype of a longitudinal cohort of never-smoking, male, WTC-exposed rescue workers presenting with pulmonary symptoms. Biomarkers collected soon after WTC-exposure were evaluated in optimized predictive models of GERD/BE. In the WTC-exposed cohort, the prevalence of BE is at least 6 times higher than in the general population. GERD/BE cases had similar lung function, D LCO , bronchodilator response and long-acting β-agonist use compared to controls. In confounder-adjusted regression models, TNF-α ≥ 6 pg/mL predicted both GERD and BE. GERD was also predicted by C-peptide ≥ 360 pg/mL, while BE was predicted by fractalkine ≥ 250 pg/mL and IP-10 ≥ 290 pg/mL. Finally, participants with GERD had significantly increased use of short-acting β-agonist compared to controls. Overall, biomarkers sampled prior to GERD/BE presentation showed strong predictive abilities of disease development. This study frames future investigations to further our understanding of aerodigestive pathology due to particulate matter exposure.

A signature of dynamic biogeography: enclaves indicate past species replacement.

PubMed

Wielstra, B; Burke, T; Butlin, R K; Arntzen, J W

2017-12-13

Understanding how species have replaced each other in the past is important to predicting future species turnover. While past species replacement is difficult to detect after the fact, the process may be inferred from present-day distribution patterns. Species with abutting ranges sometimes show a characteristic distribution pattern, where a section of one species range is enveloped by that of the other. Such an enclave could indicate past species replacement: when a species is partly supplanted by a competitor, but a population endures locally while the invading species moves around and past it, an enclave forms. If the two species hybridize and backcross, the receding species is predicted to leave genetic traces within the expanding one under a scenario of species replacement. By screening dozens of genes in hybridizing crested newts, we uncover genetic remnants of the ancestral species, now inhabiting an enclave, in the range of the surrounding invading species. This independent genetic evidence supports the past distribution dynamics we predicted from the enclave. We suggest that enclaves provide a valuable tool in understanding historical species replacement, which is important because a major conservation concern arising from anthropogenic climate change is increased species replacement in the future. © 2017 The Authors.

A precision medicine approach for psychiatric disease based on repeated symptom scores.

PubMed

Fojo, Anthony T; Musliner, Katherine L; Zandi, Peter P; Zeger, Scott L

2017-12-01

For psychiatric diseases, rich information exists in the serial measurement of mental health symptom scores. We present a precision medicine framework for using the trajectories of multiple symptoms to make personalized predictions about future symptoms and related psychiatric events. Our approach fits a Bayesian hierarchical model that estimates a population-average trajectory for all symptoms and individual deviations from the average trajectory, then fits a second model that uses individual symptom trajectories to estimate the risk of experiencing an event. The fitted models are used to make clinically relevant predictions for new individuals. We demonstrate this approach on data from a study of antipsychotic therapy for schizophrenia, predicting future scores for positive, negative, and general symptoms, and the risk of treatment failure in 522 schizophrenic patients with observations over 8 weeks. While precision medicine has focused largely on genetic and molecular data, the complementary approach we present illustrates that innovative analytic methods for existing data can extend its reach more broadly. The systematic use of repeated measurements of psychiatric symptoms offers the promise of precision medicine in the field of mental health. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Population viability of Pediocactus bradyi (Cactaceae) in a changing climate.

PubMed

Shryock, Daniel F; Esque, Todd C; Hughes, Lee

2014-11-01

A key question concerns the vulnerability of desert species adapted to harsh, variable climates to future climate change. Evaluating this requires coupling long-term demographic models with information on past and projected future climates. We investigated climatic drivers of population growth using a 22-yr demographic model for Pediocactus bradyi, an endangered cactus in northern Arizona. We used a matrix model to calculate stochastic population growth rates (λs) and the relative influences of life-cycle transitions on population growth. Regression models linked population growth with climatic variability, while stochastic simulations were used to (1) understand how predicted increases in drought frequency and extreme precipitation would affect λs, and (2) quantify variability in λs based on temporal replication of data. Overall λs was below unity (0.961). Population growth was equally influenced by fecundity and survival and significantly correlated with increased annual precipitation and higher winter temperatures. Stochastic simulations increasing the probability of drought and extreme precipitation reduced λs, but less than simulations increasing the probability of drought alone. Simulations varying the temporal replication of data suggested 14 yr were required for accurate λs estimates. Pediocactus bradyi may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events. © 2014 Botanical Society of America, Inc.

Culture History and Population Heterogeneity as Determinants of Bacterial Adaptation: the Adaptomics of a Single Environmental Transition

PubMed Central

Ryall, Ben; Eydallin, Gustavo

2012-01-01

Summary: Diversity in adaptive responses is common within species and populations, especially when the heterogeneity of the frequently large populations found in environments is considered. By focusing on events in a single clonal population undergoing a single transition, we discuss how environmental cues and changes in growth rate initiate a multiplicity of adaptive pathways. Adaptation is a comprehensive process, and stochastic, regulatory, epigenetic, and mutational changes can contribute to fitness and overlap in timing and frequency. We identify culture history as a major determinant of both regulatory adaptations and microevolutionary change. Population history before a transition determines heterogeneities due to errors in translation, stochastic differences in regulation, the presence of aged, damaged, cheating, or dormant cells, and variations in intracellular metabolite or regulator concentrations. It matters whether bacteria come from dense, slow-growing, stressed, or structured states. Genotypic adaptations are history dependent due to variations in mutation supply, contingency gene changes, phase variation, lateral gene transfer, and genome amplifications. Phenotypic adaptations underpin genotypic changes in situations such as stress-induced mutagenesis or prophage induction or in biofilms to give a continuum of adaptive possibilities. Evolutionary selection additionally provides diverse adaptive outcomes in a single transition and generally does not result in single fitter types. The totality of heterogeneities in an adapting population increases the chance that at least some individuals meet immediate or future challenges. However, heterogeneity complicates the adaptomics of single transitions, and we propose that subpopulations will need to be integrated into future population biology and systems biology predictions of bacterial behavior. PMID:22933562

Long-Term Trends and Role of Climate in the Population Dynamics of Eurasian Reindeer

PubMed Central

Horstkotte, Tim; Kaarlejärvi, Elina; Sévêque, Anthony; Stammler, Florian; Olofsson, Johan; Forbes, Bruce C.; Moen, Jon

2016-01-01

Temperature is increasing in Arctic and sub-Arctic regions at a higher rate than anywhere else in the world. The frequency and nature of precipitation events are also predicted to change in the future. These changes in climate are expected, together with increasing human pressures, to have significant impacts on Arctic and sub-Arctic species and ecosystems. Due to the key role that reindeer play in those ecosystems, it is essential to understand how climate will affect the region’s most important species. Our study assesses the role of climate on the dynamics of fourteen Eurasian reindeer (Rangifer tarandus) populations, using for the first time data on reindeer abundance collected over a 70-year period, including both wild and semi-domesticated reindeer, and covering more than half of the species’ total range. We analyzed trends in population dynamics, investigated synchrony among population growth rates, and assessed the effects of climate on population growth rates. Trends in the population dynamics were remarkably heterogeneous. Synchrony was apparent only among some populations and was not correlated with distance among population ranges. Proxies of climate variability mostly failed to explain population growth rates and synchrony. For both wild and semi-domesticated populations, local weather, biotic pressures, loss of habitat and human disturbances appear to have been more important drivers of reindeer population dynamics than climate. In semi-domesticated populations, management strategies may have masked the effects of climate. Conservation efforts should aim to mitigate human disturbances, which could exacerbate the potentially negative effects of climate change on reindeer populations in the future. Special protection and support should be granted to those semi-domesticated populations that suffered the most because of the collapse of the Soviet Union, in order to protect the livelihood of indigenous peoples that depend on the species, and the multi-faceted role that reindeer exert in Arctic ecosystems. PMID:27362499

Long-Term Trends and Role of Climate in the Population Dynamics of Eurasian Reindeer.

