Modelling the influence of predicted future climate change on the risk of wind damage within New Zealand's planted forests.

PubMed

Moore, John R; Watt, Michael S

2015-08-01

Wind is the major abiotic disturbance in New Zealand's planted forests, but little is known about how the risk of wind damage may be affected by future climate change. We linked a mechanistic wind damage model (ForestGALES) to an empirical growth model for radiata pine (Pinus radiata D. Don) and a process-based growth model (cenw) to predict the risk of wind damage under different future emissions scenarios and assumptions about the future wind climate. The cenw model was used to estimate site productivity for constant CO2 concentration at 1990 values and for assumed increases in CO2 concentration from current values to those expected during 2040 and 2090 under the B1 (low), A1B (mid-range) and A2 (high) emission scenarios. Stand development was modelled for different levels of site productivity, contrasting silvicultural regimes and sites across New Zealand. The risk of wind damage was predicted for each regime and emission scenario combination using the ForestGALES model. The sensitivity to changes in the intensity of the future wind climate was also examined. Results showed that increased tree growth rates under the different emissions scenarios had the greatest impact on the risk of wind damage. The increase in risk was greatest for stands growing at high stand density under the A2 emissions scenario with increased CO2 concentration. The increased productivity under this scenario resulted in increased tree height, without a corresponding increase in diameter, leading to more slender trees that were predicted to be at greater risk from wind damage. The risk of wind damage was further increased by the modest increases in the extreme wind climate that are predicted to occur. These results have implications for the development of silvicultural regimes that are resilient to climate change and also indicate that future productivity gains may be offset by greater losses from disturbances. © 2015 John Wiley & Sons Ltd.

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...

Allometric growth in reef-building corals.

PubMed

Dornelas, Maria; Madin, Joshua S; Baird, Andrew H; Connolly, Sean R

2017-03-29

Predicting demographic rates is a critical part of forecasting the future of ecosystems under global change. Here, we test if growth rates can be predicted from morphological traits for a highly diverse group of colonial symbiotic organisms: scleractinian corals. We ask whether growth is isometric or allometric among corals, and whether most variation in coral growth rates occurs at the level of the species or morphological group. We estimate growth as change in planar area for 11 species, across five morphological groups and over 5 years. We show that coral growth rates are best predicted from colony size and morphology rather than species. Coral size follows a power scaling law with a constant exponent of 0.91. Despite being colonial organisms, corals have consistent allometric scaling in growth. This consistency simplifies the task of projecting community responses to disturbance and climate change. © 2017 The Author(s).

Predicting the past: a simple reverse stand table projection method

Treesearch

Quang V. Cao; Shanna M. McCarty

2006-01-01

A stand table gives number of trees in each diameter class. Future stand tables can be predicted from current stand tables using a stand table projection method. In the simplest form of this method, a future stand table can be expressed as the product of a matrix of transitional proportions (based on diameter growth rates) and a vector of the current stand table. There...

Classical Mathematical Models for Description and Prediction of Experimental Tumor Growth

PubMed Central

Benzekry, Sébastien; Lamont, Clare; Beheshti, Afshin; Tracz, Amanda; Ebos, John M. L.; Hlatky, Lynn; Hahnfeldt, Philip

2014-01-01

Despite internal complexity, tumor growth kinetics follow relatively simple laws that can be expressed as mathematical models. To explore this further, quantitative analysis of the most classical of these were performed. The models were assessed against data from two in vivo experimental systems: an ectopic syngeneic tumor (Lewis lung carcinoma) and an orthotopically xenografted human breast carcinoma. The goals were threefold: 1) to determine a statistical model for description of the measurement error, 2) to establish the descriptive power of each model, using several goodness-of-fit metrics and a study of parametric identifiability, and 3) to assess the models' ability to forecast future tumor growth. The models included in the study comprised the exponential, exponential-linear, power law, Gompertz, logistic, generalized logistic, von Bertalanffy and a model with dynamic carrying capacity. For the breast data, the dynamics were best captured by the Gompertz and exponential-linear models. The latter also exhibited the highest predictive power, with excellent prediction scores (≥80%) extending out as far as 12 days in the future. For the lung data, the Gompertz and power law models provided the most parsimonious and parametrically identifiable description. However, not one of the models was able to achieve a substantial prediction rate (≥70%) beyond the next day data point. In this context, adjunction of a priori information on the parameter distribution led to considerable improvement. For instance, forecast success rates went from 14.9% to 62.7% when using the power law model to predict the full future tumor growth curves, using just three data points. These results not only have important implications for biological theories of tumor growth and the use of mathematical modeling in preclinical anti-cancer drug investigations, but also may assist in defining how mathematical models could serve as potential prognostic tools in the clinic. PMID:25167199

Classical mathematical models for description and prediction of experimental tumor growth.

PubMed

Benzekry, Sébastien; Lamont, Clare; Beheshti, Afshin; Tracz, Amanda; Ebos, John M L; Hlatky, Lynn; Hahnfeldt, Philip

2014-08-01

Despite internal complexity, tumor growth kinetics follow relatively simple laws that can be expressed as mathematical models. To explore this further, quantitative analysis of the most classical of these were performed. The models were assessed against data from two in vivo experimental systems: an ectopic syngeneic tumor (Lewis lung carcinoma) and an orthotopically xenografted human breast carcinoma. The goals were threefold: 1) to determine a statistical model for description of the measurement error, 2) to establish the descriptive power of each model, using several goodness-of-fit metrics and a study of parametric identifiability, and 3) to assess the models' ability to forecast future tumor growth. The models included in the study comprised the exponential, exponential-linear, power law, Gompertz, logistic, generalized logistic, von Bertalanffy and a model with dynamic carrying capacity. For the breast data, the dynamics were best captured by the Gompertz and exponential-linear models. The latter also exhibited the highest predictive power, with excellent prediction scores (≥80%) extending out as far as 12 days in the future. For the lung data, the Gompertz and power law models provided the most parsimonious and parametrically identifiable description. However, not one of the models was able to achieve a substantial prediction rate (≥70%) beyond the next day data point. In this context, adjunction of a priori information on the parameter distribution led to considerable improvement. For instance, forecast success rates went from 14.9% to 62.7% when using the power law model to predict the full future tumor growth curves, using just three data points. These results not only have important implications for biological theories of tumor growth and the use of mathematical modeling in preclinical anti-cancer drug investigations, but also may assist in defining how mathematical models could serve as potential prognostic tools in the clinic.

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...

Comparing models for growth and management of forest tracts

Treesearch

J.J. Colbert; Michael Schuckers; Desta Fekedulegn

2003-01-01

The Stand Damage Model (SDM) is a PC-based model that is easily installed, calibrated and initialized for use in exploring the future growth and management of forest stands or small wood lots. We compare the basic individual tree growth model incorporated in this model with alternative models that predict the basal area growth of trees. The SDM is a gap-type simulator...

Assessing Potential Climate Change Effects on Loblolly Pine Growth: A Probabilistic Regional Modeling Approach

Treesearch

Peter B. Woodbury; James E. Smith; David A. Weinstein; John A. Laurence

1998-01-01

Most models of the potential effects of climate change on forest growth have produced deterministic predictions. However, there are large uncertainties in data on regional forest condition, estimates of future climate, and quantitative relationships between environmental conditions and forest growth rate. We constructed a new model to analyze these uncertainties...

Western juniper and ponderosa pine ecotonal climate-growth relationships across landscape gradients in southern Oregon

USGS Publications Warehouse

Knutson, K.C.; Pyke, D.A.

2008-01-01

Forecasts of climate change for the Pacific northwestern United States predict warmer temperatures, increased winter precipitation, and drier summers. Prediction of forest growth responses to these climate fluctuations requires identification of climatic variables limiting tree growth, particularly at limits of free species distributions. We addressed this problem at the pine-woodland ecotone using tree-ring data for western juniper (Juniperus occidentalis var. occidentalis Hook.) and ponderosa pine (Pinus ponderosa Dougl. ex Loud.) from southern Oregon. Annual growth chronologies for 1950-2000 were developed for each species at 17 locations. Correlation and linear regression of climate-growth relationships revealed that radial growth in both species is highly dependent on October-June precipitation events that recharge growing season soil water. Mean annual radial growth for the nine driest years suggests that annual growth in both species is more sensitive to drought at lower elevations and sites with steeper slopes and sandy or rocky soils. Future increases in winter precipitation could increase productivity in both species at the pine-woodland ecotone. Growth responses, however, will also likely vary across landscape features, and our findings suggest that heightened sensitivity to future drought periods and increased temperatures in the two species will predominantly occur at lower elevation sites with poor water-holding capacities. ?? 2008 NRC.

Potential effects of climate change on the growth of fishes from different thermal guilds in Lakes Michigan and Huron

USGS Publications Warehouse

Kao, Yu-Chun; Madenjian, Charles P.; Bunnell, David B.; Lofgren, Brent M.; Perroud, Marjorie

2015-01-01

We used a bioenergetics modeling approach to investigate potential effects of climate change on the growth of two economically important native fishes: yellow perch (Perca flavescens), a cool-water fish, and lake whitefish (Coregonus clupeaformis), a cold-water fish, in deep and oligotrophic Lakes Michigan and Huron. For assessing potential changes in fish growth, we contrasted simulated fish growth in the projected future climate regime during the period 2043-2070 under different prey availability scenarios with the simulated growth during the baseline (historical reference) period 1964-1993. Results showed that effects of climate change on the growth of these two fishes are jointly controlled by behavioral thermoregulation and prey availability. With the ability of behavioral thermoregulation, temperatures experienced by yellow perch in the projected future climate regime increased more than those experienced by lake whitefish. Thus simulated future growth decreased more for yellow perch than for lake whitefish under scenarios where prey availability remains constant into the future. Under high prey availability scenarios, simulated future growth of these two fishes both increased but yellow perch could not maintain the baseline efficiency of converting prey consumption into body weight. We contended that thermal guild should not be the only factor used to predict effects of climate change on the growth of a fish, and that ecosystem responses to climate change should be also taken into account.

Effects of temperature and salinity on the growth of Alexandrium (Dinophyceae) isolates from the Salish Sea

PubMed Central

Bill, Brian D.; Moore, Stephanie K.; Hay, Levi R.; Anderson, Donald M.; Trainer, Vera L.

2016-01-01

Toxin-producing blooms of dinoflagellates in the genus Alexandrium have plagued the inhabitants of the Salish Sea for centuries. Yet the environmental conditions that promote accelerated growth of this organism, a producer of paralytic shellfish toxins, is lacking. This study quantitatively determined the growth response of two Alexandrium isolates to a range of temperatures and salinities, factors that will strongly respond to future climate change scenarios. An empirical equation, derived from observed growth rates describing the temperature and salinity dependence of growth, was used to hindcast bloom risk. Hindcasting was achieved by comparing predicted growth rates, calculated from in situ temperature and salinity data from Quartermaster Harbor, with corresponding Alexandrium cell counts and shellfish toxin data. The greatest bloom risk, defined at μ>0.25 d−1, generally occurred from April through November annually; however, growth rates rarely fell below 0.10 d−1. Except for a few occasions, Alexandrium cells were only observed during the periods of highest bloom risk and paralytic shellfish toxins above the regulatory limit always fell within the periods of predicted bloom occurrence. While acknowledging that Alexandrium growth rates are affected by other abiotic and biotic factors, such as grazing pressure and nutrient availability, the use of this empirical growth function to predict higher risk time frames for blooms and toxic shellfish within the Salish Sea provides the groundwork for a more comprehensive biological model of Alexandrium bloom dynamics in the region and will enhance our ability to forecast blooms in the Salish Sea under future climate change scenarios. PMID:27037588

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling.

PubMed

Feng, Xiaohui; Uriarte, María; González, Grizelle; Reed, Sasha; Thompson, Jill; Zimmerman, Jess K; Murphy, Lora

2018-01-01

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here, we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured interannual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including aboveground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate. © 2017 John Wiley & Sons Ltd.

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

USGS Publications Warehouse

Feng, Xiaohui; Uriarte, María; González, Grizelle; Reed, Sasha C.; Thompson, Jill; Zimmerman, Jess K.; Murphy, Lora

2018-01-01

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured inter-annual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including above-ground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.

Physiological attributes of 11 Northwest conifer species

Treesearch

Ronni L. Korol

2001-01-01

The quantitative description and simulation of the fundamental processes that characterize forest growth are increasing in importance in forestry research. Predicting future forest growth, however, is compounded by the various combinations of temperature, humidity, precipitation, and atmospheric carbon dioxide concentration that may occur. One method of integrating new...

The future of satellite remote sensing: A worldwide assessment and prediction

NASA Technical Reports Server (NTRS)

Spann, G. W.

1984-01-01

A frame-work in which to assess and predict the future prospects for satellite remote sensing markets is provided. The scope of the analysis is the satellite-related market for data, equipment, and services. It encompasses both domestic and international markets and contains an examination of the various market characteristics by market segment (e.g., Federal Government, State and Local Governments, Academic Organizations, Industrial Companies, and Individuals) and primary applications areas (e.g., Geology, Forestry, Land Resource Management, Agriculture and Cartography). The forecasts are derived from an analysis of both U.S. and foreign market data. The evolution and current status of U.S. and Foreign markets to arrive at market growth rates is evaluated. Circumstances and events which are likely to affect the future market development are examined. A market growth scenario is presented that is consistent with past data sales trends and takes into account the dynamic nature of the future satellite remote sensing market. Several areas of current and future business opportunities available in this market are discussed. Specific worldwide forecasts are presented in three market sectors for the period 1980 to 1990.

Spatial variability in forest growth—climate relationships in the Olympic Mountains, Washington.

Treesearch

Jill M. Nakawatase; David L. Peterson

2006-01-01

For many Pacific Northwest forests, little is known about the spatial and temporal variability in tree growth - climate relationships, yet it is this information that is needed to predict how forests will respond to future climatic change. We studied the effects of climatic variability on forest growth at 74 plots in the western and northeastern Olympic Mountains....

Physiological and ecological effects of increasing temperature on fish production in lakes of Arctic Alaska

USGS Publications Warehouse

Carey, Michael P.; Zimmerman, Christian E.

2014-01-01

Lake ecosystems in the Arctic are changing rapidly due to climate warming. Lakes are sensitive integrators of climate-induced changes and prominent features across the Arctic landscape, especially in lowland permafrost regions such as the Arctic Coastal Plain of Alaska. Despite many studies on the implications of climate warming, how fish populations will respond to lake changes is uncertain for Arctic ecosystems. Least Cisco (Coregonus sardinella) is a bellwether for Arctic lakes as an important consumer and prey resource. To explore the consequences of climate warming, we used a bioenergetics model to simulate changes in Least Cisco production under future climate scenarios for lakes on the Arctic Coastal Plain. First, we used current temperatures to fit Least Cisco consumption to observed annual growth. We then estimated growth, holding food availability, and then feeding rate constant, for future projections of temperature. Projected warmer water temperatures resulted in reduced Least Cisco production, especially for larger size classes, when food availability was held constant. While holding feeding rate constant, production of Least Cisco increased under all future scenarios with progressively more growth in warmer temperatures. Higher variability occurred with longer projections of time mirroring the expanding uncertainty in climate predictions further into the future. In addition to direct temperature effects on Least Cisco growth, we also considered changes in lake ice phenology and prey resources for Least Cisco. A shorter period of ice cover resulted in increased production, similar to warming temperatures. Altering prey quality had a larger effect on fish production in summer than winter and increased relative growth of younger rather than older age classes of Least Cisco. Overall, we predicted increased production of Least Cisco due to climate warming in lakes of Arctic Alaska. Understanding the implications of increased production of Least Cisco to the entire food web will be necessary to predict ecosystem responses in lakes of the Arctic.

Physiological and ecological effects of increasing temperature on fish production in lakes of Arctic Alaska

PubMed Central

Carey, Michael P; Zimmerman, Christian E

2014-01-01

Lake ecosystems in the Arctic are changing rapidly due to climate warming. Lakes are sensitive integrators of climate-induced changes and prominent features across the Arctic landscape, especially in lowland permafrost regions such as the Arctic Coastal Plain of Alaska. Despite many studies on the implications of climate warming, how fish populations will respond to lake changes is uncertain for Arctic ecosystems. Least Cisco (Coregonus sardinella) is a bellwether for Arctic lakes as an important consumer and prey resource. To explore the consequences of climate warming, we used a bioenergetics model to simulate changes in Least Cisco production under future climate scenarios for lakes on the Arctic Coastal Plain. First, we used current temperatures to fit Least Cisco consumption to observed annual growth. We then estimated growth, holding food availability, and then feeding rate constant, for future projections of temperature. Projected warmer water temperatures resulted in reduced Least Cisco production, especially for larger size classes, when food availability was held constant. While holding feeding rate constant, production of Least Cisco increased under all future scenarios with progressively more growth in warmer temperatures. Higher variability occurred with longer projections of time mirroring the expanding uncertainty in climate predictions further into the future. In addition to direct temperature effects on Least Cisco growth, we also considered changes in lake ice phenology and prey resources for Least Cisco. A shorter period of ice cover resulted in increased production, similar to warming temperatures. Altering prey quality had a larger effect on fish production in summer than winter and increased relative growth of younger rather than older age classes of Least Cisco. Overall, we predicted increased production of Least Cisco due to climate warming in lakes of Arctic Alaska. Understanding the implications of increased production of Least Cisco to the entire food web will be necessary to predict ecosystem responses in lakes of the Arctic. PMID:24963391

Physiological and ecological effects of increasing temperature on fish production in lakes of Arctic Alaska.

PubMed

Carey, Michael P; Zimmerman, Christian E

2014-05-01

Lake ecosystems in the Arctic are changing rapidly due to climate warming. Lakes are sensitive integrators of climate-induced changes and prominent features across the Arctic landscape, especially in lowland permafrost regions such as the Arctic Coastal Plain of Alaska. Despite many studies on the implications of climate warming, how fish populations will respond to lake changes is uncertain for Arctic ecosystems. Least Cisco (Coregonus sardinella) is a bellwether for Arctic lakes as an important consumer and prey resource. To explore the consequences of climate warming, we used a bioenergetics model to simulate changes in Least Cisco production under future climate scenarios for lakes on the Arctic Coastal Plain. First, we used current temperatures to fit Least Cisco consumption to observed annual growth. We then estimated growth, holding food availability, and then feeding rate constant, for future projections of temperature. Projected warmer water temperatures resulted in reduced Least Cisco production, especially for larger size classes, when food availability was held constant. While holding feeding rate constant, production of Least Cisco increased under all future scenarios with progressively more growth in warmer temperatures. Higher variability occurred with longer projections of time mirroring the expanding uncertainty in climate predictions further into the future. In addition to direct temperature effects on Least Cisco growth, we also considered changes in lake ice phenology and prey resources for Least Cisco. A shorter period of ice cover resulted in increased production, similar to warming temperatures. Altering prey quality had a larger effect on fish production in summer than winter and increased relative growth of younger rather than older age classes of Least Cisco. Overall, we predicted increased production of Least Cisco due to climate warming in lakes of Arctic Alaska. Understanding the implications of increased production of Least Cisco to the entire food web will be necessary to predict ecosystem responses in lakes of the Arctic.

Investigating calcite growth rates using a quartz crystal microbalance with dissipation (QCM-D)

NASA Astrophysics Data System (ADS)

Cao, Bo; Stack, Andrew G.; Steefel, Carl I.; DePaolo, Donald J.; Lammers, Laura N.; Hu, Yandi

2018-02-01

Calcite precipitation plays a significant role in processes such as geological carbon sequestration and toxic metal sequestration and, yet, the rates and mechanisms of calcite growth under close to equilibrium conditions are far from well understood. In this study, a quartz crystal microbalance with dissipation (QCM-D) was used for the first time to measure macroscopic calcite growth rates. Calcite seed crystals were first nucleated and grown on sensors, then growth rates of calcite seed crystals were measured in real-time under close to equilibrium conditions (saturation index, SI = log ({Ca2+}/{CO32-}/Ksp) = 0.01-0.7, where {i} represent ion activities and Ksp = 10-8.48 is the calcite thermodynamic solubility constant). At the end of the experiments, total masses of calcite crystals on sensors measured by QCM-D and inductively coupled plasma mass spectrometry (ICP-MS) were consistent, validating the QCM-D measurements. Calcite growth rates measured by QCM-D were compared with reported macroscopic growth rates measured with auto-titration, ICP-MS, and microbalance. Calcite growth rates measured by QCM-D were also compared with microscopic growth rates measured by atomic force microscopy (AFM) and with rates predicted by two process-based crystal growth models. The discrepancies in growth rates among AFM measurements and model predictions appear to mainly arise from differences in step densities, and the step velocities were consistent among the AFM measurements as well as with both model predictions. Using the predicted steady-state step velocity and the measured step densities, both models predict well the growth rates measured using QCM-D and AFM. This study provides valuable insights into the effects of reactive site densities on calcite growth rate, which may help design future growth models to predict transient-state step densities.

Evaluating predictive models for solar energy growth in the US states and identifying the key drivers

NASA Astrophysics Data System (ADS)

Chakraborty, Joheen; Banerji, Sugata

2018-03-01

Driven by a desire to control climate change and reduce the dependence on fossil fuels, governments around the world are increasing the adoption of renewable energy sources. However, among the US states, we observe a wide disparity in renewable penetration. In this study, we have identified and cleaned over a dozen datasets representing solar energy penetration in each US state, and the potentially relevant socioeconomic and other factors that may be driving the growth in solar. We have applied a number of predictive modeling approaches - including machine learning and regression - on these datasets over a 17-year period and evaluated the relative performance of the models. Our goals were: (1) identify the most important factors that are driving the growth in solar, (2) choose the most effective predictive modeling technique for solar growth, and (3) develop a model for predicting next year’s solar growth using this year’s data. We obtained very promising results with random forests (about 90% efficacy) and varying degrees of success with support vector machines and regression techniques (linear, polynomial, ridge). We also identified states with solar growth slower than expected and representing a potential for stronger growth in future.

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.

A nonparametric analysis of plot basal area growth using tree based models

Treesearch

G. L. Gadbury; H. K. lyer; H. T. Schreuder; C. Y. Ueng

1997-01-01

Tree based statistical models can be used to investigate data structure and predict future observations. We used nonparametric and nonlinear models to reexamine the data sets on tree growth used by Bechtold et al. (1991) and Ruark et al. (1991). The growth data were collected by Forest Inventory and Analysis (FIA) teams from 1962 to 1972 (4th cycle) and 1972 to 1982 (...

Chronic warm exposure impairs growth performance and reduces thermal safety margins in the common triplefin fish (Forsterygion lapillum).

PubMed

McArley, Tristan J; Hickey, Anthony J R; Herbert, Neill A

2017-10-01

Intertidal fish species face gradual chronic changes in temperature and greater extremes of acute thermal exposure through climate-induced warming. As sea temperatures rise, it has been proposed that whole-animal performance will be impaired through oxygen and capacity limited thermal tolerance [OCLTT; reduced aerobic metabolic scope (MS)] and, on acute exposure to high temperatures, thermal safety margins may be reduced because of constrained acclimation capacity of upper thermal limits. Using the New Zealand triplefin fish ( Forsterygion lapillum ), this study addressed how performance in terms of growth and metabolism (MS) and upper thermal tolerance limits would be affected by chronic exposure to elevated temperature. Growth was measured in fish acclimated (12 weeks) to present and predicted future temperatures and metabolic rates were then determined in fish at acclimation temperatures and with acute thermal ramping. In agreement with the OCLTT hypothesis, chronic exposure to elevated temperature significantly reduced growth performance and MS. However, despite the prospect of impaired growth performance under warmer future summertime conditions, an annual growth model revealed that elevated temperatures may only shift the timing of high growth potential and not the overall annual growth rate. While the upper thermal tolerance (i.e. critical thermal maxima) increased with exposure to warmer temperatures and was associated with depressed metabolic rates during acute thermal ramping, upper thermal tolerance did not differ between present and predicted future summertime temperatures. This suggests that warming may progressively decrease thermal safety margins for hardy generalist species and could limit the available habitat range of intertidal populations. © 2017. Published by The Company of Biologists Ltd.

Pinus taeda forest growth predictions in the 21st century vary with site mean annual temperature and site quality.

PubMed

Gonzalez-Benecke, Carlos A; Teskey, Robert O; Dinon-Aldridge, Heather; Martin, Timothy A

2017-11-01

Climate projections from 20 downscaled global climate models (GCMs) were used with the 3-PG model to predict the future productivity and water use of planted loblolly pine (Pinus taeda) growing across the southeastern United States. Predictions were made using Representative Concentration Pathways (RCP) 4.5 and 8.5. These represent scenarios in which total radiative forcing stabilizes before 2100 (RCP 4.5) or continues increasing throughout the century (RCP 8.5). Thirty-six sites evenly distributed across the native range of the species were used in the analysis. These sites represent a range in current mean annual temperature (14.9-21.6°C) and precipitation (1,120-1,680 mm/year). The site index of each site, which is a measure of growth potential, was varied to represent different levels of management. The 3-PG model predicted that aboveground biomass growth and net primary productivity will increase by 10%-40% in many parts of the region in the future. At cooler sites, the relative growth increase was greater than at warmer sites. By running the model with the baseline [CO 2 ] or the anticipated elevated [CO 2 ], the effect of CO 2 on growth was separated from that of other climate factors. The growth increase at warmer sites was due almost entirely to elevated [CO 2 ]. The growth increase at cooler sites was due to a combination of elevated [CO 2 ] and increased air temperature. Low site index stands had a greater relative increase in growth under the climate change scenarios than those with a high site index. Water use increased in proportion to increases in leaf area and productivity but precipitation was still adequate, based on the downscaled GCM climate projections. We conclude that an increase in productivity can be expected for a large majority of the planted loblolly pine stands in the southeastern United States during this century. © 2017 John Wiley & Sons Ltd.

Asian Pentecostalism: A Religion Whose Only Limit Is the Sky

ERIC Educational Resources Information Center

Ma, Wonsuk

2004-01-01

The study surveys the current growth of Pentecostal Christianity, as defined broadly, in Asia, particularly in comparison with Latin America and Africa, predicting that the future growth is expected to be exponential. In a brief historical survey, the continent is divided into four categories depending on the beginning and development of…

Forecasting urban growth across the United States-Mexico border

USGS Publications Warehouse

Norman, L.M.; Feller, M.; Phillip, Guertin D.

2009-01-01

The sister-city area of Nogales, Arizona, and Nogales, Sonora, Mexico, is known collectively as Ambos (both) Nogales. This area was historically one city and was administratively divided by the Gadsden Purchase in 1853. These arid-lands have limited and sensitive natural resources. Environmental planning can support sustainable development to accommodate the predicted influx of population. The objective of this research is to quantify the amount of predicted urban growth for the Ambos Nogales watershed to support future planning for sustainable development. Two modeling regimes are explored. Our goal is to identify possible growth patterns associated with the twin-city area as a whole and with the two cities modeled as separate entities. We analyzed the cross-border watershed using regression analysis from satellite images from 1975, 1983, 1996, and 2002 and created urban area classifications. We used these classifications as input to the urban growth model, SLEUTH, to simulate likely patterns of development and define projected conversion probabilities. Model results indicate that the two cities are undergoing very different patterns of change and identify locations of expected growth based on historical development. Growth in Nogales, Arizona is stagnant while the urban area in Nogales, Sonora is exploding. This paper demonstrates an application that portrays how future binational urban growth could develop and affect the environment. This research also provides locations of potential growth for use in city planning.

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

USGS Publications Warehouse

McGowan, Conor P.; Allan, Nathan; Servoss, Jeff; Hedwall, Shaula J.; Wooldridge, Brian

2017-01-01

Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

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.

Modeling urban growth by the use of a multiobjective optimization approach: environmental and economic issues for the Yangtze watershed, China.

PubMed

Zhang, Wenting; Wang, Haijun; Han, Fengxiang; Gao, Juan; Nguyen, Thuminh; Chen, Yarong; Huang, Bo; Zhan, F Benjamin; Zhou, Lequn; Hong, Song

2014-11-01

Urban growth is an unavoidable process caused by economic development and population growth. Traditional urban growth models represent the future urban growth pattern by repeating the historical urban growth regulations, which can lead to a lot of environmental problems. The Yangtze watershed is the largest and the most prosperous economic area in China, and it has been suffering from rapid urban growth from the 1970s. With the built-up area increasing from 23,238 to 31,054 km(2) during the period from 1980 to 2005, the watershed has suffered from serious nonpoint source (NPS) pollution problems, which have been mainly caused by the rapid urban growth. To protect the environment and at the same time maintain the economic development, a multiobjective optimization (MOP) is proposed to tradeoff the multiple objectives during the urban growth process of the Yangtze watershed. In particular, the four objectives of minimization of NPS pollution, maximization of GDP value, minimization of the spatial incompatibility between the land uses, and minimization of the cost of land-use change are considered by the MOP approach. Conventionally, a genetic algorithm (GA) is employed to search the Pareto solution set. In our MOP approach, a two-dimensional GA, rather than the traditional one-dimensional GA, is employed to assist with the search for the spatial optimization solution, where the land-use cells in the two-dimensional space act as genes in the GA. Furthermore, to confirm the superiority of the MOP approach over the traditional prediction approaches, a widely used urban growth prediction model, cellular automata (CA), is also carried out to allow a comparison with the Pareto solution of MOP. The results indicate that the MOP approach can make a tradeoff between the multiple objectives and can achieve an optimal urban growth pattern for Yangtze watershed, while the CA prediction model just represents the historical urban growth pattern as the future growth pattern. Moreover, according to the spatial clustering index, the urban growth pattern predicted through MOP is more reasonable. In summary, the proposed model provides a set of Pareto urban growth solutions, which compromise environmental and economic issues for the Yangtze watershed.

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...

Growth and Yield Predictions for Thinned Stands of Even-aged Natural Longleaf Pine

Treesearch

Robert M. Farrar

1979-01-01

This paper presents a system of equations and resulting tables that can predict stand volumes for thinned natural longleaf pine. The system can predict current and future total stand volume in cubic feet and merchantable stand volume in cubic feet, cords, and board feet. The system also provides for estimating dry-weight production of wood. The system uses input data...

Fine-scale variability in growth-climate relationships of Douglas-fir, North Cascade Range, Washington.

Treesearch

Michael J. Case; David L. Peterson

2005-01-01

Information about the sensitivity to climate of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) is valuable because it will allow forest managers to maximize growth, better understand how carbon sequestration may change over time, and better model and predict future ecosystem responses to climatic change. We examined the effects of climatic...

Back to the future: assessing accuracy and sensitivity of a forest growth model

Treesearch

Susan Hummel; Paul Meznarich

2014-01-01

The Forest Vegetation Simulator (FVS) is a widely used computer model that projects forest growth and predicts the effects of disturbances such as fire, insects, harvests, or disease. Land managers often use these projections to decide among silvicultural options and estimate the potential effects of these options on forest conditions. Despite FVS's popularity,...

Late-successional forests and northern spotted owls: how effective is the Northwest Forest Plan?

Treesearch

Miles Hemstrom; Martin G. Raphael

2000-01-01

This paper describes the late-successional and old-growth forest and the northern spotted owl effectiveness monitoring plans for the Northwest Forest Plan. The effectiveness monitoring plan for late-successional and old-growth forests will track changes in forest spatial distribution, and within-stand structure and composition, and it will predict future trends.

An Examination of Exercise-Induced Feeling States and Their Association With Future Participation in Physical Activity Among Older Adults.

PubMed

Brunet, Jennifer; Guérin, Eva; Speranzini, Nicolas

2018-01-01

Although exercise-induced feeling states may play a role in driving future behavior, their role in relation to older adults' participation in physical activity (PA) has seldom been considered. The objectives of this study were to describe changes in older adults' feeling states during exercise, and examine if levels of and changes in feeling states predicted their future participation in PA. Self-reported data on feeling states were collected from 82 older adults immediately before, during, and after a moderate-intensity exercise session, and on participation in PA 1 month later. Data were analyzed using latent growth modeling. Feelings of revitalization, positive engagement, and tranquility decreased during exercise, whereas feelings of physical exhaustion increased. Feelings of revitalization immediately before the exercise session predicted future participation in PA; changes in feeling states did not. This study does not provide empirical evidence that older adults' exercise-induced feeling states predict their future participation in PA.

Liver-fat and liver-function indices derived from Gd-EOB-DTPA-enhanced liver MRI for prediction of future liver remnant growth after portal vein occlusion.

PubMed

Barth, Borna K; Fischer, Michael A; Kambakamba, Patryk; Lesurtel, Mickael; Reiner, Caecilia S

2016-04-01

To evaluate the use of Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI)-derived fat- and liver function-measurements for prediction of future liver remnant (FLR) growth after portal vein occlusion (PVO) in patients scheduled for major liver resection. Forty-five patients (age, 59 ± 13.9 y) who underwent Gd-EOB-DTPA-enhanced liver MRI within 24 ± 18 days prior to PVO were included in this study. Fat-Signal-Fraction (FSF), relative liver enhancement (RLE) and corrected liver-to-spleen ratio (corrLSR) of the FLR were calculated from in- and out-of-phase (n=42) as well as from unenhanced T1-weighted, and hepatocyte-phase images (n=35), respectively. Kinetic growth rate (KGR, volume increase/week) of the FLR after PVO was the primary endpoint. Receiver operating characteristics analysis was used to determine cutoff values for prediction of impaired FLR-growth. FSF (%) showed significant inverse correlation with KGR (r=-0.41, p=0.008), whereas no significant correlation was found with RLE and corrLSR. FSF was significantly higher in patients with impaired FLR-growth than in those with normal growth (%FSF, 8.1 ± 9.3 vs. 3.0 ± 5.9, p=0.02). ROC-analysis revealed a cutoff-FSF of 4.9% for identification of patients with impaired FLR-growth with a specificity of 82% and sensitivity of 47% (AUC 0.71 [95%CI:0.54-0.87]). Patients with impaired FLR-growth according to the FSF-cutoff showed a tendency towards higher postoperative complication rates (posthepatectomy liver failure in 50% vs. 19%). Liver fat-content, but not liver function derived from Gd-EOB-DTPA-enhanced MRI is a predictor of FLR-growth after PVO. Thus, liver MRI could help in identifying patients at risk for insufficient FLR-growth, who may need re-evaluation of the therapeutic strategy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Estimating root collar diameter growth for multi-stem western woodland tree species on remeasured forest inventory and analysis plots

Treesearch

Michael T. Thompson; Maggie. Toone

2012-01-01

Tree diameter growth models are widely used in many forestry applications, often to predict tree size at a future point in time. Also, there are instances where projections of past diameters are needed. An individual tree model has been developed to estimate diameter growth of multi-stem woodland tree species where the diameter is measured at root collar. The model was...

The Work, the Workplace, and the Work Force of Tomorrow.

ERIC Educational Resources Information Center

Allen, Claudia

1995-01-01

Ann McLaughlin, a former secretary of labor, discusses her views on the future of the workplace. She feels that to solve the impending problem of educational deficits among the work force, employers will begin their own educational programs, improving both employee loyalty and work force mobility. Includes predictions for future growth fields.…

Land use planning and wildfire: development policies influence future probability of housing loss

USGS Publications Warehouse

Syphard, Alexandra D.; Massada, Avi Bar; Butsic, Van; Keeley, Jon E.

2013-01-01

Increasing numbers of homes are being destroyed by wildfire in the wildland-urban interface. With projections of climate change and housing growth potentially exacerbating the threat of wildfire to homes and property, effective fire-risk reduction alternatives are needed as part of a comprehensive fire management plan. Land use planning represents a shift in traditional thinking from trying to eliminate wildfires, or even increasing resilience to them, toward avoiding exposure to them through the informed placement of new residential structures. For land use planning to be effective, it needs to be based on solid understanding of where and how to locate and arrange new homes. We simulated three scenarios of future residential development and projected landscape-level wildfire risk to residential structures in a rapidly urbanizing, fire-prone region in southern California. We based all future development on an econometric subdivision model, but we varied the emphasis of subdivision decision-making based on three broad and common growth types: infill, expansion, and leapfrog. Simulation results showed that decision-making based on these growth types, when applied locally for subdivision of individual parcels, produced substantial landscape-level differences in pattern, location, and extent of development. These differences in development, in turn, affected the area and proportion of structures at risk from burning in wildfires. Scenarios with lower housing density and larger numbers of small, isolated clusters of development, i.e., resulting from leapfrog development, were generally predicted to have the highest predicted fire risk to the largest proportion of structures in the study area, and infill development was predicted to have the lowest risk. These results suggest that land use planning should be considered an important component to fire risk management and that consistently applied policies based on residential pattern may provide substantial benefits for future risk reduction.