PubMed

Uboni, Alessia; Horstkotte, Tim; Kaarlejärvi, Elina; Sévêque, Anthony; Stammler, Florian; Olofsson, Johan; Forbes, Bruce C; Moen, Jon

2016-01-01

Temperature is increasing in Arctic and sub-Arctic regions at a higher rate than anywhere else in the world. The frequency and nature of precipitation events are also predicted to change in the future. These changes in climate are expected, together with increasing human pressures, to have significant impacts on Arctic and sub-Arctic species and ecosystems. Due to the key role that reindeer play in those ecosystems, it is essential to understand how climate will affect the region's most important species. Our study assesses the role of climate on the dynamics of fourteen Eurasian reindeer (Rangifer tarandus) populations, using for the first time data on reindeer abundance collected over a 70-year period, including both wild and semi-domesticated reindeer, and covering more than half of the species' total range. We analyzed trends in population dynamics, investigated synchrony among population growth rates, and assessed the effects of climate on population growth rates. Trends in the population dynamics were remarkably heterogeneous. Synchrony was apparent only among some populations and was not correlated with distance among population ranges. Proxies of climate variability mostly failed to explain population growth rates and synchrony. For both wild and semi-domesticated populations, local weather, biotic pressures, loss of habitat and human disturbances appear to have been more important drivers of reindeer population dynamics than climate. In semi-domesticated populations, management strategies may have masked the effects of climate. Conservation efforts should aim to mitigate human disturbances, which could exacerbate the potentially negative effects of climate change on reindeer populations in the future. Special protection and support should be granted to those semi-domesticated populations that suffered the most because of the collapse of the Soviet Union, in order to protect the livelihood of indigenous peoples that depend on the species, and the multi-faceted role that reindeer exert in Arctic ecosystems.

A universal model for predicting human migration under climate change: examining future sea level rise in Bangladesh

NASA Astrophysics Data System (ADS)

Frankel Davis, Kyle; Bhattachan, Abinash; D’Odorico, Paolo; Suweis, Samir

2018-06-01

Climate change is expected to impact the habitability of many places around the world in significant and unprecedented ways in the coming decades. While previous studies have provided estimates of populations potentially exposed to various climate impacts, little work has been done to assess the number of people that may actually be displaced or where they will choose to go. Here we modify a diffusion-based model of human mobility in combination with population, geographic, and climatic data to estimate the sources, destinations, and flux of potential migrants as driven by sea level rise (SLR) in Bangladesh in the years 2050 and 2100. Using only maps of population and elevation, we predict that 0.9 million people (by year 2050) to 2.1 million people (by year 2100) could be displaced by direct inundation and that almost all of this movement will occur locally within the southern half of the country. We also find that destination locations should anticipate substantial additional demands on jobs (594 000), housing (197 000), and food (783 × 109 calories) by mid-century as a result of those displaced by SLR. By linking the sources of migrants displaced by SLR with their likely destinations, we demonstrate an effective approach for predicting climate-driven migrant flows, especially in data-limited settings.

Modernization is Associated with Intensive Breastfeeding Patterns in the Bolivian Amazon

PubMed Central

Veile, Amanda; Martin, Melanie; McAllister, Lisa

2014-01-01

For many traditional, non-industrialized populations, intensive and prolonged breastfeeding buffers infant health against poverty, poor sanitation, and limited health care. Due to novel influences on local economies, values, and beliefs, the traditional and largely beneficial breastfeeding patterns of such populations may be changing to the detriment of infant health. To assess if and why such changes are occurring in a traditional breastfeeding population, we document breastfeeding patterns in the Bolivian Tsimane, a forager-horticulturalist population in the early stages of modernization. Three predictions are developed and tested to evaluate the general hypothesis that modernizing influences encourage less intensive breastfeeding in the Tsimane: 1) Tsimane mothers in regions of higher infant mortality will practice more intensive BF; 2) Tsimane mothers who are located closer to a local market town will practice more intensive BF; and 3) Older Tsimane mothers will practice more intensive BF. Predictions were tested using a series of maternal interviews (from 2003-2011, n=215) and observations of mother-infant dyads (from 2002-2007, n=133). Tsimane breastfeeding patterns were generally intensive: 72% of mothers reported initiating BF within a few hours of birth, mean (± SD) age of CF introduction was 4.1±2.0 months, and mean (± SD) weaning age was 19.2±7.3 months. There was, however, intra-population variation in several dimensions of breastfeeding (initiation, frequency, duration, and complementary feeding). Contrary to our predictions, breastfeeding was most intensive in the most modernized Tsimane villages, and maternal age was not a significant predictor of breastfeeding patterns. Regional differences accounted for variation in most dimensions of breastfeeding (initiation, frequency, and complementary feeding). Future research should therefore identify constraints on breastfeeding in the less modernized Tsimane regions, and examine the formation of maternal beliefs regarding infant feeding. PMID:24444850

Separating direct and indirect effects of global change: a population dynamic modeling approach using readily available field data.

PubMed

Farrer, Emily C; Ashton, Isabel W; Knape, Jonas; Suding, Katharine N

2014-04-01

Two sources of complexity make predicting plant community response to global change particularly challenging. First, realistic global change scenarios involve multiple drivers of environmental change that can interact with one another to produce non-additive effects. Second, in addition to these direct effects, global change drivers can indirectly affect plants by modifying species interactions. In order to tackle both of these challenges, we propose a novel population modeling approach, requiring only measurements of abundance and climate over time. To demonstrate the applicability of this approach, we model population dynamics of eight abundant plant species in a multifactorial global change experiment in alpine tundra where we manipulated nitrogen, precipitation, and temperature over 7 years. We test whether indirect and interactive effects are important to population dynamics and whether explicitly incorporating species interactions can change predictions when models are forecast under future climate change scenarios. For three of the eight species, population dynamics were best explained by direct effect models, for one species neither direct nor indirect effects were important, and for the other four species indirect effects mattered. Overall, global change had negative effects on species population growth, although species responded to different global change drivers, and single-factor effects were slightly more common than interactive direct effects. When the fitted population dynamic models were extrapolated under changing climatic conditions to the end of the century, forecasts of community dynamics and diversity loss were largely similar using direct effect models that do not explicitly incorporate species interactions or best-fit models; however, inclusion of species interactions was important in refining the predictions for two of the species. The modeling approach proposed here is a powerful way of analyzing readily available datasets which should be added to our toolbox to tease apart complex drivers of global change. © 2013 John Wiley & Sons Ltd.

Variation in probability of first reproduction of Weddell seals.

PubMed

Hadley, Gillian L; Rotella, Jay J; Garrott, Robert A; Nichols, James D

2006-09-01

1. For many species, when to begin reproduction is an important life-history decision that varies by individual and can have substantial implications for lifetime reproductive success and fitness. 2. We estimated age-specific probabilities of first-time breeding and modelled variation in these rates to determine age at first reproduction and understand why it varies in a population of Weddell seals in Erebus Bay, Antarctica. We used multistate mark-recapture modelling methods and encounter histories of 4965 known-age female seals to test predictions about age-related variation in probability of first reproduction and the effects of annual variation, cohort and population density. 3. Mean age at first reproduction in this southerly located study population (7.62 years of age, SD=1.71) was greater than age at first reproduction for a Weddell seal population at a more northerly and typical latitude for breeding Weddell seals (mean=4-5 years of age). This difference suggests that age at first reproduction may be influenced by whether a population inhabits the core or periphery of its range. 4. Age at first reproduction varied from 4 to 14 years, but there was no age by which all seals recruited to the breeding population, suggesting that individual heterogeneity exists among females in this population. 5. In the best model, the probability of breeding for the first time varied by age and year, and the amount of annual variation varied with age (average variance ratio for age-specific rates=4.3%). 6. Our results affirmed the predictions of life-history theory that age at first reproduction in long-lived mammals will be sensitive to environmental variation. In terms of life-history evolution, this variability suggests that Weddell seals display flexibility in age at first reproduction in order to maximize reproductive output under varying environmental conditions. Future analyses will attempt to test predictions regarding relationships between environmental covariates and annual variation in age at first reproduction and evaluate the relationship between age at first reproduction and lifetime reproductive success.

Population signatures of large-scale, long-term disjunction and small-scale, short-term habitat fragmentation in an Afromontane forest bird

PubMed Central

Habel, J C; Mulwa, R K; Gassert, F; Rödder, D; Ulrich, W; Borghesio, L; Husemann, M; Lens, L

2014-01-01

The Eastern Afromontane cloud forests occur as geographically distinct mountain exclaves. The conditions of these forests range from large to small and from fairly intact to strongly degraded. For this study, we sampled individuals of the forest bird species, the Montane White-eye Zosterops poliogaster from 16 sites and four mountain archipelagos. We analysed 12 polymorphic microsatellites and three phenotypic traits, and calculated Species Distribution Models (SDMs) to project past distributions and predict potential future range shifts under a scenario of climate warming. We found well-supported genetic and morphologic clusters corresponding to the mountain ranges where populations were sampled, with 43% of all alleles being restricted to single mountains. Our data suggest that large-scale and long-term geographic isolation on mountain islands caused genetically and morphologically distinct population clusters in Z. poliogaster. However, major genetic and biometric splits were not correlated to the geographic distances among populations. This heterogeneous pattern can be explained by past climatic shifts, as highlighted by our SDM projections. Anthropogenically fragmented populations showed lower genetic diversity and a lower mean body mass, possibly in response to suboptimal habitat conditions. On the basis of these findings and the results from our SDM analysis we predict further loss of genotypic and phenotypic uniqueness in the wake of climate change, due to the contraction of the species' climatic niche and subsequent decline in population size. PMID:24713824

Population signatures of large-scale, long-term disjunction and small-scale, short-term habitat fragmentation in an Afromontane forest bird.

PubMed

Habel, J C; Mulwa, R K; Gassert, F; Rödder, D; Ulrich, W; Borghesio, L; Husemann, M; Lens, L

2014-09-01

The Eastern Afromontane cloud forests occur as geographically distinct mountain exclaves. The conditions of these forests range from large to small and from fairly intact to strongly degraded. For this study, we sampled individuals of the forest bird species, the Montane White-eye Zosterops poliogaster from 16 sites and four mountain archipelagos. We analysed 12 polymorphic microsatellites and three phenotypic traits, and calculated Species Distribution Models (SDMs) to project past distributions and predict potential future range shifts under a scenario of climate warming. We found well-supported genetic and morphologic clusters corresponding to the mountain ranges where populations were sampled, with 43% of all alleles being restricted to single mountains. Our data suggest that large-scale and long-term geographic isolation on mountain islands caused genetically and morphologically distinct population clusters in Z. poliogaster. However, major genetic and biometric splits were not correlated to the geographic distances among populations. This heterogeneous pattern can be explained by past climatic shifts, as highlighted by our SDM projections. Anthropogenically fragmented populations showed lower genetic diversity and a lower mean body mass, possibly in response to suboptimal habitat conditions. On the basis of these findings and the results from our SDM analysis we predict further loss of genotypic and phenotypic uniqueness in the wake of climate change, due to the contraction of the species' climatic niche and subsequent decline in population size.

The Preventable Risk Integrated ModEl and Its Use to Estimate the Health Impact of Public Health Policy Scenarios

PubMed Central

Scarborough, Peter; Harrington, Richard A.; Mizdrak, Anja; Zhou, Lijuan Marissa; Doherty, Aiden

2014-01-01

Noncommunicable disease (NCD) scenario models are an essential part of the public health toolkit, allowing for an estimate of the health impact of population-level interventions that are not amenable to assessment by standard epidemiological study designs (e.g., health-related food taxes and physical infrastructure projects) and extrapolating results from small samples to the whole population. The PRIME (Preventable Risk Integrated ModEl) is an openly available NCD scenario model that estimates the effect of population-level changes in diet, physical activity, and alcohol and tobacco consumption on NCD mortality. The structure and methods employed in the PRIME are described here in detail, including the development of open source code that will support a PRIME web application to be launched in 2015. This paper reviews scenario results from eleven papers that have used the PRIME, including estimates of the impact of achieving government recommendations for healthy diets, health-related food taxes and subsidies, and low-carbon diets. Future challenges for NCD scenario modelling, including the need for more comparisons between models and the improvement of future prediction of NCD rates, are also discussed. PMID:25328757

Predicting Future Training Opportunities Using the Land-Use Evolution and Impact Assessment Model

DTIC Science & Technology

2007-10-01

not require surveys of local populations or other time-intensive data gathering methods. ERDC/CERL SR-07-15 3 board records, local chamber of commerce records...neighbor, Fort Benning has been identified as an Army installation threatened by encroachment (Fort Benning 2004; Greater Columbus Georgia Chamber of Commerce 2004...worked with the Greater Columbus Consolidated Chamber of Commerce to create a Joint Land Use (JLUS) plan intended to implement buffer zones, land

Spatial synchrony of local populations has increased in association with the recent Northern Hemisphere climate trend.

PubMed

Post, Eric; Forchhammer, Mads C

2004-06-22

According to ecological theory, populations whose dynamics are entrained by environmental correlation face increased extinction risk as environmental conditions become more synchronized spatially. This prediction is highly relevant to the study of ecological consequences of climate change. Recent empirical studies have indicated, for example, that large-scale climate synchronizes trophic interactions and population dynamics over broad spatial scales in freshwater and terrestrial systems. Here, we present an analysis of century-scale, spatially replicated data on local weather and the population dynamics of caribou in Greenland. Our results indicate that spatial autocorrelation in local weather has increased with large-scale climatic warming. This increase in spatial synchrony of environmental conditions has been matched, in turn, by an increase in the spatial synchrony of local caribou populations toward the end of the 20th century. Our results indicate that spatial synchrony in environmental conditions and the populations influenced by them are highly variable through time and can increase with climatic warming. We suggest that if future warming can increase population synchrony, it may also increase extinction risk.

Population-dependent effects of ocean acidification.

PubMed

Wood, Hannah L; Sundell, Kristina; Almroth, Bethanie Carney; Sköld, Helén Nilsson; Eriksson, Susanne P

2016-04-13

Elevated carbon dioxide levels and the resultant ocean acidification (OA) are changing the abiotic conditions of the oceans at a greater rate than ever before and placing pressure on marine species. Understanding the response of marine fauna to this change is critical for understanding the effects of OA. Population-level variation in OA tolerance is highly relevant and important in the determination of ecosystem resilience and persistence, but has received little focus to date. In this study, whether OA has the same biological consequences in high-salinity-acclimated population versus a low-salinity-acclimated population of the same species was investigated in the marine isopod Idotea balthica.The populations were found to have physiologically different responses to OA. While survival rate was similar between the two study populations at a future CO2 level of 1000 ppm, and both populations showed increased oxidative stress, the metabolic rate and osmoregulatory activity differed significantly between the two populations. The results of this study demonstrate that the physiological response to OA of populations from different salinities can vary. Population-level variation and the environment provenance of individuals used in OA experiments should be taken into account for the evaluation and prediction of climate change effects. © 2016 The Author(s).

Population-dependent effects of ocean acidification

PubMed Central

Wood, Hannah L.; Sundell, Kristina; Almroth, Bethanie Carney; Sköld, Helén Nilsson; Eriksson, Susanne P.