A new algorithm for stand table projection models.

Treesearch

Quang V. Cao; V. Clark Baldwin

1999-01-01

The constrained least squares method is proposed as an algorithm for projecting stand tables through time. This method consists of three steps: (1) predict survival in each diameter class, (2) predict diameter growth, and (3) use the least squares approach to adjust the stand table to satisfy the constraints of future survival, average diameter, and stand basal area....

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.

The Uniform Pattern of Growth and Skeletal Maturation during the Human Adolescent Growth Spurt.

PubMed

Sanders, James O; Qiu, Xing; Lu, Xiang; Duren, Dana L; Liu, Raymond W; Dang, Debbie; Menendez, Mariano E; Hans, Sarah D; Weber, David R; Cooperman, Daniel R

2017-12-01

Humans are one of the few species undergoing an adolescent growth spurt. Because children enter the spurt at different ages making age a poor maturity measure, longitudinal studies are necessary to identify the growth patterns and identify commonalities in adolescent growth. The standard maturity determinant, peak height velocity (PHV) timing, is difficult to estimate in individuals due to diurnal, postural, and measurement variation. Using prospective longitudinal populations of healthy children from two North American populations, we compared the timing of the adolescent growth spurt's peak height velocity to normalized heights and hand skeletal maturity radiographs. We found that in healthy children, the adolescent growth spurt is standardized at 90% of final height with similar patterns for children of both sexes beginning at the initiation of the growth spurt. Once children enter the growth spurt, their growth pattern is consistent between children with peak growth at 90% of final height and skeletal maturity closely reflecting growth remaining. This ability to use 90% of final height as easily identified important maturity standard with its close relationship to skeletal maturity represents a significant advance allowing accurate prediction of future growth for individual children and accurate maturity comparisons for future studies of children's growth.

Development of a hybrid modeling approach for predicting intensively managed Douglas-fir growth at multiple scales.

Treesearch

A. Weiskittel; D. Maguire; R. Monserud

2007-01-01

Hybrid models offer the opportunity to improve future growth projections by combining advantages of both empirical and process-based modeling approaches. Hybrid models have been constructed in several regions and their performance relative to a purely empirical approach has varied. A hybrid model was constructed for intensively managed Douglas-fir plantations in the...

Biophysical modelling of intra-ring variations in tracheid features and wood density of Pinus pinaster trees exposed to seasonal droughts

Treesearch

Sarah Wilkinson; Jerome Ogee; Jean-Christophe Domec; Mark Rayment; Lisa Wingate

2015-01-01

Process-based models that link seasonally varying environmental signals to morphological features within tree rings are essential tools to predict tree growth response and commercially important wood quality traits under future climate scenarios. This study evaluated model portrayal of radial growth and wood anatomy observations within a mature maritime pine (Pinus...

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.

Women with Ovarian Cancer: Examining the Role of Social Support and Rumination in Posttraumatic Growth, Psychological Distress, and Psychological Well-being.

PubMed

Hill, Erin M; Watkins, Kaitlin

2017-03-01

The present study examined the role of social support and rumination (deliberate vs. intrusive) in posttraumatic growth (PTG), psychological distress (PD), and psychological well-being (PWB) among women with ovarian cancer. Sixty-seven women who had experienced ovarian cancer were recruited through social media and cancer-related websites, and completed an online survey. Contrary to hypotheses, results indicated that social support was not predictive of PTG, and the mediation of rumination was not significant in the regression of social support on PTG. Social support was, however, positively correlated with the Relating to Others domain of PTG. Deliberate rumination was positively predictive of PTG, and intrusive rumination was positively predictive of PD and negatively predictive of PWB. Social support was negatively predictive of PD, and positively predictive of PWB. Results are discussed with reference to clinical implications and future research needed in understanding the ovarian cancer experience.

Reliability Growth and Its Applications to Dormant Reliability

DTIC Science & Technology

1981-12-01

ability to make projection about future reli- ability (Rof 9:41-42). Barlow and Scheuer Model. Richard E. Barlow and Ernest M. Sch~uvr, of the University...Reliability Growth Prediction Models," Operations Research, 18(l):S2-6S (January/February 1970). 7. Bauer, John, William Hadley, and Robert Dietz... Texarkana , Texas, May 1973. (AD 768 119). 10. Bonis, Austin J. "Reliability Growth Curves for One Shot Devices," Proceedings 1977 Annual Reliability and

NASA Earth Science Research Results for Improved Regional Crop Yield Prediction

NASA Astrophysics Data System (ADS)

Mali, P.; O'Hara, C. G.; Shrestha, B.; Sinclair, T. R.; G de Goncalves, L. G.; Salado Navarro, L. R.

2007-12-01

National agencies such as USDA Foreign Agricultural Service (FAS), Production Estimation and Crop Assessment Division (PECAD) work specifically to analyze and generate timely crop yield estimates that help define national as well as global food policies. The USDA/FAS/PECAD utilizes a Decision Support System (DSS) called CADRE (Crop Condition and Data Retrieval Evaluation) mainly through an automated database management system that integrates various meteorological datasets, crop and soil models, and remote sensing data; providing significant contribution to the national and international crop production estimates. The "Sinclair" soybean growth model has been used inside CADRE DSS as one of the crop models. This project uses Sinclair model (a semi-mechanistic crop growth model) for its potential to be effectively used in a geo-processing environment with remote-sensing-based inputs. The main objective of this proposed work is to verify, validate and benchmark current and future NASA earth science research results for the benefit in the operational decision making process of the PECAD/CADRE DSS. For this purpose, the NASA South American Land Data Assimilation System (SALDAS) meteorological dataset is tested for its applicability as a surrogate meteorological input in the Sinclair model meteorological input requirements. Similarly, NASA sensor MODIS products is tested for its applicability in the improvement of the crop yield prediction through improving precision of planting date estimation, plant vigor and growth monitoring. The project also analyzes simulated Visible/Infrared Imager/Radiometer Suite (VIIRS, a future NASA sensor) vegetation product for its applicability in crop growth prediction to accelerate the process of transition of VIIRS research results for the operational use of USDA/FAS/PECAD DSS. The research results will help in providing improved decision making capacity to the USDA/FAS/PECAD DSS through improved vegetation growth monitoring from high spatial and temporal resolution remote sensing datasets; improved time-series meteorological inputs required for crop growth models; and regional prediction capability through geo-processing-based yield modeling.

Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models

USGS Publications Warehouse

Tipton, John; Hooten, Mevin B.; Pederson, Neil; Tingley, Martin; Bishop, Daniel

2016-01-01

Reconstruction of pre-instrumental, late Holocene climate is important for understanding how climate has changed in the past and how climate might change in the future. Statistical prediction of paleoclimate from tree ring widths is challenging because tree ring widths are a one-dimensional summary of annual growth that represents a multi-dimensional set of climatic and biotic influences. We develop a Bayesian hierarchical framework using a nonlinear, biologically motivated tree ring growth model to jointly reconstruct temperature and precipitation in the Hudson Valley, New York. Using a common growth function to describe the response of a tree to climate, we allow for species-specific parameterizations of the growth response. To enable predictive backcasts, we model the climate variables with a vector autoregressive process on an annual timescale coupled with a multivariate conditional autoregressive process that accounts for temporal correlation and cross-correlation between temperature and precipitation on a monthly scale. Our multi-scale temporal model allows for flexibility in the climate response through time at different temporal scales and predicts reasonable climate scenarios given tree ring width data.

FutureTox II: In vitro Data and In Silico Models for Predictive Toxicology

PubMed Central

Knudsen, Thomas B.; Keller, Douglas A.; Sander, Miriam; Carney, Edward W.; Doerrer, Nancy G.; Eaton, David L.; Fitzpatrick, Suzanne Compton; Hastings, Kenneth L.; Mendrick, Donna L.; Tice, Raymond R.; Watkins, Paul B.; Whelan, Maurice

2015-01-01

FutureTox II, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in January, 2014. The meeting goals were to review and discuss the state of the science in toxicology in the context of implementing the NRC 21st century vision of predicting in vivo responses from in vitro and in silico data, and to define the goals for the future. Presentations and discussions were held on priority concerns such as predicting and modeling of metabolism, cell growth and differentiation, effects on sensitive subpopulations, and integrating data into risk assessment. Emerging trends in technologies such as stem cell-derived human cells, 3D organotypic culture models, mathematical modeling of cellular processes and morphogenesis, adverse outcome pathway development, and high-content imaging of in vivo systems were discussed. Although advances in moving towards an in vitro/in silico based risk assessment paradigm were apparent, knowledge gaps in these areas and limitations of technologies were identified. Specific recommendations were made for future directions and research needs in the areas of hepatotoxicity, cancer prediction, developmental toxicity, and regulatory toxicology. PMID:25628403

Harnessing the landscape of microbial culture media to predict new organism–media pairings

PubMed Central

Oberhardt, Matthew A.; Zarecki, Raphy; Gronow, Sabine; Lang, Elke; Klenk, Hans-Peter; Gophna, Uri; Ruppin, Eytan

2015-01-01

Culturing microorganisms is a critical step in understanding and utilizing microbial life. Here we map the landscape of existing culture media by extracting natural-language media recipes into a Known Media Database (KOMODO), which includes >18,000 strain–media combinations, >3300 media variants and compound concentrations (the entire collection of the Leibniz Institute DSMZ repository). Using KOMODO, we show that although media are usually tuned for individual strains using biologically common salts, trace metals and vitamins/cofactors are the most differentiating components between defined media of strains within a genus. We leverage KOMODO to predict new organism–media pairings using a transitivity property (74% growth in new in vitro experiments) and a phylogeny-based collaborative filtering tool (83% growth in new in vitro experiments and stronger growth on predicted well-scored versus poorly scored media). These resources are integrated into a web-based platform that predicts media given an organism's 16S rDNA sequence, facilitating future cultivation efforts. PMID:26460590

Forecast of Future Aviation Fuels. Part 1: Scenarios

NASA Technical Reports Server (NTRS)

English, J. M.; Liu, C. Y.; Smith, J. L.; Yin, A. K. K.; Pan, G. A.; Ayati, M. B.; Gyamfi, M.; Arabzadah, M. R.

1978-01-01

A preliminary set of scenarios is described for depicting the air transport industry as it grows and changes, up to the year 2025. This provides the background for predicting the needs for future aviation fuels to meet the requirements of the industry as new basic sources, such as oil shale and coal, which are utilized to supplement petroleum. Five scenarios are written to encompass a range of futures from a serious resource-constrained economy to a continuous and optimistic economic growth. A unique feature is the choice of one immediate range scenario which is based on a serious interruption of economic growth occasioned by an energy shortfall. This is presumed to occur due to lags in starting a synfuels program.

Modelling urban growth in the Indo-Gangetic plain using nighttime OLS data and cellular automata

NASA Astrophysics Data System (ADS)

Roy Chowdhury, P. K.; Maithani, Sandeep

2014-12-01

The present study demonstrates the applicability of the Operational Linescan System (OLS) sensor in modelling urban growth at regional level. The nighttime OLS data provides an easy, inexpensive way to map urban areas at a regional scale, requiring a very small volume of data. A cellular automata (CA) model was developed for simulating urban growth in the Indo-Gangetic plain; using OLS data derived maps as input. In the proposed CA model, urban growth was expressed in terms of causative factors like economy, topography, accessibility and urban infrastructure. The model was calibrated and validated based on OLS data of year 2003 and 2008 respectively using spatial metrics measures and subsequently the urban growth was predicted for the year 2020. The model predicted high urban growth in North Western part of the study area, in south eastern part growth would be concentrated around two cities, Kolkata and Howrah. While in the middle portion of the study area, i.e., Jharkhand, Bihar and Eastern Uttar Pradesh, urban growth has been predicted in form of clusters, mostly around the present big cities. These results will not only provide an input to urban planning but can also be utilized in hydrological and ecological modelling which require an estimate of future built up areas especially at regional level.

Localized delivery of growth factors for periodontal tissue regeneration: role, strategies, and perspectives.

PubMed

Chen, Fa-Ming; Shelton, Richard M; Jin, Yan; Chapple, Iain L C

2009-05-01

Difficulties associated with achieving predictable periodontal regeneration, means that novel techniques need to be developed in order to regenerate the extensive soft and hard tissue destruction that results from periodontitis. Localized delivery of growth factors to the periodontium is an emerging and versatile therapeutic approach, with the potential to become a powerful tool in future regenerative periodontal therapy. Optimized delivery regimes and well-defined release kinetics appear to be logical prerequisites for safe and efficacious clinical application of growth factors and to avoid unwanted side effects and toxicity. While adequate concentrations of growth factor(s) need to be appropriately localized, delivery vehicles are also expected to possess properties such as protein protection, precision in controlled release, biocompatibility and biodegradability, self-regulated therapeutic activity, potential for multiple delivery, and good cell/tissue penetration. Here, current knowledge, recent advances, and future possibilities of growth factor delivery strategies are outlined for periodontal regeneration. First, the role of those growth factors that have been implicated in the periodontal healing/regeneration process, general requirements for their delivery, and the different material types available are described. A detailed discussion follows of current strategies for the selection of devices for localized growth factor delivery, with particular emphasis placed upon their advantages and disadvantages and future prospects for ongoing studies in reconstructing the tooth supporting apparatus.

Adaptive reproduction schedule as a cause of worker policing in social hymenoptera: a dynamic game analysis.

PubMed

Ohtsuki, Hisashi; Tsuji, Kazuki

2009-06-01

Evolutionary theories predict conflicts over sex allocation, male parentage, and reproductive allocation in hymenopteran societies. However, no theory to date has considered the evolution when a colony faces these three conflicts simultaneously. We tackled this issue by developing a dynamic game model, focusing especially on worker policing. Whereas a Nash equilibrium predicts male parentage patterns that are basically the same as those of relatedness-based worker-policing theory (queen multiple mating impedes worker reproduction), we also show the potential for worker policing under queen single mating. Worker policing will depend on the stage of colony growth that is caused by interaction with reproductive allocation conflict or a trade-off between current and future reproduction. Male production at an early stage greatly hinders the growth of the work force and undermines future inclusive fitness of colony members, leading to worker policing at the ergonomic stage. This new mechanism can explain much broader ranges of existing worker-policing behavior than that predicted from relatedness. Predictions differ in many respects from those of models assuming operation of only one or two of the three conflicts, suggesting the importance of interactions among conflicts.

Effects of arbuscular mycorrhizal fungi and soil nutrient addition on the growth of Phragmites australis under different drying-rewetting cycles.

PubMed

Liang, Jin-Feng; An, Jing; Gao, Jun-Qin; Zhang, Xiao-Ya; Yu, Fei-Hai

2018-01-01

The frequency of soil drying-rewetting cycles is predicted to increase under future global climate change, and arbuscular mycorrhizal fungi (AMF) are symbiotic with most plants. However, it remains unknown how AMF affect plant growth under different frequencies of soil drying-rewetting cycles. We subjected a clonal wetland plant Phragmites australis to three frequencies of drying-rewetting cycles (1, 2, or 4 cycles), two nutrient treatments (with or without), and two AMF treatments (with or without) for 64 days. AMF promoted the growth of P. australis, especially in the 2 cycles of the drying-rewetting treatment. AMF had a significant positive effect on leaf mass and number of ramets in the 2 cycles of the drying-rewetting treatment with nutrient addition. In the 2 cycles of drying-rewetting treatment without nutrient addition, AMF increased leaf area and decreased belowground to aboveground biomass ratio. These results indicate that AMF may assist P. australis in coping with medium frequency of drying-rewetting cycles, and provide theoretical guidance for predicting how wetland plants respond to future global climate change.

Effects of ocean acidification and sea-level rise on coral reefs

USGS Publications Warehouse

Yates, K.K.; Moyer, R.P.

2010-01-01

U.S. Geological Survey (USGS) scientists are developing comprehensive records of historical and modern coral reef growth and calcification rates relative to changing seawater chemistry resulting from increasing atmospheric CO2 from the pre-industrial period to the present. These records will provide the scientific foundation for predicting future impacts of ocean acidification and sea-level rise on coral reef growth. Changes in coral growth rates in response to past changes in seawater pH are being examined by using cores from coral colonies.

Coupling urban growth scenarios with nearshore biophysical change models to inform coastal restoration planning in Puget Sound, Washington

NASA Astrophysics Data System (ADS)

Byrd, K. B.; Kreitler, J.; Labiosa, W.

2010-12-01

A scenario represents an account of a plausible future given logical assumptions about how conditions change over discrete bounds of space and time. Development of multiple scenarios provides a means to identify alternative directions of urban growth that account for a range of uncertainty in human behavior. Interactions between human and natural processes may be studied by coupling urban growth scenario outputs with biophysical change models; if growth scenarios encompass a sufficient range of alternative futures, scenario assumptions serve to constrain the uncertainty of biophysical models. Spatially explicit urban growth models (map-based) produce output such as distributions and densities of residential or commercial development in a GIS format that can serve as input to other models. Successful fusion of growth model outputs with other model inputs requires that both models strategically address questions of interest, incorporate ecological feedbacks, and minimize error. The U.S. Geological Survey (USGS) Puget Sound Ecosystem Portfolio Model (PSEPM) is a decision-support tool that supports land use and restoration planning in Puget Sound, Washington, a 35,500 sq. km region. The PSEPM couples future scenarios of urban growth with statistical, process-based and rule-based models of nearshore biophysical changes and ecosystem services. By using a multi-criteria approach, the PSEPM identifies cross-system and cumulative threats to the nearshore environment plus opportunities for conservation and restoration. Sub-models that predict changes in nearshore biophysical condition were developed and existing models were integrated to evaluate three growth scenarios: 1) Status Quo, 2) Managed Growth, and 3) Unconstrained Growth. These decadal scenarios were developed and projected out to 2060 at Oregon State University using the GIS-based ENVISION model. Given land management decisions and policies under each growth scenario, the sub-models predicted changes in 1) fecal coliform in shellfish growing areas, 2) sediment supply to beaches, 3) State beach recreational visits, 4) eelgrass habitat suitability, 5) forage fish habitat suitability, and 6) nutrient loadings. In some cases thousands of shoreline units were evaluated with multiple predictive models, creating a need for streamlined and consistent database development and data processing. Model development over multiple disciplines demonstrated the challenge of merging data types from multiple sources that were inconsistent in spatial and temporal resolution, classification schemes, and topology. Misalignment of data in space and time created potential for error and misinterpretation of results. This effort revealed that the fusion of growth scenarios and biophysical models requires an up-front iterative adjustment of both scenarios and models so that growth model outputs provide the needed input data in the correct format. Successful design of data flow across models that includes feedbacks between human and ecological systems was found to enhance the use of the final data product for decision making.