2016-01-01

Elevated carbon dioxide levels and the resultant ocean acidification (OA) are changing the abiotic conditions of the oceans at a greater rate than ever before and placing pressure on marine species. Understanding the response of marine fauna to this change is critical for understanding the effects of OA. Population-level variation in OA tolerance is highly relevant and important in the determination of ecosystem resilience and persistence, but has received little focus to date. In this study, whether OA has the same biological consequences in high-salinity-acclimated population versus a low-salinity-acclimated population of the same species was investigated in the marine isopod Idotea balthica. The populations were found to have physiologically different responses to OA. While survival rate was similar between the two study populations at a future CO2 level of 1000 ppm, and both populations showed increased oxidative stress, the metabolic rate and osmoregulatory activity differed significantly between the two populations. The results of this study demonstrate that the physiological response to OA of populations from different salinities can vary. Population-level variation and the environment provenance of individuals used in OA experiments should be taken into account for the evaluation and prediction of climate change effects. PMID:27053741

Geographical gradients in selection can reveal genetic constraints for evolutionary responses to ocean acidification

PubMed Central

Gaitán-Espitia, Juan Diego; Marshall, Dustin; Dupont, Sam; Bacigalupe, Leonardo D.; Bodrossy, Levente; Hobday, Alistair J.

2017-01-01

Geographical gradients in selection can shape different genetic architectures in natural populations, reflecting potential genetic constraints for adaptive evolution under climate change. Investigation of natural pH/pCO2 variation in upwelling regions reveals different spatio-temporal patterns of natural selection, generating genetic and phenotypic clines in populations, and potentially leading to local adaptation, relevant to understanding effects of ocean acidification (OA). Strong directional selection, associated with intense and continuous upwellings, may have depleted genetic variation in populations within these upwelling regions, favouring increased tolerances to low pH but with an associated cost in other traits. In contrast, diversifying or weak directional selection in populations with seasonal upwellings or outside major upwelling regions may have resulted in higher genetic variances and the lack of genetic correlations among traits. Testing this hypothesis in geographical regions with similar environmental conditions to those predicted under climate change will build insights into how selection may act in the future and how populations may respond to stressors such as OA. PMID:28148831

Implications of rural-urban migration for conservation of the Atlantic Forest and urban growth in Misiones, Argentina (1970-2030).

PubMed

Izquierdo, Andrea E; Grau, Héctor R; Aide, T Mitchell

2011-05-01

Global trends of increasing rural-urban migration and population urbanization could provide opportunities for nature conservation, particularly in regions where deforestation is driven by subsistence agriculture. We analyzed the role of rural population as a driver of deforestation and its contribution to urban population growth from 1970 to the present in the Atlantic Forest of Argentina, a global conservation priority. We created future land-use-cover scenarios based on human demographic parameters and the relationship between rural population and land-cover change between 1970 and 2006. In 2006, native forest covered 50% of the province, but by 2030 all scenarios predicted a decrease that ranged from 18 to 39% forest cover. Between 1970 and 2001, rural migrants represented 20% of urban population growth and are expected to represent less than 10% by 2030. This modeling approach shows how rural-urban migration and land-use planning can favor nature conservation with little impact on urban areas.

Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models.

PubMed

Keith, David A; Akçakaya, H Resit; Thuiller, Wilfried; Midgley, Guy F; Pearson, Richard G; Phillips, Steven J; Regan, Helen M; Araújo, Miguel B; Rebelo, Tony G

2008-10-23

Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.

Adaptive harvest management of North American waterfowl populations: a brief history and future prospects

USGS Publications Warehouse

Nichols, J.D.; Runge, M.C.; Johnson, F.A.; Williams, B.K.

2007-01-01

Since 1995, the US Fish and Wildlife Service has used an adaptive approach to the management of sport harvest of mid-continent Mallard ducks (Anas platyrhynchos) in North America. This approach differs from many current approaches to conservation and management in requiring close collaboration between managers and scientists. Key elements of this process are objectives, alternative management actions, models permitting prediction of system responses, and a monitoring program. The iterative process produces optimal management decisions and leads to reduction in uncertainty about response of populations to management. This general approach to management has a number of desirable features and is recommended for use in many other programs of management and conservation.

Elastic Multi-scale Mechanisms: Computation and Biological Evolution.

PubMed

Diaz Ochoa, Juan G

2018-01-01

Explanations based on low-level interacting elements are valuable and powerful since they contribute to identify the key mechanisms of biological functions. However, many dynamic systems based on low-level interacting elements with unambiguous, finite, and complete information of initial states generate future states that cannot be predicted, implying an increase of complexity and open-ended evolution. Such systems are like Turing machines, that overlap with dynamical systems that cannot halt. We argue that organisms find halting conditions by distorting these mechanisms, creating conditions for a constant creativity that drives evolution. We introduce a modulus of elasticity to measure the changes in these mechanisms in response to changes in the computed environment. We test this concept in a population of predators and predated cells with chemotactic mechanisms and demonstrate how the selection of a given mechanism depends on the entire population. We finally explore this concept in different frameworks and postulate that the identification of predictive mechanisms is only successful with small elasticity modulus.

Desert mammal populations are limited by introduced predators rather than future climate change

PubMed Central

Wardle, Glenda M.; Dickman, Chris R.

2017-01-01

Climate change is predicted to place up to one in six species at risk of extinction in coming decades, but extinction probability is likely to be influenced further by biotic interactions such as predation. We use structural equation modelling to integrate results from remote camera trapping and long-term (17–22 years) regional-scale (8000 km2) datasets on vegetation and small vertebrates (greater than 38 880 captures) to explore how biotic processes and two key abiotic drivers influence the structure of a diverse assemblage of desert biota in central Australia. We use our models to predict how changes in rainfall and wildfire are likely to influence the cover and productivity of the dominant vegetation and the impacts of predators on their primary rodent prey over a 100-year timeframe. Our results show that, while vegetation cover may decline due to climate change, the strongest negative effect on prey populations in this desert system is top-down suppression from introduced predators. PMID:29291051

Evaluation of Health Equity Impact of Structural Policies: Overview of Research Methods Used in the SOPHIE Project.

PubMed

Kunst, Anton E

2017-07-01

This article briefly assesses the research methods that were applied in the SOPHIE project to evaluate the impact of structural policies on population health and health inequalities. The evaluation of structural policies is one of the key methodological challenges in today's public health. The experience in the SOPHIE project was that mixed methods are essential to identify, understand, and predict the health impact of structural policies. On the one hand, quantitative studies that included spatial comparisons or time trend analyses, preferably in a quasi-experimental design, showed that some structural policies were associated with improved population health and smaller health inequalities. On the other hand, qualitative studies, often inspired by realist approaches, were important to understand how these policies could have achieved the observed impact and why they would succeed in some settings but fail in others. This review ends with five recommendations for future studies that aim to evaluate, understand, and predict how health inequalities can be reduced through structural policies.

Topographic, latitudinal and climatic distribution of Pinus coulteri: geographic range limits are not at the edge of the climate envelope

USGS Publications Warehouse

Chardon, Nathalie I.; Cornwell, William K.; Flint, Lorraine E.; Flint, Alan L.; Ackerly, David D.

2015-01-01

With changing climate, many species are projected to move poleward or to higher elevations to track suitable climates. The prediction that species will move poleward assumes that geographically marginal populations are at the edge of the species' climatic range. We studied Pinus coulteri from the center to the northern (poleward) edge of its range, and examined three scenarios regarding the relationship between the geographic and climatic margins of a species' range. We used herbarium and iNaturalist.org records to identify P. coulteri sites, generated a species distribution model based on temperature, precipitation, climatic water deficit, and actual evapotranspiration, and projected suitability under future climate scenarios. In fourteen populations from the central to northern portions of the range, we conducted field studies and recorded elevation, slope and aspect (to estimate solar insolation) to examine relationships between local and regional distributions. We found that northern populations of P. coulteri do not occupy the cold or wet edge of the species' climatic range; mid-latitude, high elevation populations occupy the cold margin. Aspect and insolation of P. coulteri populations changed significantly across latitudes and elevations. Unexpectedly, northern, low-elevation stands occupy north-facing aspects and receive low insolation, while central, high-elevation stands grow on more south-facing aspects that receive higher insolation. Modeled future climate suitability is projected to be highest in the central, high elevation portion of the species range, and in low-lying coastal regions under some scenarios, with declining suitability in northern areas under most future scenarios. For P. coulteri, the lack of high elevation habitat combined with a major dispersal barrier may limit northward movement in response to a warming climate. Our analyses demonstrate the importance of distinguishing geographically vs. climatically marginal populations, and the importance of quantitative analysis of the realized climate space to understand species range limits.