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.

Modeling and predicting urban growth pattern of the Tokyo metropolitan area based on cellular automata

NASA Astrophysics Data System (ADS)

Zhao, Yaolong; Zhao, Junsan; Murayama, Yuji

2008-10-01

The period of high economic growth in Japan which began in the latter half of the 1950s led to a massive migration of population from rural regions to the Tokyo metropolitan area. This phenomenon brought about rapid urban growth and urban structure changes in this area. Purpose of this study is to establish a constrained CA (Cellular Automata) model with GIS (Geographical Information Systems) to simulate urban growth pattern in the Tokyo metropolitan area towards predicting urban form and landscape for the near future. Urban land-use is classified into multi-categories for interpreting the effect of interaction among land-use categories in the spatial process of urban growth. Driving factors of urban growth pattern, such as land condition, railway network, land-use zoning, random perturbation, and neighborhood interaction and so forth, are explored and integrated into this model. These driving factors are calibrated based on exploratory spatial data analysis (ESDA), spatial statistics, logistic regression, and "trial and error" approach. The simulation is assessed at both macro and micro classification levels in three ways: visual approach; fractal dimension; and spatial metrics. Results indicate that this model provides an effective prototype to simulate and predict urban growth pattern of the Tokyo metropolitan area.

Paths to future growth in photovoltaics manufacturing

DOE PAGES

Basore, Paul A.

2016-03-01

The past decade has seen rapid growth in the photovoltaics industry, followed in the past few years by a period of much slower growth. A simple model that is consistent with this historical record can be used to predict the future evolution of the industry. Two key parameters are identified that determine the outcome. One is the annual global investment in manufacturing capacity normalized to the manufacturing capacity for the previous year (capacity-normalized capital investment rate, CapIR, units dollar/W). The other is how much capital investment is required for each watt of annual manufacturing capacity, normalized to the service lifemore » of the assets (capacity-normalized capital demand rate, CapDR, units dollar/W). If these two parameters remain unchanged from the values they have held for the past few years, global manufacturing capacity will peak in the next few years and then decline. However, it only takes a modest improvement in CapIR to ensure future growth in photovoltaics. Here, several approaches are presented that can enable the required improvement in CapIR. If, in addition, there is an accompanying improvement in CapDR, the rate of growth can be substantially accelerated.« less

Revising the economic imperative for US STEM education.

PubMed

Donovan, Brian M; Moreno Mateos, David; Osborne, Jonathan F; Bisaccio, Daniel J

2014-01-01

Over the last decade macroeconomic studies have established a clear link between student achievement on science and math tests and per capita gross domestic product (GDP) growth, supporting the widely held belief that science, technology, engineering, and math(STEM) education are important factors in the production of economic prosperity. We critique studies that use science and math tests to predict GDP growth, arguing that estimates of the future economic value of STEM education involve substantial speculation because they ignore the impacts of economic growth on biodiversity and ecosystem functionality, which, in the long-term, limit the potential for future economic growth. Furthermore, we argue that such ecological impacts can be enabled by STEM education. Therefore, we contend that the real economic imperative for the STEM pipeline is not just raising standardized test scores, but also empowering students to assess, preserve, and restore ecosystems in order to reduce ecological degradation and increase economic welfare.

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...

Air cargo market outlook and impact via the NASA CLASS project. [Cargo/Logistics Airlift Systems Study

NASA Technical Reports Server (NTRS)

Winston, M. M.; Conner, D. W.

1980-01-01

An overview is given of the Cargo/Logistics Airlift Systems Study (CLASS) project which was a 10 man-year effort carried out by two contractor teams, aimed at defining factors impacting future system growth and obtaining market requirements and design guidelines for future air freighters. Growth projection was estimated by two approaches: one, an optimal systems approach with a more efficient and cost effective system considered as being available in 1990; and the other, an evolutionary approach with an econometric behavior model used to predict long term evolution from the present system. Both approaches predict significant growth in demand for international air freighter services and less growth for U.S. domestic services. Economic analysis of air freighter fleet options indicate very strong market appeal of derivative widebody transports in 1990 with little incentive to develop all new dedicated air freighters utilizing the 1990's technology until sometime beyond the year 2000. Advanced air freighters would be economically attractive for a wide range of payload sizes (to 500 metric tons), however, if a government would share in the RD and T costs by virtue of its needs for a slightly modified version of a civil air freighter design (a.g. military airlifter).

Contribution of air conditioning adoption to future energy use under global warming.

PubMed

Davis, Lucas W; Gertler, Paul J

2015-05-12

As household incomes rise around the world and global temperatures go up, the use of air conditioning is poised to increase dramatically. Air conditioning growth is expected to be particularly strong in middle-income countries, but direct empirical evidence is scarce. In this paper we use high-quality microdata from Mexico to describe the relationship between temperature, income, and air conditioning. We describe both how electricity consumption increases with temperature given current levels of air conditioning, and how climate and income drive air conditioning adoption decisions. We then combine these estimates with predicted end-of-century temperature changes to forecast future energy consumption. Under conservative assumptions about household income, our model predicts near-universal saturation of air conditioning in all warm areas within just a few decades. Temperature increases contribute to this surge in adoption, but income growth by itself explains most of the increase. What this will mean for electricity consumption and carbon dioxide emissions depends on the pace of technological change. Continued advances in energy efficiency or the development of new cooling technologies could reduce the energy consumption impacts. Similarly, growth in low-carbon electricity generation could mitigate the increases in carbon dioxide emissions. However, the paper illustrates the enormous potential impacts in this sector, highlighting the importance of future research on adaptation and underscoring the urgent need for global action on climate change.

Contribution of air conditioning adoption to future energy use under global warming

PubMed Central

Davis, Lucas W.; Gertler, Paul J.

2015-01-01

As household incomes rise around the world and global temperatures go up, the use of air conditioning is poised to increase dramatically. Air conditioning growth is expected to be particularly strong in middle-income countries, but direct empirical evidence is scarce. In this paper we use high-quality microdata from Mexico to describe the relationship between temperature, income, and air conditioning. We describe both how electricity consumption increases with temperature given current levels of air conditioning, and how climate and income drive air conditioning adoption decisions. We then combine these estimates with predicted end-of-century temperature changes to forecast future energy consumption. Under conservative assumptions about household income, our model predicts near-universal saturation of air conditioning in all warm areas within just a few decades. Temperature increases contribute to this surge in adoption, but income growth by itself explains most of the increase. What this will mean for electricity consumption and carbon dioxide emissions depends on the pace of technological change. Continued advances in energy efficiency or the development of new cooling technologies could reduce the energy consumption impacts. Similarly, growth in low-carbon electricity generation could mitigate the increases in carbon dioxide emissions. However, the paper illustrates the enormous potential impacts in this sector, highlighting the importance of future research on adaptation and underscoring the urgent need for global action on climate change. PMID:25918391

The Geology of the Florida Keys.

ERIC Educational Resources Information Center

Shinn, Eugene A.

1988-01-01

Describes some of the ancient geologic history of the Florida Keys from Key Largo to Key West including the effects of glaciers, sea level rise, reef distribution, spurs and grooves, backstepping and ecological zonation, growth rates and erosion. Predicts future changes in this area. (CW)

Predicting future staffing needs at teaching hospitals: use of an analytical program with multiple variables.

PubMed

Mitchell, Christine C; Ashley, Stanley W; Zinner, Michael J; Moore, Francis D

2007-04-01

To develop a model to predict future staffing for the surgery service at a teaching hospital. Tertiary hospital. A computer model with potential future variables was constructed. Some of the variables were distribution of resident staff, fellows, and physician extenders; salary/wages; work hours; educational value of rotations; work units, inpatient wards, and clinics; future volume growth; and efficiency savings. Outcomes Number of staff to be hired, staffing expense, and educational impact. On a busy general surgery service, we estimated the impact of changes in resident work hours, service growth, and workflow efficiency in the next 5 years. Projecting a reduction in resident duty hours to 60 hours per week will require the hiring of 10 physician assistants at a cost of $1 134 000, a cost that is increased by $441 000 when hiring hospitalists instead. Implementing a day of didactic and simulator time (10 hours) will further increase the costs by $568 000. A 10% improvement in the efficiency of floor care, as might be gained by advanced information technology capability or by regionalization of patients, can mitigate these expenses by as much as 21%. On the other hand, a modest annual growth of 2% will increase the costs by $715 000 to $2 417 000. To simply replace residents with alternative providers requires large amounts of human and fiscal capital. The potential for simple efficiencies to mitigate some of this expense suggests that traditional patterns of care in teaching hospitals will have to change in response to educational mandates.

Land Use Planning and Wildfire: Development Policies Influence Future Probability of Housing Loss

PubMed Central

Syphard, Alexandra D.; Bar Massada, Avi; Butsic, Van; Keeley, Jon E.

2013-01-01

Increasing numbers of homes are being destroyed by wildfire in the wildland-urban interface. With projections of climate change and housing growth potentially exacerbating the threat of wildfire to homes and property, effective fire-risk reduction alternatives are needed as part of a comprehensive fire management plan. Land use planning represents a shift in traditional thinking from trying to eliminate wildfires, or even increasing resilience to them, toward avoiding exposure to them through the informed placement of new residential structures. For land use planning to be effective, it needs to be based on solid understanding of where and how to locate and arrange new homes. We simulated three scenarios of future residential development and projected landscape-level wildfire risk to residential structures in a rapidly urbanizing, fire-prone region in southern California. We based all future development on an econometric subdivision model, but we varied the emphasis of subdivision decision-making based on three broad and common growth types: infill, expansion, and leapfrog. Simulation results showed that decision-making based on these growth types, when applied locally for subdivision of individual parcels, produced substantial landscape-level differences in pattern, location, and extent of development. These differences in development, in turn, affected the area and proportion of structures at risk from burning in wildfires. Scenarios with lower housing density and larger numbers of small, isolated clusters of development, i.e., resulting from leapfrog development, were generally predicted to have the highest predicted fire risk to the largest proportion of structures in the study area, and infill development was predicted to have the lowest risk. These results suggest that land use planning should be considered an important component to fire risk management and that consistently applied policies based on residential pattern may provide substantial benefits for future risk reduction. PMID:23977120

Predictive biomarkers of sorafenib efficacy in advanced hepatocellular carcinoma: Are we getting there?

PubMed Central

Shao, Yu-Yun; Hsu, Chih-Hung; Cheng, Ann-Lii

2015-01-01

Sorafenib is the current standard treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is modest with low response rates and short response duration. Predictive biomarkers for sorafenib efficacy are necessary. However, efforts to determine biomarkers for sorafenib have led only to potential candidates rather than clinically useful predictors. Studies based on patient cohorts identified the potential of blood levels of angiopoietin-2, hepatocyte growth factor, insulin-like growth factor-1, and transforming growth factor-β1 for predicting sorafenib efficacy. Alpha-fetoprotein response, dynamic contrast-enhanced magnetic resonance imaging, and treatment-related side effects may serve as early surrogate markers. Novel approaches based on super-responders or experimental mouse models may provide new directions in biomarker research. These studies identified tumor amplification of FGF3/FGF4 or VEGFA and tumor expression of phospho-Mapk14 and phospho-Atf2 as possible predictive markers that await validation. A group effort that considers various prognostic factors and proper collection of tumor tissues before treatment is imperative for the success of future biomarker research in advanced HCC. PMID:26420960

Predictive biomarkers of sorafenib efficacy in advanced hepatocellular carcinoma: Are we getting there?

PubMed

Shao, Yu-Yun; Hsu, Chih-Hung; Cheng, Ann-Lii

2015-09-28

Sorafenib is the current standard treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is modest with low response rates and short response duration. Predictive biomarkers for sorafenib efficacy are necessary. However, efforts to determine biomarkers for sorafenib have led only to potential candidates rather than clinically useful predictors. Studies based on patient cohorts identified the potential of blood levels of angiopoietin-2, hepatocyte growth factor, insulin-like growth factor-1, and transforming growth factor-β1 for predicting sorafenib efficacy. Alpha-fetoprotein response, dynamic contrast-enhanced magnetic resonance imaging, and treatment-related side effects may serve as early surrogate markers. Novel approaches based on super-responders or experimental mouse models may provide new directions in biomarker research. These studies identified tumor amplification of FGF3/FGF4 or VEGFA and tumor expression of phospho-Mapk14 and phospho-Atf2 as possible predictive markers that await validation. A group effort that considers various prognostic factors and proper collection of tumor tissues before treatment is imperative for the success of future biomarker research in advanced HCC.

Modeling Forest Biomass and Growth: Coupling Long-Term Inventory and Lidar Data

NASA Technical Reports Server (NTRS)

Babcock, Chad; Finley, Andrew O.; Cook, Bruce D.; Weiskittel, Andrew; Woodall, Christopher W.

2016-01-01

Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB growth using LiDAR data. The proposed model accommodates temporal misalignment between field measurements and remotely sensed data-a problem pervasive in such settings-by including multiple time-indexed measurements at plot locations to estimate AGB growth. We pursue a Bayesian modeling framework that allows for appropriately complex parameter associations and uncertainty propagation through to prediction. Specifically, we identify a space-varying coefficients model to predict and map AGB and its associated growth simultaneously. The proposed model is assessed using LiDAR data acquired from NASA Goddard's LiDAR, Hyper-spectral & Thermal imager and field inventory data from the Penobscot Experimental Forest in Bradley, Maine. The proposed model outperformed the time-invariant counterpart models in predictive performance as indicated by a substantial reduction in root mean squared error. The proposed model adequately accounts for temporal misalignment through the estimation of forest AGB growth and accommodates residual spatial dependence. Results from this analysis suggest that future AGB models informed using remotely sensed data, such as LiDAR, may be improved by adapting traditional modeling frameworks to account for temporal misalignment and spatial dependence using random effects.

How do attachment dimensions affect bereavement adjustment? A mediation model of continuing bonds.

PubMed

Yu, Wei; He, Li; Xu, Wei; Wang, Jianping; Prigerson, Holly G

2016-04-30

The current study aims to examine mechanisms underlying the impact of attachment dimensions on bereavement adjustment. Bereaved mainland Chinese participants (N=247) completed anonymous, retrospective, self-report surveys assessing attachment dimensions, continuing bonds (CB), grief symptoms and posttraumatic growth (PTG). Results demonstrated that attachment anxiety predicted grief symptoms via externalized CB and predicted PTG via internalized CB at the same time, whereas attachment avoidance positively predicted grief symptoms via externalized CB but negatively predicted PTG directly. Findings suggested that individuals with a high level of attachment anxiety could both suffer from grief and obtain posttraumatic growth after loss, but it depended on which kind of CB they used. By contrast, attachment avoidance was associated with a heightened risk of maladaptive bereavement adjustment. Future grief therapy may encourage the bereaved to establish CB with the deceased and gradually shift from externalized CB to internalized CB. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Prediction of future urban growth using CA-Markov for urban sustainability planning of Banda Aceh, Indonesia

NASA Astrophysics Data System (ADS)

Achmad, A.; Irwansyah, M.; Ramli, I.

2018-03-01

Banda Aceh experienced rapid growth, both physically, socially, and economically, after the Tsunami that devastated it the end of December in 2004. Hence policy controls are needed to direct the pattern of urban growth to achieve sustainable development for the future. The purpose of this paper is to generate a growth model for Banda Aceh using the CA-Markov process. By knowing the changes in land use between 2005 and 2009 from the results of previous research, simulations for 2013, 2019 and 2029 using the application of Idrisi@Selva. CA-Markov models were prepared to determine the quantity of changes. The simulation results showed that, after the Tsunami, the City of Banda Aceh tended to grow towards the coast. For the control of the LUC, the Banda Aceh City government needs to prepare comprehensive and detailed maps and inventory of LUC for the city to provide basic data and information needed for monitoring and evaluation that can be done effectively and efficiently. An institution for monitoring and evaluation of the urban landscape and the LUC should be formed immediately. This institution could consist of representatives from government, academia, community leaders, the private sector and other experts. The findings from this study can be used to start the monitoring and evaluation of future urban growth. Especially for the coastal areas, the local government should immediately prepare special spatial coastal area plans to control growth in those areas and to ensure that the economic benefits from disaster mitigation and coastal protection are preserved. For the development of the city in the future, it is necessary to achieve a balance between economic development, and social welfare with environmental protection and disaster mitigation. iIt will become a big challenge to achieve sustainable development for the future.

What Went Wrong, If Anything, Since Copernicus?

ERIC Educational Resources Information Center

Boulding, Kenneth E.

1974-01-01

Discusses the history of the inequality of world incomes on the basis of a four-fold classification of societies. Indicates that a zero-growth, industrial, ontological, non-destructive society is predictable in the future due to man's expansion from isolated ecosystems into one single world. (CC)

How to make a tree ring: Coupling stem water flow and cambial activity in mature Alpine conifers

NASA Astrophysics Data System (ADS)

Peters, Richard L.; Frank, David C.; Treydte, Kerstin; Steppe, Kathy; Kahmen, Ansgar; Fonti, Patrick

2017-04-01

Inter-annual tree-ring measurements are used to understand tree-growth responses to climatic variability and reconstruct past climate conditions. In parallel, mechanistic models use experimentally defined plant-atmosphere interactions to explain past growth responses and predict future environmental impact on forest productivity. Yet, substantial inconsistencies within mechanistic model ensembles and mismatches with empirical data indicate that significant progress is still needed to understand the processes occurring at an intra-annual resolution that drive annual growth. However, challenges arise due to i) few datasets describing climatic responses of high-resolution physiological processes over longer time-scales, ii) uncertainties on the main mechanistic process limiting radial stem growth and iii) complex interactions between multiple environmental factors which obscure detection of the main stem growth driver, generating a gap between our understanding of intra- and inter-annual growth mechanisms. We attempt to bridge the gap between inter-annual tree-ring width and sub-daily radial stem-growth and provide a mechanistic perspective on how environmental conditions affect physiological processes that shape tree rings in conifers. We combine sub-hourly sap flow and point dendrometer measurements performed on mature Alpine conifers (Larix decidua) into an individual-based mechanistic tree-growth model to simulate sub-hourly cambial activity. The monitored trees are located along a high elevational transect in the Swiss Alps (Lötschental) to analyse the effect of increasing temperature. The model quantifies internal tree hydraulic pathways that regulate the turgidity within the cambial zone and induce cell enlargement for radial growth. The simulations are validated against intra-annual growth patterns derived from xylogenesis data and anatomical analyses. Our efforts advance the process-based understanding of how climate shapes the annual tree-ring structures and could potentially improve our ability to reconstruct the climate of the past and predict future growth under changing climate.