The future of postgraduate training.

PubMed

Walsh, Kieran

2014-01-01

Improvements to postgraduate training have included newly designed postgraduate curricula, new forms of delivery of learning, more valid and reliable assessments, and more rigorous evaluation of training programmes. All these changes have been necessary and have now started to settle in. Now therefore is an appropriate time to look to the future of postgraduate training. Predicting the future is difficult in any course of life-however an examination of recent trends is often a good place to start. In this regard the recent trend to start to produce more doctors and healthcare professionals of the type that the population needs is likely to continue for some time to come. Medical education will also need to be more flexible in the future. The more flexible that training programmes are, the more likely that we will have experts that are sufficiently flexible to meet a range of different challenges throughout the rest of their careers. Medical education will also become more seamless in the future (at present there are probably too many major milestones and transitions in medical education). In the future educators will make much more use of technology enhanced learning, e-learning and simulation in postgraduate medical education. There will also be more pressure on postgraduate training programmes to offer value for money and to be able to demonstrate such value for money. Postgraduate medical education of the future will also be a more personalised and adaptive experience. It will be far more based on learners' individual needs and will be more responsive to those needs. Lastly postgraduate education will be much more closely supervised than it has been in the past. A common theme running through these changes will be patient centredness. This will mean safer training programmes that produce the type of doctors that patients and populations need.

Translating effects of inbreeding depression on component vital rates to overall population growth in endangered bighorn sheep.

PubMed

Johnson, Heather E; Mills, L Scott; Wehausen, John D; Stephenson, Thomas R; Luikart, Gordon

2011-12-01

Evidence of inbreeding depression is commonly detected from the fitness traits of animals, yet its effects on population growth rates of endangered species are rarely assessed. We examined whether inbreeding depression was affecting Sierra Nevada bighorn sheep (Ovis canadensis sierrae), a subspecies listed as endangered under the U.S. Endangered Species Act. Our objectives were to characterize genetic variation in this subspecies; test whether inbreeding depression affects bighorn sheep vital rates (adult survival and female fecundity); evaluate whether inbreeding depression may limit subspecies recovery; and examine the potential for genetic management to increase population growth rates. Genetic variation in 4 populations of Sierra Nevada bighorn sheep was among the lowest reported for any wild bighorn sheep population, and our results suggest that inbreeding depression has reduced adult female fecundity. Despite this population sizes and growth rates predicted from matrix-based projection models demonstrated that inbreeding depression would not substantially inhibit the recovery of Sierra Nevada bighorn sheep populations in the next approximately 8 bighorn sheep generations (48 years). Furthermore, simulations of genetic rescue within the subspecies did not suggest that such activities would appreciably increase population sizes or growth rates during the period we modeled (10 bighorn sheep generations, 60 years). Only simulations that augmented the Mono Basin population with genetic variation from other subspecies, which is not currently a management option, predicted significant increases in population size. Although we recommend that recovery activities should minimize future losses of genetic variation, genetic effects within these endangered populations-either negative (inbreeding depression) or positive (within subspecies genetic rescue)-appear unlikely to dramatically compromise or stimulate short-term conservation efforts. The distinction between detecting the effects of inbreeding depression on a component vital rate (e.g., fecundity) and the effects of inbreeding depression on population growth underscores the importance of quantifying inbreeding costs relative to population dynamics to effectively manage endangered populations. ©2011 Society for Conservation Biology.

Review of fall risk assessment in geriatric populations using inertial sensors

PubMed Central

2013-01-01

Background Falls are a prevalent issue in the geriatric population and can result in damaging physical and psychological consequences. Fall risk assessment can provide information to enable appropriate interventions for those at risk of falling. Wearable inertial-sensor-based systems can provide quantitative measures indicative of fall risk in the geriatric population. Methods Forty studies that used inertial sensors to evaluate geriatric fall risk were reviewed and pertinent methodological features were extracted; including, sensor placement, derived parameters used to assess fall risk, fall risk classification method, and fall risk classification model outcomes. Results Inertial sensors were placed only on the lower back in the majority of papers (65%). One hundred and thirty distinct variables were assessed, which were categorized as position and angle (7.7%), angular velocity (11.5%), linear acceleration (20%), spatial (3.8%), temporal (23.1%), energy (3.8%), frequency (15.4%), and other (14.6%). Fallers were classified using retrospective fall history (30%), prospective fall occurrence (15%), and clinical assessment (32.5%), with 22.5% using a combination of retrospective fall occurrence and clinical assessments. Half of the studies derived models for fall risk prediction, which reached high levels of accuracy (62-100%), specificity (35-100%), and sensitivity (55-99%). Conclusions Inertial sensors are promising sensors for fall risk assessment. Future studies should identify fallers using prospective techniques and focus on determining the most promising sensor sites, in conjunction with determination of optimally predictive variables. Further research should also attempt to link predictive variables to specific fall risk factors and investigate disease populations that are at high risk of falls. PMID:23927446

Rheumatology in the community of Madrid: current availability of rheumatologists and future needs using a predictive model.

PubMed

Lázaro y De Mercado, Pablo; Blasco Bravo, Antonio Javier; Lázaro y De Mercado, Ignacio; Castañeda, Santos; López Robledillo, Juan Carlos

2013-01-01

To: 1) describe the distribution of the public sector rheumatologists; 2) identify variables on which the workload in Rheumatology depends; and 3) build a predictive model on the need of rheumatologists for the next 10 years, in the Community of Madrid (CM). The information was obtained through structured questionnaires sent to all services/units of Rheumatology of public hospitals in the CM. The population figures, current and forecasted, were obtained from the National Statistics Institute. A predictive model was built based on information about the current and foreseeable supply, current and foreseeable demand, and the assumptions and criteria used to match supply with demand. The underlying uncertainty in the model was assessed by sensitivity analysis. In the CM in 2011 there were 150 staff rheumatologists and 49 residents in 27 centers, which is equivalent to one rheumatologist for every 33,280 inhabitants in the general population, and one for every 4,996 inhabitants over 65 years. To keep the level of assistance of 2011 in 2021 in the general population, it would be necessary to train more residents or hire more rheumatologists in scenarios of demand higher than 15%. However, to keep the level of assistance in the population over 65 years of age it would be necessary to train more residents or hire more specialists even without increased demand. The model developed may be very useful for planning, with the CM policy makers, the needs of human resources in Rheumatology in the coming years. Copyright © 2012 Elsevier España, S.L. All rights reserved.

Suicide Among Soldiers: A Review of Psychosocial Risk and Protective Factors

PubMed Central

Nock, Matthew K.; Deming, Charlene A.; Fullerton, Carol S.; Gilman, Stephen E.; Goldenberg, Matthew; Kessler, Ronald C.; McCarroll, James E.; McLaughlin, Katie A.; Peterson, Christopher; Schoenbaum, Michael; Stanley, Barbara; Ursano, Robert J.

2014-01-01

Suicide is difficult to predict and prevent and remains a leading cause of death worldwide. Although soldiers historically have had a suicide rate well below that of the general population, the suicide rate among members of the U.S. Army has increased markedly over the past several years and now exceeds that of the general population. This paper reviews psychosocial factors known to be associated with the increased risk of suicidal behavior in general and describes how some of these factors may be especially important in understanding suicide among soldiers. Moving forward, the prevention of suicide requires additional research aimed at: (a) better describing when, where, and among whom suicidal behavior occurs, (b) using exploratory studies to discover new risk and protective factors, (c) developing new methods of predicting suicidal behavior that synthesize information about modifiable risk and protective factors from multiple domains, and (d) understanding the mechanisms and pathways through which suicidal behavior develops. Although the scope and severity of this problem is daunting, the increasing attention and dedication to this issue by the Armed Forces, scientists, and society provide hope for our ability to better predict and prevent these tragic outcomes in the future. PMID:23631542

Application of Athletic Movement Tests that Predict Injury Risk in a Military Population: Development of Normative Data.

PubMed

Teyhen, Deydre S; Shaffer, Scott W; Butler, Robert J; Goffar, Stephen L; Kiesel, Kyle B; Rhon, Daniel I; Boyles, Robert E; McMillian, Daniel J; Williamson, Jared N; Plisky, Phillip J

2016-10-01

Performance on movement tests helps to predict injury risk in a variety of physically active populations. Understanding baseline measures for normal is an important first step. Determine differences in physical performance assessments and describe normative values for these tests based on military unit type. Assessment of power, balance, mobility, motor control, and performance on the Army Physical Fitness Test were assessed in a cohort of 1,466 soldiers. Analysis of variance was performed to compare the results based on military unit type (Rangers, Combat, Combat Service, and Combat Service Support) and analysis of covariance was performed to determine the influence of age and gender. Rangers performed the best on all performance and fitness measures (p < 0.05). Combat soldiers performed better than Combat Service and Service Support soldiers on several physical performance tests and the Army Physical Fitness Test (p < 0.05). Performance in Combat Service and Service Support soldiers was equivalent on most measures (p < 0.05). Functional performance and level of fitness varied significantly by military unit type. Understanding these differences will provide a foundation for future injury prediction and prevention strategies. Reprint & Copyright © 2016 Association of Military Surgeons of the U.S.

Validation of a Screening Questionnaire for Chronic Leg Ulcers.

PubMed

Zarchi, Kian; Theut Riis, Peter; Graversgaard, Christine; Miller, Iben M; Heidenheim, Michael; Jemec, Gregor B E

2016-12-01

The use of a validated screening questionnaire to identify individuals with chronic leg ulcers allows large-scale population-based studies to be conducted that measure and monitor the prevalence of the disease. The aim of this study was to design and validate such a screening questionnaire to identify patients with chronic leg ulcers. A simple 3-item questionnaire was developed at the Department of Dermatology, University Hospital of Zealand, Denmark. In total, 90 patients attending the department's outpatient clinic for dermatological diseases and chronic wounds were included in this study. All included participants completed the questionnaire and were subsequently examined by dermatologists. We found that the constructed 3-item questionnaire in this study had a sensitivity and specificity of 95% and 93% and a positive predictive value and negative predictive value of 78% and 95%, respectively. Moreover, we found that the use of the 3-item questionnaire, as compared with a single question, in which the participants were asked whether they currently have a leg ulcer, resulted in significantly higher positive predictive value (+11.6%, P = .035) and specificity (+5.6%, P = .046) of the diagnostic test. Future studies are merited to investigate the diagnostic accuracy of the questionnaire in other populations and settings.

Long-term fitness consequences of early environment in a long-lived ungulate

PubMed Central

Festa-Bianchet, Marco; Pelletier, Fanie

2017-01-01

Cohort effects can be a major source of heterogeneity and play an important role in population dynamics. Silver-spoon effects, when environmental quality at birth improves future performance regardless of the adult environment, can induce strong lagged responses on population growth. Alternatively, the external predictive adaptive response (PAR) hypothesis predicts that organisms will adjust their developmental trajectory and physiology during early life in anticipation of expected adult conditions but has rarely been assessed in wild species. We used over 40 years of detailed individual monitoring of bighorn ewes (Ovis canadensis) to quantify long-term cohort effects on survival and reproduction. We then tested both the silver-spoon and the PAR hypotheses. Cohort effects involved a strong interaction between birth and current environments: reproduction and survival were lowest for ewes that were born and lived at high population densities. This interaction, however, does not support the PAR hypothesis because individuals with matching high-density birth and adult environments had reduced fitness. Instead, individuals born at high density had overall lower lifetime fitness suggesting a silver-spoon effect. Early-life conditions can induce long-term changes in fitness components, and their effects on cohort fitness vary according to adult environment. PMID:28424347

Hip fracture incidence 2003-2013 and projected cases until 2050 in Austria: a population-based study.

PubMed

Concin, Hans; Brozek, Wolfgang; Benedetto, Karl-Peter; Häfele, Hartmut; Kopf, Joachim; Bärenzung, Thomas; Schnetzer, Richard; Schenk, Christian; Stimpfl, Elmar; Waheed-Hutter, Ursula; Ulmer, Hanno; Rapp, Kilian; Zwettler, Elisabeth; Nagel, Gabriele

2016-12-01

Elevated hip fracture incidence is a major public health problem looming to aggravate in industrialized countries due to demographic developments. We report hip fracture incidence and expected future cases from Vorarlberg, the westernmost province of Austria, results potentially representative of Central European populations. Crude and standardized hip fracture incidence rates in Vorarlberg 2003-2013 are reported. Based on the age-specific incidence in 2013 or trends 2003-2013, we predict hip fractures till 2050. Female age-standardized hip fracture incidence decreased 2005-2013, whereas for men, the trend was rather unclear. Uncorrected forecasts indicate that by 2050, female and male cases will each have more than doubled from 2015 in all demographic core scenarios. Corrected by incidence trends before 2013, cases are expected to drop among women but rise among men. We anticipate rising hip fracture numbers in Vorarlberg within the next decades, unless prevention programs that presumably account for decreasing incidence rates, particularly among women since 2005, take further effect to counteract the predicted steady increase due to demographic changes. Concomitantly, augmented endeavors to target the male population by these programs are needed.

The Formation of Milky Way-mass Disk Galaxies in the First 500 Million Years of a Cold Dark Matter Universe

NASA Astrophysics Data System (ADS)

Feng, Yu; Di Matteo, Tiziana; Croft, Rupert; Tenneti, Ananth; Bird, Simeon; Battaglia, Nicholas; Wilkins, Stephen

2015-07-01

Whether or not among the myriad tiny protogalaxies there exists a population with similarities to present-day galaxies is an open question. We show, using BlueTides, the first hydrodynamic simulation large enough to resolve the relevant scales, that the first massive galaxies to form are predicted to have extensive rotationally supported disks. Although their morphology resembles in some ways Milky Way types seen at much lower redshifts, these high-redshift galaxies are smaller, denser, and richer in gas than their low-redshift counterparts. From a kinematic analysis of a statistical sample of 216 galaxies at redshift z = 8-10, we have found that disk galaxies make up 70% of the population of galaxies with stellar mass {10}10{M}⊙ or greater. Cold dark matter cosmology therefore makes specific predictions for the population of large galaxies 500 million years after the Big Bang. We argue that wide-field satellite telescopes (e.g., WFIRST) will in the near future discover these first massive disk galaxies. The simplicity of their structure and formation history should make new tests of cosmology possible.

Testicular cancer incidence to rise by 25% by 2025 in Europe? Model-based predictions in 40 countries using population-based registry data.

PubMed

Le Cornet, Charlotte; Lortet-Tieulent, Joannie; Forman, David; Béranger, Rémi; Flechon, Aude; Fervers, Béatrice; Schüz, Joachim; Bray, Freddie

2014-03-01

Testicular cancer mainly affects White Caucasian populations, accounts for 1% of all male cancers, and is frequently the most common malignancy among young adult men. In light of the escalating rates of testicular cancer incidence in Europe, and in support of future planning to ensure optimal care of patients with what can be a curable disease, we predict the future burden in 40 European countries around 2025. Current observed trends were extrapolated with the NORDPRED model to estimate the future burden of testicular cancer in the context of changes in risk versus changes in demographics. Despite substantial heterogeneity in the rates, the vast majority of European countries will see an increasing burden over the next two decades. We estimate there will be 23,000 new cases of testicular cancer annually in Europe by 2025, a rise of 24% from 2005. Some of the most rapid increases in testicular cancer are observed in Croatia, Slovenia, Italy and Spain, and a transition is underway, whereby recent attenuations and declines in rates in certain high-risk countries in Northern Europe contrast with the increasing trends and escalating burden in Southern Europe. According to our estimates for 2025, around one in 100 men will be diagnosed with the disease annually in the highest risk countries of Europe (Croatia, Slovenia and Norway). Elucidating the key determinants of testicular cancer and the equitable provision of optimal care for patients across Europe are priorities given the steady rise in the number of patients by 2025, and an absence of primary prevention opportunities. None. Copyright © 2013 Elsevier Ltd. All rights reserved.