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.

Collision frequency of artificial satellites - The creation of a debris belt

NASA Technical Reports Server (NTRS)

Kessler, D. J.; Cour-Palais, B. G.

1978-01-01

The probability of satellite collisions increases with the number of satellites. In the present paper, possible time scales for the growth of a debris belt from collision fragments are determined, and possible consequences of continued unrestrained launch activities are examined. Use is made of techniques formerly developed for studying the evolution (growth) of the asteroid belt. A model describing the flux from the known earth-orbiting satellites is developed, and the results from this model are extrapolated in time to predict the collision frequency between satellites. Hypervelocity impact phenomena are then examined to predict the debris flux resulting from collisions. The results are applied to design requirements for three types of future space missions.

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.

Long-term growth rates and effects of bleaching in Acropora hyacinthus

NASA Astrophysics Data System (ADS)

Gold, Zachary; Palumbi, Stephen R.

2018-03-01

Understanding the response of coral growth to natural variation in the environment, as well as to acute temperature stress under current and future climate change conditions, is critical to predicting the future health of coral reef ecosystems. As such, ecological surveys are beginning to focus on corals that live in high thermal stress environments to understand how future coral populations may adapt to climate change. We investigated the relationship between coral growth, thermal microhabitat, symbionts type, and thermal acclimatization of four species of the Acropora hyacinthus complex in back-reef lagoons in American Samoa. Coral growth was measured from August 2010 to April 2016 using horizontal planar area of coral colonies derived from photographs and in situ maximum width measurements. Despite marked intraspecific variation, we found that planar colony growth rates were significantly different among cryptic species. The highly heat tolerant A. hyacinthus variant "HE" increased in area an average of 2.9% month-1 (0.03 cm average mean radial extension month-1). By contrast, the three less tolerant species averaged 6.1% (0.07 cm average mean radial extension month-1). Planar growth rates were 40% higher on average in corals harboring Clade C versus Clade D symbiont types, although marked inter-colony variation in growth rendered this difference nonsignificant. Planar growth rates for all four species dropped to near zero following a 2015 bleaching event, independent of the visually estimated percent area of bleaching. Within 1 yr, growth rates recovered to previous levels, confirming previous studies that found sublethal effects of thermal stress on coral growth. Long-term studies of individual coral colonies provide an important tool to measure impacts of environmental change and allow integration of coral physiology, genetics, symbionts, and microclimate on reef growth patterns.

Mapping the environmental limitations to growth of coastal Douglas-fir stands on Vancouver Island, British Columbia.

PubMed

Coops, Nicholas C; Coggins, Sam B; Kurz, Werner A

2007-06-01

Coastal Douglas-fir (Pseudotsuga menziesii spp. menziesii (Mirb.) Franco) occurs over a wide range of environmental conditions on Vancouver Island, British Columbia. Although ecological zones have been drawn, no formal spatial analysis of environmental limitations on tree growth has been carried out. Such an exercise is desirable to identify areas that may warrant intensive management and to evaluate the impacts of predicted climate change this century. We applied a physiologically based forest growth model, 3-PG (Physiological Principles Predicting Growth), to interpret and map current limitations to Douglas-fir growth across Vancouver Island at 100-m cell resolution. We first calibrated the model to reproduce the regional productivity estimates reported in yield table growth curves. Further analyses indicated that slope exposure is important; southwest slopes of 30 degrees receive 40% more incident radiation than similarly inclined northeast slopes. When combined with other environmental differences associated with aspect, the model predicted 60% more growth on southwest exposures than on northeast exposures. The model simulations support field observations that drought is rare in the wetter zones, but common on the eastern side of Vancouver Island at lower elevations and on more exposed slopes. We illustrate the current limitations on growth caused by suboptimal temperature, high vapor pressure deficits and other factors. The modeling approach complements ecological classifications and offers the potential to identify the most favorable sites for management of other native tree species under current and future climatic conditions.

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.

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).

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

FutureTox II: in vitro data and in silico models for predictive toxicology.

PubMed

Knudsen, Thomas B; Keller, Douglas A; Sander, Miriam; Carney, Edward W; Doerrer, Nancy G; Eaton, David L; Fitzpatrick, Suzanne Compton; Hastings, Kenneth L; Mendrick, Donna L; Tice, Raymond R; Watkins, Paul B; Whelan, Maurice

2015-02-01

FutureTox II, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in January, 2014. The meeting goals were to review and discuss the state of the science in toxicology in the context of implementing the NRC 21st century vision of predicting in vivo responses from in vitro and in silico data, and to define the goals for the future. Presentations and discussions were held on priority concerns such as predicting and modeling of metabolism, cell growth and differentiation, effects on sensitive subpopulations, and integrating data into risk assessment. Emerging trends in technologies such as stem cell-derived human cells, 3D organotypic culture models, mathematical modeling of cellular processes and morphogenesis, adverse outcome pathway development, and high-content imaging of in vivo systems were discussed. Although advances in moving towards an in vitro/in silico based risk assessment paradigm were apparent, knowledge gaps in these areas and limitations of technologies were identified. Specific recommendations were made for future directions and research needs in the areas of hepatotoxicity, cancer prediction, developmental toxicity, and regulatory toxicology. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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.

Where Full-Text Is Viable.

ERIC Educational Resources Information Center

Cotton, P. L.

1987-01-01

Defines two types of online databases: source, referring to those intended to be complete in themselves, whether full-text or abstracts; and bibliographic, meaning those that are not complete. Predictions are made about the future growth rate of these two types of databases, as well as full-text versus abstract databases. (EM)

Species characteristics and intraspecific variation in growth and photosynthesis of Cryptomeria japonica under elevated O3 and CO2.

PubMed

Hiraoka, Yuichiro; Iki, Taiichi; Nose, Mine; Tobita, Hiroyuki; Yazaki, Kenichi; Watanabe, Atsushi; Fujisawa, Yoshitake; Kitao, Mitsutoshi

2017-06-01

In order to predict the effects of future atmospheric conditions on forest productivity, it is necessary to clarify the physiological responses of major forest tree species to high concentrations of ozone (O3) and carbon dioxide (CO2). Furthermore, intraspecific variation of these responses should also be examined in order to predict productivity gains through tree improvements in the future. We investigated intraspecific variation in growth and photosynthesis of Cryptomeria japonica D. Don, a major silviculture species in Japan, in response to elevated concentrations of O3 (eO3) and CO2 (eCO2), separately and in combination. Cuttings of C. japonica were grown and exposed to two levels of O3 (ambient and twice-ambient levels) in combination with two levels of CO2 (ambient and 550 µmol mol-1 in the daytime) for two growing seasons in a free-air CO2 enrichment experiment. There was no obvious negative effect of eO3 on growth or photosynthetic traits of the C. japonica clones, but a positive effect was observed for annual height increments in the first growing season. Dry mass production and the photosynthetic rate increased under eCO2 conditions, while the maximum carboxylation rate decreased. Significant interaction effects of eO3 and eCO2 on growth and photosynthetic traits were not observed. Clonal effects on growth and photosynthetic traits were significant, but the interactions between clones and O3 and/or CO2 treatments were not. Spearman's rank correlation coefficients between growth traits under ambient conditions and for each treatment were significantly positive, implying that clonal ranking in growth abilities might not be affected by either eO3 or eCO2. The knowledge obtained from this study will be helpful for species selection in afforestation programs, to continue and to improve current programs involving this species, and to accurately predict the CO2 fixation capacity of Japanese forests. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Revisiting a model of ontogenetic growth: estimating model parameters from theory and data.

PubMed

Moses, Melanie E; Hou, Chen; Woodruff, William H; West, Geoffrey B; Nekola, Jeffery C; Zuo, Wenyun; Brown, James H

2008-05-01

The ontogenetic growth model (OGM) of West et al. provides a general description of how metabolic energy is allocated between production of new biomass and maintenance of existing biomass during ontogeny. Here, we reexamine the OGM, make some minor modifications and corrections, and further evaluate its ability to account for empirical variation on rates of metabolism and biomass in vertebrates both during ontogeny and across species of varying adult body size. We show that the updated version of the model is internally consistent and is consistent with other predictions of metabolic scaling theory and empirical data. The OGM predicts not only the near universal sigmoidal form of growth curves but also the M(1/4) scaling of the characteristic times of ontogenetic stages in addition to the curvilinear decline in growth efficiency described by Brody. Additionally, the OGM relates the M(3/4) scaling across adults of different species to the scaling of metabolic rate across ontogeny within species. In providing a simple, quantitative description of how energy is allocated to growth, the OGM calls attention to unexplained variation, unanswered questions, and opportunities for future research.

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

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

Thomas, R. Quinn; Brooks, Evan B.; Jersild, Annika L.

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions,more » DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO 2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 10 5 km 2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO 2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO 2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO 2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO 2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.« less

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

DOE PAGES

Thomas, R. Quinn; Brooks, Evan B.; Jersild, Annika L.; ...

2017-07-26

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions,more » DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO 2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 10 5 km 2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO 2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO 2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO 2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO 2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.« less

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

NASA Astrophysics Data System (ADS)

Quinn Thomas, R.; Brooks, Evan B.; Jersild, Annika L.; Ward, Eric J.; Wynne, Randolph H.; Albaugh, Timothy J.; Dinon-Aldridge, Heather; Burkhart, Harold E.; Domec, Jean-Christophe; Fox, Thomas R.; Gonzalez-Benecke, Carlos A.; Martin, Timothy A.; Noormets, Asko; Sampson, David A.; Teskey, Robert O.

2017-07-01

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model-data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 105 km2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.

Kinetic growth rate after portal vein embolization predicts posthepatectomy outcomes: toward zero liver-related mortality in patients with colorectal liver metastases and small future liver remnant.

PubMed

Shindoh, Junichi; Truty, Mark J; Aloia, Thomas A; Curley, Steven A; Zimmitti, Giuseppe; Huang, Steven Y; Mahvash, Armeen; Gupta, Sanjay; Wallace, Michael J; Vauthey, Jean-Nicolas

2013-02-01

Standardized future liver remnant (sFLR) volume and degree of hypertrophy after portal vein embolization (PVE) have been recognized as important predictors of surgical outcomes after major liver resection. However, the regeneration rate of the FLR after PVE varies among individuals and its clinical significance is unknown. Kinetic growth rate (KGR) is defined as the degree of hypertrophy at initial volume assessment divided by number of weeks elapsed after PVE. In 107 consecutive patients who underwent liver resection for colorectal liver metastases with an sFLR volume >20%, the ability of the KGR to predict overall and liver-specific postoperative morbidity and mortality was compared with sFLR volume and degree of hypertrophy. Using receiver operating characteristic analysis, the best cutoff values for sFLR volume, degree of hypertrophy, and KGR for predicting postoperative hepatic insufficiency were estimated as 29.6%, 7.5%, and 2.0% per week, respectively. Among these, KGR was the most accurate predictor (area under the curve 0.830 [95% CI, 0.736-0.923]; asymptotic significance, 0.002). A KGR of <2% per week vs ≥2% per week correlates with rates of hepatic insufficiency (21.6% vs 0%; p = 0.0001) and liver-related 90-day mortality (8.1% vs 0%; p = 0.04). The predictive value of KGR was not influenced by sFLR volume or the timing of initial volume assessment when evaluated within 8 weeks after PVE. Kinetic growth rate is a better predictor of postoperative morbidity and mortality after liver resection for small FLR than conventional measured volume parameters (ie, sFLR volume and degree of hypertrophy). Copyright © 2013 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

PRODUCTION AND ECONOMIC OPTIMIZATION OF DIETARY PROTEIN AND CARBOHYDRATE IN THE CULTURE OF JUVENILE SEA URCHIN Lytechinus variegatus

PubMed Central

Heflin, Laura E.; Makowsky, Robert; Taylor, J. Christopher; Williams, Michael B.; Lawrence, Addison L.; Watts, Stephen A.

2016-01-01

Juvenile Lytechinus variegatus (ca. 3.95± 0.54 g) were fed one of 10 formulated diets with different protein (ranging from 11- 43%) and carbohydrate (12 or 18%; brackets determined from previous studies) levels. Urchins (n= 16 per treatment) were fed a daily sub-satiation ration equivalent to 2.0% of average body weight for 10 weeks. Our objective was (1) to create predictive models of growth, production and efficiency outcomes and (2) to generate economic analysis models in relation to these dietary outcomes for juvenile L. variegatus held in culture. At dietary protein levels below ca. 30%, models for most growth and production outcomes predicted increased rates of growth and production among urchins fed diets containing 18% dietary carbohydrate levels as compared to urchins fed diets containing 12% dietary carbohydrate. For most outcomes, growth and production was predicted to increase with increasing level of dietary protein up to ca. 30%, after which, no further increase in growth and production were predicted. Likewise, dry matter production efficiency was predicted to increase with increasing protein level up to ca. 30%, with urchins fed diets with 18% carbohydrate exhibiting greater efficiency than those fed diets with 12% carbohydrate. The energetic cost of dry matter production was optimal at protein levels less than those required for maximal weight gain and gonad production, suggesting an increased energetic cost (decreased energy efficiency) is required to increase gonad production relative to somatic growth. Economic analysis models predict when cost of feed ingredients are low, the lowest cost per gram of wet weight gain will occur at 18% dietary carbohydrate and ca. 25- 30% dietary protein. In contrast, lowest cost per gram of wet weight gain will occur at 12% dietary carbohydrate and ca. 35- 40% dietary protein when feed ingredient costs are high or average. For both 18 and 12% levels of dietary carbohydrate, cost per gram of wet weight gain is predicted to be maximized at low dietary protein levels, regardless of feed ingredient costs. These models will compare dietary requirements and growth outcomes in relation to economic costs and provide insight for future commercialization of sea urchin aquaculture. PMID:28082753

PRODUCTION AND ECONOMIC OPTIMIZATION OF DIETARY PROTEIN AND CARBOHYDRATE IN THE CULTURE OF JUVENILE SEA URCHIN Lytechinus variegatus.

PubMed

Heflin, Laura E; Makowsky, Robert; Taylor, J Christopher; Williams, Michael B; Lawrence, Addison L; Watts, Stephen A

2016-10-01

Juvenile Lytechinus variegatus (ca. 3.95± 0.54 g) were fed one of 10 formulated diets with different protein (ranging from 11- 43%) and carbohydrate (12 or 18%; brackets determined from previous studies) levels. Urchins (n= 16 per treatment) were fed a daily sub-satiation ration equivalent to 2.0% of average body weight for 10 weeks. Our objective was (1) to create predictive models of growth, production and efficiency outcomes and (2) to generate economic analysis models in relation to these dietary outcomes for juvenile L. variegatus held in culture. At dietary protein levels below ca. 30%, models for most growth and production outcomes predicted increased rates of growth and production among urchins fed diets containing 18% dietary carbohydrate levels as compared to urchins fed diets containing 12% dietary carbohydrate. For most outcomes, growth and production was predicted to increase with increasing level of dietary protein up to ca. 30%, after which, no further increase in growth and production were predicted. Likewise, dry matter production efficiency was predicted to increase with increasing protein level up to ca. 30%, with urchins fed diets with 18% carbohydrate exhibiting greater efficiency than those fed diets with 12% carbohydrate. The energetic cost of dry matter production was optimal at protein levels less than those required for maximal weight gain and gonad production, suggesting an increased energetic cost (decreased energy efficiency) is required to increase gonad production relative to somatic growth. Economic analysis models predict when cost of feed ingredients are low, the lowest cost per gram of wet weight gain will occur at 18% dietary carbohydrate and ca. 25- 30% dietary protein. In contrast, lowest cost per gram of wet weight gain will occur at 12% dietary carbohydrate and ca. 35- 40% dietary protein when feed ingredient costs are high or average. For both 18 and 12% levels of dietary carbohydrate, cost per gram of wet weight gain is predicted to be maximized at low dietary protein levels, regardless of feed ingredient costs. These models will compare dietary requirements and growth outcomes in relation to economic costs and provide insight for future commercialization of sea urchin aquaculture.

Multiscale Systems Analysis of Root Growth and Development: Modeling Beyond the Network and Cellular Scales

PubMed Central

Band, Leah R.; Fozard, John A.; Godin, Christophe; Jensen, Oliver E.; Pridmore, Tony; Bennett, Malcolm J.; King, John R.

2012-01-01

Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties. PMID:23110897

Photosynthesis, N(2) fixation and taproot reserves during the cutting regrowth cycle of alfalfa under elevated CO(2) and temperature.

PubMed

Erice, G; Sanz-Sáez, A; Aranjuelo, I; Irigoyen, J J; Aguirreolea, J; Avice, J-C; Sánchez-Díaz, M

2011-11-15

Future climatic conditions, including rising atmospheric CO(2) and temperature may increase photosynthesis and, consequently, plant production. A larger knowledge of legume performance under the predicted growth conditions will be crucial for safeguarding crop management and extending the area under cultivation with these plants in the near future. N(2) fixation is a key process conditioning plant responsiveness to varying growth conditions. Moreover, it is likely to increase under future environments, due to the higher photosynthate availability, as a consequence of the higher growth rate under elevated CO(2). However, as described in the literature, photosynthesis performance is frequently down-regulated (acclimated) under long-term exposure to CO(2), especially when affected by stressful temperature and water availability conditions. As growth responses to elevated CO(2) are dependent on sink-source status, it is generally accepted that down-regulation occurs in situations with insufficient plant C sink capacity. Alfalfa management involves the cutting of shoots, which alters the source-sink relationship and thus the photosynthetic behaviour. As the growth rate decreases at the end of the pre-cut vegetative growth period, nodulated alfalfa plants show photosynthetic down-regulation, but during regrowth following defoliation, acclimation to elevated CO(2) disappears. The shoot harvest also leads to a drop in mineral N uptake and C translocation to the roots, resulting in a reduction in N(2) fixation due to the dependence on photosynthate supply to support nodule function. Therefore, the production of new shoots during the first days following cutting requires the utilization of reduced C and N compounds that have been stored previously in reserve organs. The stored reserves are mediated by phytohormones such as methyl jasmonate and abscisic acid and in situations where water stress reduces shoot production this potentially enables the enhancement of taproot protein levels in nodulated alfalfa, which may lead to these plants being in better condition in the following cut/regrowth cycle. Furthering our knowledge of legume performance under predicted climate change conditions will be crucial for the development of varieties with better adaptation that will achieve greater and more efficient production values. Furthermore, for this purpose it will be necessary to improve existing methodologies and create new ones for phenotype characterization. Such knowledge will provide key information for future plant breeding programs. Copyright © 2011 Elsevier GmbH. All rights reserved.

Optimality Based Dynamic Plant Allocation Model: Predicting Acclimation Response to Climate Change

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Drewry, D.; Kumar, P.; Sivapalan, M.

2009-12-01

Allocation of assimilated carbon to different plant parts determines the future plant status and is important to predict long term (months to years) vegetated land surface fluxes. Plants have the ability to modify their allometry and exhibit plasticity by varying the relative proportions of the structural biomass contained in each of its tissue. The ability of plants to be plastic provides them with the potential to acclimate to changing environmental conditions in order to enhance their probability of survival. Allometry based allocation models and other empirical allocation models do not account for plant plasticity cause by acclimation due to environmental changes. In the absence of a detailed understanding of the various biophysical processes involved in plant growth and development an optimality approach is adopted here to predict carbon allocation in plants. Existing optimality based models of plant growth are either static or involve considerable empiricism. In this work, we adopt an optimality based approach (coupled with limitations on plant plasticity) to predict the dynamic allocation of assimilated carbon to different plant parts. We explore the applicability of this approach using several optimization variables such as net primary productivity, net transpiration, realized growth rate, total end of growing season reproductive biomass etc. We use this approach to predict the dynamic nature of plant acclimation in its allocation of carbon to different plant parts under current and future climate scenarios. This approach is designed as a growth sub-model in the multi-layer canopy plant model (MLCPM) and is used to obtain land surface fluxes and plant properties over the growing season. The framework of this model is such that it retains the generality and can be applied to different types of ecosystems. We test this approach using the data from free air carbon dioxide enrichment (FACE) experiments using soybean crop at the Soy-FACE research site. Our results show that there are significant changes in the allocation patterns of vegetation when subjected to elevated CO2 indicating that our model is able to account for plant plasticity arising from acclimation. Soybeans when grown under elevated CO2, increased their allocation to structural components such as leaves and decreased their allocation to reproductive biomass. This demonstrates that plant acclimation causes lower than expected crop yields when grown under elevated CO2. Our findings can have serious implications in estimating future crop yields under climate change scenarios where it is widely expected that rising CO2 will fully offset losses due to climate change.

The Predictive Validity of the ABFM's In-Training Examination.

PubMed

O'Neill, Thomas R; Li, Zijia; Peabody, Michael R; Lybarger, Melanie; Royal, Kenneth; Puffer, James C

2015-05-01

Our objective was to examine the predictive validity of the American Board of Family Medicine's (ABFM) In-Training Examination (ITE) with regard to predicting outcomes on the ABFM certification examination. This study used a repeated measures design across three levels of medical training (PGY1--PGY2, PGY2--PGY3, and PGY3--initial certification) with three different cohorts (2010--2011, 2011--2012, and 2012--2013) to examine: (1) how well the residents' ITE scores correlated with their test scores in the following year, (2) what the typical score increase was across training years, and (3) what was the sensitivity, specificity, positive predictive value, and negative predictive value of the PGY3 scores with regard to predicting future results on the MC-FP Examination. ITE scores generally correlate at about .7 with the following year's ITE or with the following year's certification examination. The mean growth from PGY1 to PGY2 was 52 points, from PGY2 to PGY3 was 34 points, and from PGY3 to initial certification was 27 points. The sensitivity, specificity, positive predictive value, and negative predictive value were .91, .47, .96, and .27, respectively. The ITE is a useful predictor of future ITE and initial certification examination performance.

Effects of Genotype and Growth Temperature on the Contents of Tannin, Phytate and In Vitro Iron Availability of Sorghum Grains

PubMed Central

Wu, Gangcheng; Johnson, Stuart K.; Bornman, Janet F.; Bennett, Sarita J.; Singh, Vijaya; Simic, Azra; Fang, Zhongxiang

2016-01-01

Background It has been predicted that the global temperature will rise in the future, which means crops including sorghum will likely be grown under higher temperatures, and consequently may affect the nutritional properties. Methods The effects of two growth temperatures (OT, day/night 32/21°C; HT 38/21°C) on tannin, phytate, mineral, and in vitro iron availability of raw and cooked grains (as porridge) of six sorghum genotypes were investigated. Results Tannin content significantly decreased across all sorghum genotypes under high growth temperature (P ≤0.05), while the phytate and mineral contents maintained the same level, increased or decreased significantly, depending on the genotype. The in vitro iron availability in most sorghum genotypes was also significantly reduced under high temperature, except for Ai4, which showed a pronounced increase (P ≤0.05). The cooking process significantly reduced tannin content in all sorghum genotypes (P ≤0.05), while the phytate content and in vitro iron availability were not significantly affected. Conclusions This research provides some new information on sorghum grain nutritional properties when grown under predicted future higher temperatures, which could be important for humans where sorghum grains are consumed as staple food. PMID:26859483

NASA Experimental Program to Stimulate Competitive Research: South Carolina

NASA Technical Reports Server (NTRS)

Sutton, Michael A.

2004-01-01

The use of an appropriate relationship model is critical for reliable prediction of future urban growth. Identification of proper variables and mathematic functions and determination of the weights or coefficients are the key tasks for building such a model. Although the conventional logistic regression model is appropriate for handing land use problems, it appears insufficient to address the issue of interdependency of the predictor variables. This study used an alternative approach to simulation and modeling urban growth using artificial neural networks. It developed an operational neural network model trained using a robust backpropagation method. The model was applied in the Myrtle Beach region of South Carolina, and tested with both global datasets and areal datasets to examine the strength of both regional models and areal models. The results indicate that the neural network model not only has many theoretic advantages over other conventional mathematic models in representing the complex urban systems, but also is practically superior to the logistic model in its capability to predict urban growth with better - accuracy and less variation. The neural network model is particularly effective in terms of successfully identifying urban patterns in the rural areas where the logistic model often falls short. It was also found from the area-based tests that there are significant intra-regional differentiations in urban growth with different rules and rates. This suggests that the global modeling approach, or one model for the entire region, may not be adequate for simulation of a urban growth at the regional scale. Future research should develop methods for identification and subdivision of these areas and use a set of area-based models to address the issues of multi-centered, intra- regionally differentiated urban growth.

Future Supply of Pediatric Surgeons: Analytical Study of the Current and Projected Supply of Pediatric Surgeons in the Context of a Rapidly Changing Process for Specialty and Subspecialty Training.

PubMed

Ricketts, Thomas C; Adamson, William T; Fraher, Erin P; Knapton, Andy; Geiger, James D; Abdullah, Fizan; Klein, Michael D

2017-03-01

To describe the future supply and demand for pediatric surgeons using a physician supply model to determine what the future supply of pediatric surgeons will be over the next decade and a half and to compare that projected supply with potential indicators of demand and the growth of other subspecialties. Anticipating the supply of physicians and surgeons in the future has met with varying levels of success. However, there remains a need to anticipate supply given the rapid growth of specialty and subspecialty fellowships. This analysis is intended to support decision making on the size of future fellowships in pediatric surgery. The model used in the study is an adaptation of the FutureDocs physician supply and need tool developed to anticipate future supply and need for all physician specialties. Data from national inventories of physicians by specialty, age, sex, activity, and location are combined with data from residency and fellowship programs and accrediting bodies in an agent-based or microsimulation projection model that considers movement into and among specialties. Exits from practice and the geographic distribution of physician and the patient population are also included in the model. Three scenarios for the annual entry into pediatric surgery fellowships (28, 34, and 56) are modeled and their effects on supply through 2030 are presented. The FutureDocs model predicts a very rapid growth of the supply of surgeons who treat pediatric patients-including general pediatric surgeon and focused subspecialties. The supply of all pediatric surgeons will grow relatively rapidly through 2030 under current conditions. That growth is much faster than the rate of growth of the pediatric population. The volume of complex surgical cases will likely match this population growth rate meaning there will be many more surgeons trained for those procedures. The current entry rate into pediatric surgery fellowships (34 per year) will result in a slowing of growth after 2025, a rate of 56 will generate a continued growth through 2030 with a likely plateau after 2035. The rate of entry into pediatric surgery will continue to exceed population growth through 2030 under two likely scenarios. The very rapid anticipated growth in focused pediatric subspecialties will likely prove challenging to surgeons wishing to maintain their skills with complex cases as a larger and more diverse group of surgeons will also seek to care for many of the conditions and patients which the general pediatric surgeons and general surgeons now see. This means controlling the numbers of pediatric surgery fellowships in a way that recognizes problems with distribution, the volume of cases available to maintain proficiency, and the dynamics of retirement and shifts into other specialty practice.

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.

Convergence of the effect of root hydraulic functioning and root hydraulic redistribution on ecosystem water and carbon balance across divergent forest ecosystems

NASA Astrophysics Data System (ADS)

domec, J.; King, J. S.; Ogée, J.; Noormets, A.; Warren, J.; Meinzer, F. C.; Sun, G.; Jordan-Meille, L.; Martineau, E.; Brooks, R. J.; Laclau, J.; Battie Laclau, P.; McNulty, S.

2012-12-01

INVITED ABSTRACT: Deep root water uptake and hydraulic redistribution (HR) play a major role in forest ecosystems during drought, but little is known about the impact of climate change on root-zone processes influencing HR and its consequences on water and carbon fluxes. Using data from two old growth sites in the western USA, two mature sites in the eastern USA, one site in southern Brazil, and simulations with the process-based model MuSICA, our objectives were to show that HR can 1) mitigate the effects of soil drying on root functioning, and 2) have important implications for carbon uptake and net ecosystem exchange (NEE). In a dry, old-growth ponderosa pine (USA) and a eucalyptus stand (Brazil) both characterized by deep sandy soils, HR limited the decline in root hydraulic conductivity and increased dry season tree transpiration (T) by up to 30%, which impacted NEE through major increases in gross primary productivity (GPP). The presence of deep-rooted trees did not necessarily imply high rates of HR unless soil texture allowed large water potential gradients to occur, as was the case in the wet old-growth Douglas-fir/mixed conifer stand. At the Duke mixed hardwood forest characterized by a shallow clay-loam soil, modeled HR was low but not negligible, representing annually up to 10% of T, and maintaining root conductance high. At this site, in the absence of HR, it was predicted that annual GPP would have been diminished by 7-19%. At the coastal loblolly pine plantation, characterized by deep organic soil, HR limited the decline in shallow root conductivity by more than 50% and increased dry season T by up to 40%, which increased net carbon gain by the ecosystem by about 400 gC m-2 yr-1, demonstrating the significance of HR in maintaining the stomatal conductance and assimilation capacity of the whole ecosystem. Under future climate conditions (elevated atmospheric [CO2] and temperature), HR is predicted to be reduced by up to 50%; reducing the resilience of trees to droughts. Under future conditions, T is predicted to stay the same at the Duke mixed hardwood forest, but to decline slightly at the coastal loblolly pine plantation and slightly increase at the old-growth ponderosa pine stand and the eucalyptus plantation. As a consequence, water use efficiency in all sites was predicted to improve dramatically under future climate conditions. Our simulations also showed that the negative effect of drier nights on HR would be greater under future climate conditions. Assuming no increase in stomatal control with increasing drier nights, increased vapor pressure deficit at night under future conditions was sufficient to drive significant nighttime T at all sites , which reduced HR, because the plant and the atmosphere became a sink for hydraulically redistributed water . We concluded that the predicted reductions in HR under future climate conditions are expected to play an important regulatory role in land-atmosphere interactions by affecting whole ecosystem carbon and water balance. We suggest that root distribution should be treated dynamically in response to climate change and that HR and its interactions with rooting depth and soil texture should be implemented in soil-vegetation-atmosphere transfer models.

Transition index maps for urban growth simulation: application of artificial neural networks, weight of evidence and fuzzy multi-criteria evaluation.

PubMed

Shafizadeh-Moghadam, Hossein; Tayyebi, Amin; Helbich, Marco

2017-06-01

Transition index maps (TIMs) are key products in urban growth simulation models. However, their operationalization is still conflicting. Our aim was to compare the prediction accuracy of three TIM-based spatially explicit land cover change (LCC) models in the mega city of Mumbai, India. These LCC models include two data-driven approaches, namely artificial neural networks (ANNs) and weight of evidence (WOE), and one knowledge-based approach which integrates an analytical hierarchical process with fuzzy membership functions (FAHP). Using the relative operating characteristics (ROC), the performance of these three LCC models were evaluated. The results showed 85%, 75%, and 73% accuracy for the ANN, FAHP, and WOE. The ANN was clearly superior compared to the other LCC models when simulating urban growth for the year 2010; hence, ANN was used to predict urban growth for 2020 and 2030. Projected urban growth maps were assessed using statistical measures, including figure of merit, average spatial distance deviation, producer accuracy, and overall accuracy. Based on our findings, we recomend ANNs as an and accurate method for simulating future patterns of urban growth.

A manpower calculus: the implications of SUO fellowship expansion on oncologic surgeon case volumes.

PubMed

See, William A

2014-01-01

Society of Urologic Oncology (SUO)-accredited fellowship programs have undergone substantial expansion. This study developed a mathematical model to estimate future changes in urologic oncologic surgeon (UOS) manpower and analyzed the effect of those changes on per-UOS case volumes. SUO fellowship program directors were queried as to the number of positions available on an annual basis. Current US UOS manpower was estimated from the SUO membership list. Future manpower was estimated on an annual basis by linear senescence of existing manpower combined with linear growth of newly trained surgeons. Case-volume estimates for the 4 surgical disease sites (prostate, kidney/renal pelvis, bladder, and testes) were obtained from the literature. The future number of major cases was determined from current volumes based upon the US population growth rates and the historic average annual change in disease incidence. Two models were used to predict future per-UOS major case volumes. Model 1 assumed the current distribution of cases between nononcologic surgeons and UOS would continue. Model 2 assumed a progressive redistribution of cases over time such that in 2043 100% of major urologic cancer cases would be performed by UOSs. Over the 30-year period to "manpower steady-state" SUO-accredited UOSs practicing in the United States have the potential to increase from approximately 600 currently to 1,650 in 2043. During this interval, case volumes are predicted to change 0.97-, 2.4-, 1.1-, and 1.5-fold for prostatectomy, nephrectomy, cystectomy, and retroperitoneal lymph node dissection, respectively. The ratio of future to current total annual case volumes is predicted to be 0.47 and 0.9 for models 1 and 2, respectively. The number of annual US practicing graduates necessary to achieve a future to current case-volume ratio greater than 1 is 25 and 49 in models 1 and 2, respectively. The current number of SUO fellowship trainees has the potential to decrease future per-UOS case volumes relative to current levels. Redistribution of existing case volume or a decrease in the annual number of trainees or both would be required to insure sufficient surgical volumes for skill maintenance and optimal patient outcomes. Published by Elsevier Inc.

Predictive Capabilities of Multiphysics and Multiscale Models in Modeling Solidification of Steel Ingots and DC Casting of Aluminum

NASA Astrophysics Data System (ADS)

Combeau, Hervé; Založnik, Miha; Bedel, Marie

2016-08-01

Prediction of solidification defects, such as macrosegregation and inhomogeneous microstructures, constitutes a key issue for industry. The development of models of casting processes needs to account for several imbricated length scales and different physical phenomena. For example, the kinetics of the growth of microstructures needs to be coupled with the multiphase flow at the process scale. We introduce such a state-of-the-art model and outline its principles. We present the most recent applications of the model to casting of a heavy steel ingot and to direct chill casting of a large Al alloy sheet ingot. Their ability to help in the understanding of complex phenomena, such as the competition between nucleation and growth of grains in the presence of convection of the liquid and of grain motion is shown, and its predictive capabilities are discussed. Key issues for future developments and research are addressed.

Transition and protective agency of early childhood learning behaviors as portents of later school attendance and adjustment.

PubMed

McDermott, Paul A; Rikoon, Samuel H; Fantuzzo, John W

2016-02-01

This article reports on the study of differential change trajectories for early childhood learning behaviors as they relate to future classroom adjustment and school attendance. A large sample (N=2152) of Head Start children was followed through prekindergarten, kindergarten, and 1st grade. Classroom learning behaviors were assessed twice each year by teachers who observed gradual declines in Competence Motivation and Attentional Persistence as children transitioned through schooling. Cross-classified multilevel growth models revealed distinct transitional pathways for future adjustment versus maladjustment and sporadic versus chronic absenteeism. Generalized multilevel logistic modeling and receiver operating characteristic curve analyses showed that teachers' earliest assessments were substantially predictive of eventual good classroom adjustment and school attendance, with increasing accuracy for prediction of future sociobehavioral adjustment as time progressed. Copyright © 2015 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

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…

High-order computational fluid dynamics tools for aircraft design

PubMed Central

Wang, Z. J.

2014-01-01

Most forecasts predict an annual airline traffic growth rate between 4.5 and 5% in the foreseeable future. To sustain that growth, the environmental impact of aircraft cannot be ignored. Future aircraft must have much better fuel economy, dramatically less greenhouse gas emissions and noise, in addition to better performance. Many technical breakthroughs must take place to achieve the aggressive environmental goals set up by governments in North America and Europe. One of these breakthroughs will be physics-based, highly accurate and efficient computational fluid dynamics and aeroacoustics tools capable of predicting complex flows over the entire flight envelope and through an aircraft engine, and computing aircraft noise. Some of these flows are dominated by unsteady vortices of disparate scales, often highly turbulent, and they call for higher-order methods. As these tools will be integral components of a multi-disciplinary optimization environment, they must be efficient to impact design. Ultimately, the accuracy, efficiency, robustness, scalability and geometric flexibility will determine which methods will be adopted in the design process. This article explores these aspects and identifies pacing items. PMID:25024419

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.