Urinary Sugars--A Biomarker of Total Sugars Intake.

PubMed

Tasevska, Natasha

2015-07-15

Measurement error in self-reported sugars intake may explain the lack of consistency in the epidemiologic evidence on the association between sugars and disease risk. This review describes the development and applications of a biomarker of sugars intake, informs its future use and recommends directions for future research. Recently, 24 h urinary sucrose and fructose were suggested as a predictive biomarker for total sugars intake, based on findings from three highly controlled feeding studies conducted in the United Kingdom. From this work, a calibration equation for the biomarker that provides an unbiased measure of sugars intake was generated that has since been used in two US-based studies with free-living individuals to assess measurement error in dietary self-reports and to develop regression calibration equations that could be used in future diet-disease analyses. Further applications of the biomarker include its use as a surrogate measure of intake in diet-disease association studies. Although this biomarker has great potential and exhibits favorable characteristics, available data come from a few controlled studies with limited sample sizes conducted in the UK. Larger feeding studies conducted in different populations are needed to further explore biomarker characteristics and stability of its biases, compare its performance, and generate a unique, or population-specific biomarker calibration equations to be applied in future studies. A validated sugars biomarker is critical for informed interpretation of sugars-disease association studies.

Urinary Sugars—A Biomarker of Total Sugars Intake

PubMed Central

Tasevska, Natasha

2015-01-01

Measurement error in self-reported sugars intake may explain the lack of consistency in the epidemiologic evidence on the association between sugars and disease risk. This review describes the development and applications of a biomarker of sugars intake, informs its future use and recommends directions for future research. Recently, 24 h urinary sucrose and fructose were suggested as a predictive biomarker for total sugars intake, based on findings from three highly controlled feeding studies conducted in the United Kingdom. From this work, a calibration equation for the biomarker that provides an unbiased measure of sugars intake was generated that has since been used in two US-based studies with free-living individuals to assess measurement error in dietary self-reports and to develop regression calibration equations that could be used in future diet-disease analyses. Further applications of the biomarker include its use as a surrogate measure of intake in diet-disease association studies. Although this biomarker has great potential and exhibits favorable characteristics, available data come from a few controlled studies with limited sample sizes conducted in the UK. Larger feeding studies conducted in different populations are needed to further explore biomarker characteristics and stability of its biases, compare its performance, and generate a unique, or population-specific biomarker calibration equations to be applied in future studies. A validated sugars biomarker is critical for informed interpretation of sugars-disease association studies. PMID:26184307

The Workforce Task Force report: clinical implications for neurology.

PubMed

Freeman, William D; Vatz, Kenneth A; Griggs, Robert C; Pedley, Timothy

2013-07-30

The American Academy of Neurology Workforce Task Force (WFTF) report predicts a future shortfall of neurologists in the United States. The WFTF data also suggest that for most states, the current demand for neurologist services already exceeds the supply, and by 2025 the demand for neurologists will be even higher. This future demand is fueled by the aging of the US population, the higher health care utilization rates of neurologic services, and by a greater number of patients gaining access to the health care system due to the Patient Protection and Affordable Care Act. Uncertainties in health care delivery and patient access exist due to looming concerns about further Medicare reimbursement cuts. This uncertainty is set against a backdrop of Congressional volatility on a variety of issues, including the repeal of the sustainable growth rate for physician reimbursement. The impact of these US health care changes on the neurology workforce, future increasing demands, reimbursement, and alternative health care delivery models including accountable care organizations, nonphysician providers such as nurse practitioners and physician assistants, and teleneurology for both stroke and general neurology are discussed. The data lead to the conclusion that neurologists will need to play an even larger role in caring for the aging US population by 2025. We propose solutions to increase the availability of neurologic services in the future and provide other ways of meeting the anticipated increased demand for neurologic care.

The Workforce Task Force Report

PubMed Central

Vatz, Kenneth A.; Griggs, Robert C.; Pedley, Timothy

2013-01-01

The American Academy of Neurology Workforce Task Force (WFTF) report predicts a future shortfall of neurologists in the United States. The WFTF data also suggest that for most states, the current demand for neurologist services already exceeds the supply, and by 2025 the demand for neurologists will be even higher. This future demand is fueled by the aging of the US population, the higher health care utilization rates of neurologic services, and by a greater number of patients gaining access to the health care system due to the Patient Protection and Affordable Care Act. Uncertainties in health care delivery and patient access exist due to looming concerns about further Medicare reimbursement cuts. This uncertainty is set against a backdrop of Congressional volatility on a variety of issues, including the repeal of the sustainable growth rate for physician reimbursement. The impact of these US health care changes on the neurology workforce, future increasing demands, reimbursement, and alternative health care delivery models including accountable care organizations, nonphysician providers such as nurse practitioners and physician assistants, and teleneurology for both stroke and general neurology are discussed. The data lead to the conclusion that neurologists will need to play an even larger role in caring for the aging US population by 2025. We propose solutions to increase the availability of neurologic services in the future and provide other ways of meeting the anticipated increased demand for neurologic care. PMID:23783750

An adaptive strategy for active debris removal

NASA Astrophysics Data System (ADS)

White, Adam E.; Lewis, Hugh G.

2014-04-01

Many parameters influence the evolution of the near-Earth debris population, including launch, solar, explosion and mitigation activities, as well as other future uncertainties such as advances in space technology or changes in social and economic drivers that effect the utilisation of space activities. These factors lead to uncertainty in the long-term debris population. This uncertainty makes it difficult to identify potential remediation strategies, involving active debris removal (ADR), that will perform effectively in all possible future cases. Strategies that cannot perform effectively, because of this uncertainty, risk either not achieving their intended purpose, or becoming a hindrance to the efforts of spacecraft manufactures and operators to address the challenges posed by space debris. One method to tackle this uncertainty is to create a strategy that can adapt and respond to the space debris population. This work explores the concept of an adaptive strategy, in terms of the number of objects required to be removed by ADR, to prevent the low Earth orbit (LEO) debris population from growing in size. This was demonstrated by utilising the University of Southampton’s Debris Analysis and Monitoring Architecture to the Geosynchronous Environment (DAMAGE) tool to investigate ADR rates (number of removals per year) that change over time in response to the current space environment, with the requirement of achieving zero growth of the LEO population. DAMAGE was used to generate multiple Monte Carlo projections of the future LEO debris environment. Within each future projection, the debris removal rate was derived at five-year intervals, by a new statistical debris evolutionary model called the Computational Adaptive Strategy to Control Accurately the Debris Environment (CASCADE) model. CASCADE predicted the long-term evolution of the current DAMAGE population with a variety of different ADR rates in order to identify a removal rate that produced a zero net growth for that particular projection after 200 years. The results show that using an adaptive ADR rate generated by CASCADE, alongside good compliance with existing mitigation measures, increases the probability of achieving a constant LEO population of objects greater than 10 cm. This was shown to be 12% greater compared with removing five objects per year, with the additional advantage of requiring only 3.1 removals per year, on average.

Population of Nuclei Via 7Li-Induced Binary Reactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clark, Rodney M.; Phair, Larry W.; Descovich, M.

2005-08-08

The authors have investigated the population of nuclei formed in binary reactions involving {sup 7}Li beams on targets of {sup 160}Gd and {sup 184}W. The {sup 7}Li + {sup 184}W data were taken in the first experiment using the LIBERACE Ge-array in combination with the STARS Si {Delta}E-E telescope system at the 88-Inch Cyclotron of the Lawrence Berkeley National Laboratory. By using the Wilczynski binary transfer model, in combination with a standard evaporation model, they are able to reproduce the experimental results. This is a useful method for predicting the population of neutron-rich heavy nuclei formed in binary reactions involvingmore » beams of weakly bound nuclei formed in binary reactions involving beams of weakly bound nuclei and will be of use in future spectroscopic studies.« less

Analysis of crimes committed against scheduled tribes

NASA Astrophysics Data System (ADS)

Khadse, Vivek P.; Akhil, P.; Anto, Christopher; Gnanasigamani, Lydia J.

2017-11-01

One of the curses to the society is a crime which has a deep impact on the society. Victims of crimes are the one who is impacted the most. All communities in the world are affected by crime and the criminal justice system, but largely impacted communities are the backward classes. There are many cases reported of crime committed against scheduled tribes from the year 2005 till date. This paper states the analysis of Crimes Committed against Scheduled Tribes in the year 2015 in various states and union territories in India. In this study, Multiple Linear regression techniques have been used to analyze the crimes committed against scheduled tribes’ community in India. This study compares the number of cases reported to the police station and rate of crime committed in different states in India. It also states the future prediction of the crime that would happen. It will also predict the number of cases of crime committed against the scheduled tribe that can be reported in future. The dataset which has been used in this study is taken from official Indian government repository for crimes which include different information of crimes committed against scheduled tribes in different states and union territories measured under the population census of the year 2011. This study will help different Indian states and union territory government to analyze and predict the future crimes that may occur and take appropriate measures against it before the actual crime would occur.

Potential changes in forest composition could reduce impacts of climate change on boreal wildfires.

PubMed

Terrier, Aurélie; Girardin, Martin P; Périé, Catherine; Legendre, Pierre; Bergeron, Yves

2013-01-01

There is general consensus that wildfires in boreal forests will increase throughout this century in response to more severe and frequent drought conditions induced by climate change. However, prediction models generally assume that the vegetation component will remain static over the next few decades. As deciduous species are less flammable than conifer species, it is reasonable to believe that a potential expansion of deciduous species in boreal forests, either occurring naturally or through landscape management, could offset some of the impacts of climate change on the occurrence of boreal wildfires. The objective of this study was to determine the potential of this offsetting effect through a simulation experiment conducted in eastern boreal North America. Predictions of future fire activity were made using multivariate adaptive regression splines (MARS) with fire behavior indices and ecological niche models as predictor variables so as to take into account the effects of changing climate and tree distribution on fire activity. A regional climate model (RCM) was used for predictions of future fire risk conditions. The experiment was conducted under two tree dispersal scenarios: the status quo scenario, in which the distribution of forest types does not differ from the present one, and the unlimited dispersal scenario, which allows forest types to expand their range to fully occupy their climatic niche. Our results show that future warming will create climate conditions that are more prone to fire occurrence. However, unlimited dispersal of southern restricted deciduous species could reduce the impact of climate change on future fire occurrence. Hence, the use of deciduous species could be a good option for an efficient strategic fire mitigation strategy aimed at reducing fire Propagation in coniferous landscapes and increasing public safety in remote populated areas of eastern boreal Canada under climate change.

Adolescents’ expectations for the future predict health behaviors in early adulthood

PubMed Central

McDade, Thomas W.; Chyu, Laura; Duncan, Greg J.; Hoyt, Lindsay T.; Doane, Leah D.; Adam, Emma K.

2011-01-01

Health-related behaviors in adolescence establish trajectories of risk for obesity and chronic degenerative diseases, and they represent an important pathway through which socio-economic environments shape patterns of morbidity and mortality. Most behaviors that promote health involve making choices that may not pay off until the future, but the factors that predict an individual's investment in future health are not known. In this paper we consider whether expectations for the future in two domains relevant to adolescents in the U.S.—perceived chances of living to middle age and perceived chances of attending college—are associated with an individual's engagement in behaviors that protect health in the long run. We focus on adolescence as an important life stage during which habits formed may shape trajectories of disease risk later in life. We use data from a large, nationally representative sample of American youth (the US National Longitudinal Study of Adolescent Health) to predict levels of physical activity, fast food consumption, and cigarette smoking in young adulthood in relation to perceived life chances in adolescence, controlling for baseline health behaviors and a wide range of potentially confounding factors. We found that adolescents who rated their chances of attending college more highly exercised more frequently and smoked fewer cigarettes in young adulthood. Adolescents with higher expectations of living to age 35 smoked fewer cigarettes as young adults. Parental education was a significant predictor of perceived life chances, as well as health behaviors, but for each outcome the effects of perceived life chances were independent of, and often stronger than, parental education. Perceived life chances in adolescence may therefore play an important role in establishing individual trajectories of health, and in contributing to social gradients in population health. PMID:21764487

Adolescents' expectations for the future predict health behaviors in early adulthood.

PubMed

McDade, Thomas W; Chyu, Laura; Duncan, Greg J; Hoyt, Lindsay T; Doane, Leah D; Adam, Emma K

2011-08-01

Health-related behaviors in adolescence establish trajectories of risk for obesity and chronic degenerative diseases, and they represent an important pathway through which socio-economic environments shape patterns of morbidity and mortality. Most behaviors that promote health involve making choices that may not pay off until the future, but the factors that predict an individual's investment in future health are not known. In this paper we consider whether expectations for the future in two domains relevant to adolescents in the U.S.-perceived chances of living to middle age and perceived chances of attending college-are associated with an individual's engagement in behaviors that protect health in the long run. We focus on adolescence as an important life stage during which habits formed may shape trajectories of disease risk later in life. We use data from a large, nationally representative sample of American youth (the US National Longitudinal Study of Adolescent Health) to predict levels of physical activity, fast food consumption, and cigarette smoking in young adulthood in relation to perceived life chances in adolescence, controlling for baseline health behaviors and a wide range of potentially confounding factors. We found that adolescents who rated their chances of attending college more highly exercised more frequently and smoked fewer cigarettes in young adulthood. Adolescents with higher expectations of living to age 35 smoked fewer cigarettes as young adults. Parental education was a significant predictor of perceived life chances, as well as health behaviors, but for each outcome the effects of perceived life chances were independent of, and often stronger than, parental education. Perceived life chances in adolescence may therefore play an important role in establishing individual trajectories of health, and in contributing to social gradients in population health. Copyright © 2011 Elsevier Ltd. All rights reserved.

Accuracy of risk scales for predicting repeat self-harm and suicide: a multicentre, population-level cohort study using routine clinical data.

PubMed

Steeg, Sarah; Quinlivan, Leah; Nowland, Rebecca; Carroll, Robert; Casey, Deborah; Clements, Caroline; Cooper, Jayne; Davies, Linda; Knipe, Duleeka; Ness, Jennifer; O'Connor, Rory C; Hawton, Keith; Gunnell, David; Kapur, Nav

2018-04-25

Risk scales are used widely in the management of patients presenting to hospital following self-harm. However, there is evidence that their diagnostic accuracy in predicting repeat self-harm is limited. Their predictive accuracy in population settings, and in identifying those at highest risk of suicide is not known. We compared the predictive accuracy of the Manchester Self-Harm Rule (MSHR), ReACT Self-Harm Rule (ReACT), SAD PERSONS Scale (SPS) and Modified SAD PERSONS Scale (MSPS) in an unselected sample of patients attending hospital following self-harm. Data on 4000 episodes of self-harm presenting to Emergency Departments (ED) between 2010 and 2012 were obtained from four established monitoring systems in England. Episodes were assigned a risk category for each scale and followed up for 6 months. The episode-based repeat rate was 28% (1133/4000) and the incidence of suicide was 0.5% (18/3962). The MSHR and ReACT performed with high sensitivity (98% and 94% respectively) and low specificity (15% and 23%). The SPS and the MSPS performed with relatively low sensitivity (24-29% and 9-12% respectively) and high specificity (76-77% and 90%). The area under the curve was 71% for both MSHR and ReACT, 51% for SPS and 49% for MSPS. Differences in predictive accuracy by subgroup were small. The scales were less accurate at predicting suicide than repeat self-harm. The scales failed to accurately predict repeat self-harm and suicide. The findings support existing clinical guidance not to use risk classification scales alone to determine treatment or predict future risk.