Taming the Hurricane of Acquisition Cost Growth - Or at Least Predicting It

DTIC Science & Technology

2015-01-01

the practice of generating two different cost estimates dubbed Will Cost and Should Cost. The Should Cost estimate is “based on realistic tech...to predict estimate error in similar future programs. This method is dubbed “macro-stochastic” estimation (Ryan, Schubert Kabban, Jacques...mph Potential Day 1-3 Track Area Tropical Storm Warning OK AR TN AL FL Mexico MS LA TX 30 N 35 N 25 N 95 W 90 W 85 W 80 W True at 30.00N Approx

Evidence for climate-driven synchrony of marine and terrestrial ecosystems in northwest Australia.

PubMed

Ong, Joyce J L; Rountrey, Adam N; Zinke, Jens; Meeuwig, Jessica J; Grierson, Pauline F; O'Donnell, Alison J; Newman, Stephen J; Lough, Janice M; Trougan, Mélissa; Meekan, Mark G

2016-08-01

The effects of climate change are difficult to predict for many marine species because little is known of their response to climate variations in the past. However, long-term chronologies of growth, a variable that integrates multiple physical and biological factors, are now available for several marine taxa. These allow us to search for climate-driven synchrony in growth across multiple taxa and ecosystems, identifying the key processes driving biological responses at very large spatial scales. We hypothesized that in northwest (NW) Australia, a region that is predicted to be strongly influenced by climate change, the El Niño Southern Oscillation (ENSO) phenomenon would be an important factor influencing the growth patterns of organisms in both marine and terrestrial environments. To test this idea, we analyzed existing growth chronologies of the marine fish Lutjanus argentimaculatus, the coral Porites spp. and the tree Callitris columellaris and developed a new chronology for another marine fish, Lethrinus nebulosus. Principal components analysis and linear model selection showed evidence of ENSO-driven synchrony in growth among all four taxa at interannual time scales, the first such result for the Southern Hemisphere. Rainfall, sea surface temperatures, and sea surface salinities, which are linked to the ENSO system, influenced the annual growth of fishes, trees, and corals. All four taxa had negative relationships with the Niño-4 index (a measure of ENSO status), with positive growth patterns occurring during strong La Niña years. This finding implies that future changes in the strength and frequency of ENSO events are likely to have major consequences for both marine and terrestrial taxa. Strong similarities in the growth patterns of fish and trees offer the possibility of using tree-ring chronologies, which span longer time periods than those of fish, to aid understanding of both historical and future responses of fish populations to climate variation. © 2016 John Wiley & Sons Ltd.

The response of tropical rainforests to drought-lessons from recent research and future prospects.

PubMed

Bonal, Damien; Burban, Benoit; Stahl, Clément; Wagner, Fabien; Hérault, Bruno

We review the recent findings on the influence of drought on tree mortality, growth or ecosystem functioning in tropical rainforests. Drought plays a major role in shaping tropical rainforests and the response mechanisms are highly diverse and complex. The numerous gaps identified here require the international scientific community to combine efforts in order to conduct comprehensive studies in tropical rainforests on the three continents. These results are essential to simulate the future of these ecosystems under diverse climate scenarios and to predict the future of the global earth carbon balance. Tropical rainforest ecosystems are characterized by high annual rainfall. Nevertheless, rainfall regularly fluctuates during the year and seasonal soil droughts do occur. Over the past decades, a number of extreme droughts have hit tropical rainforests, not only in Amazonia but also in Asia and Africa. The influence of drought events on tree mortality and growth or on ecosystem functioning (carbon and water fluxes) in tropical rainforest ecosystems has been studied intensively, but the response mechanisms are complex. Herein, we review the recent findings related to the response of tropical forest ecosystems to seasonal and extreme droughts and the current knowledge about the future of these ecosystems. This review emphasizes the progress made over recent years and the importance of the studies conducted under extreme drought conditions or in through-fall exclusion experiments in understanding the response of these ecosystems. It also points to the great diversity and complexity of the response of tropical rainforest ecosystems to drought. The numerous gaps identified here require the international scientific community to combine efforts in order to conduct comprehensive studies in tropical forest regions. These results are essential to simulate the future of these ecosystems under diverse climate scenarios and to predict the future of the global earth carbon balance.

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

Stage-Specific Changes in Physiological and Life-History Responses to Elevated Temperature and Pco2 during the Larval Development of the European Lobster Homarus gammarus (L.).

PubMed

Small, Daniel P; Calosi, Piero; Boothroyd, Dominic; Widdicombe, Steve; Spicer, John I

2015-01-01

An organism's physiological processes form the link between its life-history traits and the prevailing environmental conditions, especially in species with complex life cycles. Understanding how these processes respond to changing environmental conditions, thereby affecting organismal development, is critical if we are to predict the biological implications of current and future global climate change. However, much of our knowledge is derived from adults or single developmental stages. Consequently, we investigated the metabolic rate, organic content, carapace mineralization, growth, and survival across each larval stage of the European lobster Homarus gammarus, reared under current and predicted future ocean warming and acidification scenarios. Larvae exhibited stage-specific changes in the temperature sensitivity of their metabolic rate. Elevated Pco2 increased C∶N ratios and interacted with elevated temperature to affect carapace mineralization. These changes were linked to concomitant changes in survivorship and growth, from which it was concluded that bottlenecks were evident during H. gammarus larval development in stages I and IV, the transition phases between the embryonic and pelagic larval stages and between the larval and megalopa stages, respectively. We therefore suggest that natural changes in optimum temperature during ontogeny will be key to larvae survival in a future warmer ocean. The interactions of these natural changes with elevated temperature and Pco2 significantly alter physiological condition and body size of the last larval stage before the transition from a planktonic to a benthic life style. Thus, living and growing in warm, hypercapnic waters could compromise larval lobster growth, development, and recruitment.

Bigger data, collaborative tools and the future of predictive drug discovery

NASA Astrophysics Data System (ADS)

Ekins, Sean; Clark, Alex M.; Swamidass, S. Joshua; Litterman, Nadia; Williams, Antony J.

2014-10-01

Over the past decade we have seen a growth in the provision of chemistry data and cheminformatics tools as either free websites or software as a service commercial offerings. These have transformed how we find molecule-related data and use such tools in our research. There have also been efforts to improve collaboration between researchers either openly or through secure transactions using commercial tools. A major challenge in the future will be how such databases and software approaches handle larger amounts of data as it accumulates from high throughput screening and enables the user to draw insights, enable predictions and move projects forward. We now discuss how information from some drug discovery datasets can be made more accessible and how privacy of data should not overwhelm the desire to share it at an appropriate time with collaborators. We also discuss additional software tools that could be made available and provide our thoughts on the future of predictive drug discovery in this age of big data. We use some examples from our own research on neglected diseases, collaborations, mobile apps and algorithm development to illustrate these ideas.

Optimizing future imaging survey of galaxies to confront dark energy and modified gravity models

NASA Astrophysics Data System (ADS)

Yamamoto, Kazuhiro; Parkinson, David; Hamana, Takashi; Nichol, Robert C.; Suto, Yasushi

2007-07-01

We consider the extent to which future imaging surveys of galaxies can distinguish between dark energy and modified gravity models for the origin of the cosmic acceleration. Dynamical dark energy models may have similar expansion rates as models of modified gravity, yet predict different growth of structure histories. We parametrize the cosmic expansion by the two parameters, w0 and wa, and the linear growth rate of density fluctuations by Linder’s γ, independently. Dark energy models generically predict γ≈0.55, while the Dvali-Gabadadze-Porrati (DGP) model γ≈0.68. To determine if future imaging surveys can constrain γ within 20% (or Δγ<0.1), we perform the Fisher matrix analysis for a weak-lensing survey such as the ongoing Hyper Suprime-Cam (HSC) project. Under the condition that the total observation time is fixed, we compute the figure of merit (FoM) as a function of the exposure time texp. We find that the tomography technique effectively improves the FoM, which has a broad peak around texp≃several˜10min; a shallow and wide survey is preferred to constrain the γ parameter. While Δγ<0.1 cannot be achieved by the HSC weak-lensing survey alone, one can improve the constraints by combining with a follow-up spectroscopic survey like Wide-field Fiber-fed Multi-Object Spectrograph (WFMOS) and/or future cosmic microwave background (CMB) observations.

Forecast of future aviation fuels: The model

NASA Technical Reports Server (NTRS)

Ayati, M. B.; Liu, C. Y.; English, J. M.

1981-01-01

A conceptual models of the commercial air transportation industry is developed which can be used to predict trends in economics, demand, and consumption. The methodology is based on digraph theory, which considers the interaction of variables and propagation of changes. Air transportation economics are treated by examination of major variables, their relationships, historic trends, and calculation of regression coefficients. A description of the modeling technique and a compilation of historic airline industry statistics used to determine interaction coefficients are included. Results of model validations show negligible difference between actual and projected values over the twenty-eight year period of 1959 to 1976. A limited application of the method presents forecasts of air tranportation industry demand, growth, revenue, costs, and fuel consumption to 2020 for two scenarios of future economic growth and energy consumption.

Urban change analysis and future growth of Istanbul.

PubMed

Akın, Anıl; Sunar, Filiz; Berberoğlu, Süha

2015-08-01

This study is aimed at analyzing urban change within Istanbul and assessing the city's future growth potential using appropriate approach modeling for the year 2040. Urban growth is a major driving force of land-use change, and spatial and temporal components of urbanization can be identified through accurate spatial modeling. In this context, widely used urban modeling approaches, such as the Markov chain and logistic regression based on cellular automata (CA), were used to simulate urban growth within Istanbul. The distance from each pixel to the urban and road classes, elevation, and slope, together with municipality and land use maps (as an excluded layer), were identified as factors. Calibration data were obtained from remotely sensed data recorded in 1972, 1986, and 2013. Validation was performed by overlaying the simulated and actual 2013 urban maps, and a kappa index of agreement was derived. The results indicate that urban expansion will influence mainly forest areas during the time period of 2013-2040. The urban expansion was predicted as 429 and 327 km(2) with the Markov chain and logistic regression models, respectively.

From the Lab to the Model: Using Historical Data to Forecast and Understand Harmful Algal Blooms

NASA Astrophysics Data System (ADS)

Doherty, O. M.; Gobler, C.; Hattenrath-Lehmann, T. K.; Griffith, A. W.; Davis, T. W.; Kang, Y.

2017-12-01

Ocean warming has expanded and shifted the niche of harmful algal blooms (HABs) in oceans and lakes globally. There is significant interest in using global climate models (GCMs) to predict future and ongoing shifts in HABs, however its unclear if our current understanding of HAB response to changing environmental conditions allow for sufficiently accurate predictions of HAB growth. Here we present an approach which uses resampling in conjunction with a meta-analysis of lab experiments to create robust and resilient models of HAB growth. Laboratory experiments yield a wide range of temperature growth rate responses and, as such, care must be taken to accurately convey the uncertainty of the relationship into any statistical model. Using high resolution sea surface temperature data, we produce probabilistic hindcasts of HAB growth rates and seasonal durations and compare to historical observations of HAB. Results from three studies will be presented: (1) showing expansion of the niche of and growth potential of Alexandrium fundyense and Dinophysis acuminate in the North Atlantic and North Pacific, (2) identifying shifts in the seasonality of and increases in growth potential of Cochlodinium polykrikoides in Long Island Sound and Chesapeake Bay and (3) reconstructing historical growth rates of multiple HAB species in Lake Erie. We conclude that warming ocean and lake temperature are an important factor facilitating the intensification of HABs and thus contributes to an expanding human health threat. Further, the success of this approach suggests that these ground truthed and experimentally constrained statistical models can be used as a basis for HAB predictions in GCMs.

Testing Einstein's gravity and dark energy with growth of matter perturbations: Indications for new physics?

NASA Astrophysics Data System (ADS)

Basilakos, Spyros; Nesseris, Savvas

2016-12-01

The growth index of matter fluctuations is computed for ten distinct accelerating cosmological models and confronted by the latest growth-rate data via a two-step process. First, we implement a joint statistical analysis in order to place constraints on the free parameters of all models using solely background data. Second, using the observed growth rate of clustering from various galaxy surveys we test the performance of the current cosmological models at the perturbation level while either marginalizing over σ8 or having it as a free parameter. As a result, we find that at a statistical level, i.e., after considering the best-fit χ2 or the value of the Akaike information criterion, most models are in very good agreement with the growth-rate data and are practically indistinguishable from Λ CDM . However, when we also consider the internal consistency of the models by comparing the theoretically predicted values of (γ0,γ1), i.e., the value of the growth index γ (z ) and its derivative today, with the best-fit ones, we find that the predictions of three out of ten dark energy models are in mild tension with the best-fit ones when σ8 is marginalized over. When σ8 is free we find that most models are not only in mild tension, but also predict low values for σ8. This could be attributed to either a systematic problem with the growth-rate data or the emergence of new physics at low redshifts, with the latter possibly being related to the well-known issue of the lack of power at small scales. Finally, by utilizing mock data based on an large synoptic survey telescope-like survey we show that with future surveys and by using the growth index parametrization, it will be possible to resolve the issue of the low σ8 but also the tension between the fitted and theoretically predicted values of (γ0,γ1).

Prenatal stress accelerates offspring growth to compensate for reduced maternal investment across mammals

PubMed Central

Berghänel, Andreas; Heistermann, Michael; Schülke, Oliver; Ostner, Julia

2017-01-01

Across mammals, prenatal maternal stress (PREMS) affects many aspects of offspring development, including offspring growth. However, how PREMS translates to offspring growth is inconsistent, even within species. To explain the full range of reported effects of prenatal adversity on offspring growth, we propose an integrative hypothesis: developmental constraints and a counteracting adaptive growth plasticity work in opposition to drive PREMS effects on growth. Mothers experiencing adversity reduce maternal investment leading to stunted growth (developmental constraints). Concomitantly, the pace of offspring life history is recalibrated to partly compensate for these developmental constraints (adaptive growth plasticity). Moreover, the relative importance of each process changes across ontogeny with increasing offspring independence. Thus, offspring exposed to PREMS may grow at the same rate as controls during gestation and lactation, but faster after weaning when direct maternal investment has ceased. We tested these predictions with a comparative analysis on the outcomes of 719 studies across 21 mammal species. First, the observed growth changes in response to PREMS varied across offspring developmental periods as predicted. We argue that the observed growth acceleration after weaning is not “catch-up growth,” because offspring that were small for age grew slower. Second, only PREMS exposure early during gestation produced adaptive growth plasticity. Our results suggest that PREMS effects benefit the mother’s future reproduction and at the same time accelerate offspring growth and possibly maturation and reproductive rate. In this sense, PREMS effects on offspring growth allow mother and offspring to make the best of a bad start. PMID:29180423

A review of fracture mechanics life technology

NASA Technical Reports Server (NTRS)

Besuner, P. M.; Harris, D. O.; Thomas, J. M.

1986-01-01

Lifetime prediction technology for structural components subjected to cyclic loads is examined. The central objectives of the project are: (1) to report the current state of the art, and (2) recommend future development of fracture mechanics-based analytical tools for modeling subcritical fatigue crack growth in structures. Of special interest is the ability to apply these tools to practical engineering problems and the developmental steps necessary to bring vital technologies to this stage. The authors conducted a survey of published literature and numerous discussions with experts in the field of fracture mechanics life technology. One of the key points made is that fracture mechanics analyses of crack growth often involve consideration of fatigue and fracture under extreme conditions. Therefore, inaccuracies in predicting component lifetime will be dominated by inaccuracies in environment and fatigue crack growth relations, stress intensity factor solutions, and methods used to model given loads and stresses. Suggestions made for reducing these inaccuracies include development of improved models of subcritical crack growth, research efforts aimed at better characterizing residual and assembly stresses that can be introduced during fabrication, and more widespread and uniform use of the best existing methods.

A review of fracture mechanics life technology

NASA Technical Reports Server (NTRS)

Thomas, J. M.; Besuner, P. M.; Harris, D. O.

1985-01-01

Current lifetime prediction technology for structural components subjected to cyclic loads was reviewed. The central objectives of the project were to report the current state of and recommend future development of fracture mechanics-based analytical tools for modeling and forecasting subcritical fatigue crack growth in structures. Of special interest to NASA was the ability to apply these tools to practical engineering problems and the developmental steps necessary to bring vital technologies to this stage. A survey of published literature and numerous discussions with experts in the field of fracture mechanics life technology were conducted. One of the key points made is that fracture mechanics analyses of crack growth often involve consideration of fatigue and fracture under extreme conditions. Therefore, inaccuracies in predicting component lifetime will be dominated by inaccuracies in environment and fatigue crack growth relations, stress intensity factor solutions, and methods used to model given loads and stresses. Suggestions made for reducing these inaccuracies include: development of improved models of subcritical crack growth, research efforts aimed at better characterizing residual and assembly stresses that can be introduced during fabrication, and more widespread and uniform use of the best existing methods.

Linking climate, gross primary productivity, and site index across forests of the western United States

Treesearch

Aaron R. Weiskittel; Nicholas L. Crookston; Philip J. Radtke

2011-01-01

Assessing forest productivity is important for developing effective management regimes and predicting future growth. Despite some important limitations, the most common means for quantifying forest stand-level potential productivity is site index (SI). Another measure of productivity is gross primary production (GPP). In this paper, SI is compared with GPP estimates...

A Detailed Rubric for Assessing the Quality of Teacher Resource Apps

ERIC Educational Resources Information Center

Cherner, Todd; Lee, Cheng-Yuan; Fegely, Alex; Santaniello, Lauren

2016-01-01

Since the advent of the iPhone and rise of mobile technologies, educational apps represent one of the fastest growing markets, and both the mobile technology and educational app markets are predicted to continue experiencing growth into the foreseeable future. The irony, however, is that even with a booming market for educational apps, very little…

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)…

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.

Taking the pulse of mountains: Ecosystem responses to climatic variability

USGS Publications Warehouse

Fagre, Daniel B.; Peterson, David L.; Hessl, Amy E.

2003-01-01

An integrated program of ecosystem modeling and field studies in the mountains of the Pacific Northwest (U.S.A.) has quantified many of the ecological processes affected by climatic variability. Paleoecological and contemporary ecological data in forest ecosystems provided model parameterization and validation at broad spatial and temporal scales for tree growth, tree regeneration and treeline movement. For subalpine tree species, winter precipitation has a strong negative correlation with growth; this relationship is stronger at higher elevations and west-side sites (which have more precipitation). Temperature affects tree growth at some locations with respect to length of growing season (spring) and severity of drought at drier sites (summer). Furthermore, variable but predictable climate-growth relationships across elevation gradients suggest that tree species respond differently to climate at different locations, making a uniform response of these species to future climatic change unlikely. Multi-decadal variability in climate also affects ecosystem processes. Mountain hemlock growth at high-elevation sites is negatively correlated with winter snow depth and positively correlated with the winter Pacific Decadal Oscillation (PDO) index. At low elevations, the reverse is true. Glacier mass balance and fire severity are also linked to PDO. Rapid establishment of trees in subalpine ecosystems during this century is increasing forest cover and reducing meadow cover at many subalpine locations in the western U.S.A. and precipitation (snow depth) is a critical variable regulating conifer expansion. Lastly, modeling potential future ecosystem conditions suggests that increased climatic variability will result in increasing forest fire size and frequency, and reduced net primary productivity in drier, east-side forest ecosystems. As additional empirical data and modeling output become available, we will improve our ability to predict the effects of climatic change across a broad range of climates and mountain ecosystems in the northwestern U.S.A.

Harvesting interacts with climate change to affect future habitat quality of a focal species in eastern Canada’s boreal forest

PubMed Central

Boulanger, Yan; Cyr, Dominic; Taylor, Anthony R.; Price, David T.; St-Laurent, Martin-Hugues

2018-01-01

Many studies project future bird ranges by relying on correlative species distribution models. Such models do not usually represent important processes explicitly related to climate change and harvesting, which limits their potential for predicting and understanding the future of boreal bird assemblages at the landscape scale. In this study, we attempted to assess the cumulative and specific impacts of both harvesting and climate-induced changes on wildfires and stand-level processes (e.g., reproduction, growth) in the boreal forest of eastern Canada. The projected changes in these landscape- and stand-scale processes (referred to as “drivers of change”) were then assessed for their impacts on future habitats and potential productivity of black-backed woodpecker (BBWO; Picoides arcticus), a focal species representative of deadwood and old-growth biodiversity in eastern Canada. Forest attributes were simulated using a forest landscape model, LANDIS-II, and were used to infer future landscape suitability to BBWO under three anthropogenic climate forcing scenarios (RCP 2.6, RCP 4.5 and RCP 8.5), compared to the historical baseline. We found climate change is likely to be detrimental for BBWO, with up to 92% decline in potential productivity under the worst-case climate forcing scenario (RCP 8.5). However, large declines were also projected under baseline climate, underlining the importance of harvest in determining future BBWO productivity. Present-day harvesting practices were the single most important cause of declining areas of old-growth coniferous forest, and hence appeared as the single most important driver of future BBWO productivity, regardless of the climate scenario. Climate-induced increases in fire activity would further promote young, deciduous stands at the expense of old-growth coniferous stands. This suggests that the biodiversity associated with deadwood and old-growth boreal forests may be greatly altered by the cumulative impacts of natural and anthropogenic disturbances under a changing climate. Management adaptations, including reduced harvesting levels and strategies to promote coniferous species content, may help mitigate these cumulative impacts. PMID:29414989

Harvesting interacts with climate change to affect future habitat quality of a focal species in eastern Canada's boreal forest.

PubMed

Tremblay, Junior A; Boulanger, Yan; Cyr, Dominic; Taylor, Anthony R; Price, David T; St-Laurent, Martin-Hugues

2018-01-01

Many studies project future bird ranges by relying on correlative species distribution models. Such models do not usually represent important processes explicitly related to climate change and harvesting, which limits their potential for predicting and understanding the future of boreal bird assemblages at the landscape scale. In this study, we attempted to assess the cumulative and specific impacts of both harvesting and climate-induced changes on wildfires and stand-level processes (e.g., reproduction, growth) in the boreal forest of eastern Canada. The projected changes in these landscape- and stand-scale processes (referred to as "drivers of change") were then assessed for their impacts on future habitats and potential productivity of black-backed woodpecker (BBWO; Picoides arcticus), a focal species representative of deadwood and old-growth biodiversity in eastern Canada. Forest attributes were simulated using a forest landscape model, LANDIS-II, and were used to infer future landscape suitability to BBWO under three anthropogenic climate forcing scenarios (RCP 2.6, RCP 4.5 and RCP 8.5), compared to the historical baseline. We found climate change is likely to be detrimental for BBWO, with up to 92% decline in potential productivity under the worst-case climate forcing scenario (RCP 8.5). However, large declines were also projected under baseline climate, underlining the importance of harvest in determining future BBWO productivity. Present-day harvesting practices were the single most important cause of declining areas of old-growth coniferous forest, and hence appeared as the single most important driver of future BBWO productivity, regardless of the climate scenario. Climate-induced increases in fire activity would further promote young, deciduous stands at the expense of old-growth coniferous stands. This suggests that the biodiversity associated with deadwood and old-growth boreal forests may be greatly altered by the cumulative impacts of natural and anthropogenic disturbances under a changing climate. Management adaptations, including reduced harvesting levels and strategies to promote coniferous species content, may help mitigate these cumulative impacts.

FORUM - FutureTox II: In vitro Data and In Silico Models for ...

EPA Pesticide Factsheets

FutureTox II, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in January, 2014. The meeting goals were to review and discuss the state of the science in toxicology in the context of implementing the NRC 21st century vision of predicting in vivo responses from in vitro and in silico data, and to define the goals for the future. Presentations and discussions were held on priority concerns such as predicting and modeling of metabolism, cell growth and differentiation, effects on sensitive subpopulations, and integrating data into risk assessment. Emerging trends in technologies such as stem cell-derived human cells, 3D organotypic culture models, mathematical modeling of cellular processes and morphogenesis, adverse outcome pathway development, and high-content imaging of in vivo systems were discussed. Although advances in moving towards an in vitro/in silico based risk assessment paradigm were apparent, knowledge gaps in these areas and limitations of technologies were identified. Specific recommendations were made for future directions and research needs in the areas of hepatotoxicity, cancer prediction, developmental toxicity, and regulatory toxicology. This article reports on the outcome of FutureTox II1,2, the second in a series of Society of Toxicology (SOT) Contemporary Concepts in Toxicology (CCT) Workshops, which was attended by invitees and participants from governmental and regulatory agencies, research institutes, academ

Escaping herbivory: ocean warming as a refuge for primary producers where consumer metabolism and consumption cannot pursue.

PubMed

Mertens, Nicole L; Russell, Bayden D; Connell, Sean D

2015-12-01

Ocean warming is anticipated to strengthen the persistence of turf-forming habitat, yet the concomitant elevation of grazer metabolic rates may accelerate per capita rates of consumption to counter turf predominance. Whilst this possibility of strong top-down control is supported by the metabolic theory of ecology (MTE), it assumes that consumer metabolism and consumption keep pace with increasing production. This assumption was tested by quantifying the metabolic rates of turfs and herbivorous gastropods under a series of elevated temperatures in which the ensuing production and consumption were observed. We discovered that as temperature increases towards near-future levels (year 2100), consumption rates of gastropods peak earlier than the rate of growth of producers. Hence, turfs have greater capacity to persist under near-future temperatures than the capacity for herbivores to counter their growth. These results suggest that whilst MTE predicts stronger top-down control, understanding whether consumer-producer responses are synchronous is key to assessing the future strength of top-down control.

A design of mathematical modelling for the mudharabah scheme in shariah insurance

NASA Astrophysics Data System (ADS)

Cahyandari, R.; Mayaningsih, D.; Sukono

2017-01-01

Indonesian Shariah Insurance Association (AASI) believes that 2014 is the year of Indonesian Shariah insurance, since its growth was above the conventional insurance. In December 2013, 43% growth was recorded for shariah insurance, while the conventional insurance was only hit 20%. This means that shariah insurance has tremendous potential to remain growing in the future. In addition, the growth can be predicted from the number of conventional insurance companies who open sharia division, along with the development of Islamic banking development which automatically demand the role of shariah insurance to protect assets and banking transactions. The development of shariah insurance should be accompanied by the development of premium fund management mechanism, in order to create innovation on shariah insurance products which beneficial for the society. The development of premium fund management model shows a positive progress through the emergence of Mudharabah, Wakala, Hybrid (Mudharabah-Wakala), and Wakala-Waqf. However, ‘model’ term that referred in this paper is regarded as an operational model in form of a scheme of management mechanism. Therefore, this paper will describe a mathematical modeling for premium fund management scheme, especially for Mudharabah concept. Mathematical modeling is required for an analysis process that can be used to predict risks that could be faced by a company in the future, so that the company could take a precautionary policy to minimize those risks.

Sensitivity of salmonid freshwater life history in western US streams to future climate conditions.

PubMed

Beer, W Nicholas; Anderson, James J

2013-08-01

We projected effects of mid-21st century climate on the early life growth of Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in western United States streams. Air temperature and snowpack trends projected from observed 20th century trends were used to predict future seasonal stream temperatures. Fish growth from winter to summer was projected with temperature-dependent models of egg development and juvenile growth. Based on temperature data from 115 sites, by mid-21st century, the effects of climate change are projected to be mixed. Fish in warm-region streams that are currently cooled by snow melt will grow less, and fish in suboptimally cool streams will grow more. Relative to 20th century conditions, by mid-21st century juvenile salmonids' weights are expected to be lower in the Columbia Basin and California Central Valley, but unchanged or greater in coastal and mountain streams. Because fish weight affects fish survival, the predicted changes in weight could impact population fitness depending on other factors such as density effects, food quality and quantity changes, habitat alterations, etc. The level of year-to-year variability in stream temperatures is high and our analysis suggests that identifying effects of climate change over the natural variability will be difficult except in a few streams. © 2013 John Wiley & Sons Ltd.

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.

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.

Placental weight and foetal growth rate as predictors of ischaemic heart disease in a Swedish cohort.

PubMed

Heshmati, A; Koupil, I

2014-06-01

Studies on placental size and cardiovascular disease have shown inconsistent results. We followed 10,503 men and women born in Uppsala, Sweden, 1915-1929 from 1964 to 2008 to assess whether birth characteristics, including placental weight and placenta/birth weight ratio, were predictive of future ischaemic heart disease (IHD). Adjustments were made for birth cohort, age, sex, mother's parity, birth weight, gestational age and social class at birth. Placental weight and birth weight were negatively associated with IHD. The effect of placental weight on IHD was stronger in individuals from medium social class at birth and in those with low education. Men and women from non-manual social class at birth had the lowest risk for IHD as adults. We conclude that low foetal growth rate rather than placental weight was more predictive of IHD in the Swedish cohort. However, the strong effect of social class at birth on risk for IHD did not appear to be mediated by foetal growth rate.

Lunisolar tidal force and the growth of plant roots, and some other of its effects on plant movements.

PubMed

Barlow, Peter W; Fisahn, Joachim

2012-07-01

Correlative evidence has often suggested that the lunisolar tidal force, to which the Sun contributes 30 % and the Moon 60 % of the combined gravitational acceleration, regulates a number of features of plant growth upon Earth. The time scales of the effects studied have ranged from the lunar day, with a period of approx. 24.8 h, to longer, monthly or seasonal variations. We review evidence for a lunar involvement with plant growth. In particular, we describe experimental observations which indicate a putative lunar-based relationship with the rate of elongation of roots of Arabidopsis thaliana maintained in constant light. The evidence suggests that there may be continuous modulation of root elongation growth by the lunisolar tidal force. In order to provide further supportive evidence for a more general hypothesis of a lunisolar regulation of growth, we highlight similarly suggestive evidence from the time courses of (a) bean leaf movements obtained from kymographic observations; (b) dilatation cycles of tree stems obtained from dendrograms; and (c) the diurnal changes of wood-water relationships in a living tree obtained by reflectometry. At present, the evidence for a lunar or a lunisolar influence on root growth or, indeed, on any other plant system, is correlative, and therefore circumstantial. Although it is not possible to alter the lunisolar gravitational force experienced by living organisms on Earth, it is possible to predict how this putative lunisolar influence will vary at times in the near future. This may offer ways of testing predictions about possible Moon-plant relationships. As for a hypothesis about how the three-body system of Earth-Sun-Moon could interact with biological systems to produce a specific growth response, this remains a challenge for the future. Plant growth responses are mainly brought about by differential movement of water across protoplasmic membranes in conjunction with water movement in the super-symplasm. It may be in this realm of water movements, or even in the physical forms which water adopts within cells, that the lunisolar tidal force has an impact upon living growth systems.

Lunisolar tidal force and the growth of plant roots, and some other of its effects on plant movements

PubMed Central

Barlow, Peter W.; Fisahn, Joachim

2012-01-01

Background Correlative evidence has often suggested that the lunisolar tidal force, to which the Sun contributes 30 % and the Moon 60 % of the combined gravitational acceleration, regulates a number of features of plant growth upon Earth. The time scales of the effects studied have ranged from the lunar day, with a period of approx. 24·8 h, to longer, monthly or seasonal variations. Scope We review evidence for a lunar involvement with plant growth. In particular, we describe experimental observations which indicate a putative lunar-based relationship with the rate of elongation of roots of Arabidopsis thaliana maintained in constant light. The evidence suggests that there may be continuous modulation of root elongation growth by the lunisolar tidal force. In order to provide further supportive evidence for a more general hypothesis of a lunisolar regulation of growth, we highlight similarly suggestive evidence from the time courses of (a) bean leaf movements obtained from kymographic observations; (b) dilatation cycles of tree stems obtained from dendrograms; and (c) the diurnal changes of wood–water relationships in a living tree obtained by reflectometry. Conclusions At present, the evidence for a lunar or a lunisolar influence on root growth or, indeed, on any other plant system, is correlative, and therefore circumstantial. Although it is not possible to alter the lunisolar gravitational force experienced by living organisms on Earth, it is possible to predict how this putative lunisolar influence will vary at times in the near future. This may offer ways of testing predictions about possible Moon–plant relationships. As for a hypothesis about how the three-body system of Earth–Sun–Moon could interact with biological systems to produce a specific growth response, this remains a challenge for the future. Plant growth responses are mainly brought about by differential movement of water across protoplasmic membranes in conjunction with water movement in the super-symplasm. It may be in this realm of water movements, or even in the physical forms which water adopts within cells, that the lunisolar tidal force has an impact upon living growth systems. PMID:22437666

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

Title: Freshwater phytoplankton responses to global warming.

PubMed

Wagner, Heiko; Fanesi, Andrea; Wilhelm, Christian

2016-09-20

Global warming alters species composition and function of freshwater ecosystems. However, the impact of temperature on primary productivity is not sufficiently understood and water quality models need to be improved in order to assess the quantitative and qualitative changes of aquatic communities. On the basis of experimental data, we demonstrate that the commonly used photosynthetic and water chemistry parameters alone are not sufficient for modeling phytoplankton growth under changing temperature regimes. We present some new aspects of the acclimation process with respect to temperature and how contrasting responses may be explained by a more complete physiological knowledge of the energy flow from photons to new biomass. We further suggest including additional bio-markers/traits for algal growth such as carbon allocation patterns to increase the explanatory power of such models. Although carbon allocation patterns are promising and functional cellular traits for growth prediction under different nutrient and light conditions, their predictive power still waits to be tested with respect to temperature. A great challenge for the near future will be the prediction of primary production efficiencies under the global change scenario using a uniform model for phytoplankton assemblages. Copyright © 2016 Elsevier GmbH. All rights reserved.

A comparative analysis of soft computing techniques for gene prediction.

PubMed

Goel, Neelam; Singh, Shailendra; Aseri, Trilok Chand

2013-07-01

The rapid growth of genomic sequence data for both human and nonhuman species has made analyzing these sequences, especially predicting genes in them, very important and is currently the focus of many research efforts. Beside its scientific interest in the molecular biology and genomics community, gene prediction is of considerable importance in human health and medicine. A variety of gene prediction techniques have been developed for eukaryotes over the past few years. This article reviews and analyzes the application of certain soft computing techniques in gene prediction. First, the problem of gene prediction and its challenges are described. These are followed by different soft computing techniques along with their application to gene prediction. In addition, a comparative analysis of different soft computing techniques for gene prediction is given. Finally some limitations of the current research activities and future research directions are provided. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

REG1B as a predictor of childhood stunting in Bangladesh and Peru123

PubMed Central

Peterson, Kristine M; Buss, Janice; Easley, Rebecca; Yang, Zhengyu; Korpe, Poonum S; Niu, Feiyang; Ma, Jennie Z; Olortegui, Maribel Paredes; Haque, Rashidul; Kosek, Margaret N; Petri, William A

2013-01-01

Background: Undernutrition remains a significant problem worldwide, with environmental enteropathy implicated as a contributing factor. An understanding of the pathogenesis and identification of children at risk are critical to the design of more-effective interventions. Objective: The stool regenerating gene 1β (REG1B) protein, which is a putative measure of intestinal injury and repair, was tested as a noninvasive biomarker of future childhood stunting. Design: A total of 222 children from Bangladesh and 97 children from Peru, who were from impoverished communities, were followed from birth through 24 mo of age with anthropometric measures obtained every 3 mo. Stool REG1B protein concentrations were obtained by using an REG1B polyclonal-polyclonal ELISA at 3 mo of age. We tested for the ability of REG1B to forecast future anthropometric shortfalls, independent of known predictors of undernutrition of family income and baseline height and weight. Results: In the Bangladesh cohort of 222 children, higher REG1B concentrations at month 3 were significantly and independently associated with a growth shortfall in a linear regression analysis at months 9, 12, 18, 21, and 24 and, in the Peru cohort, at months 12, 15, 18, 21, and 24. With the use of a mixed model for repeated measurements, higher stool REG1B concentrations at 3 mo were also independently predictive of a lower future length-for-age z score through 24 mo of age (Bangladesh P = 0.006; Peru P = 0.058). Conclusion: The ability of fecal REG1B to predict growth shortfall in independent cohorts of impoverished children from the developing world offers promise as a malnutrition biomarker and supports a role for environmental enteropathy in the pathogenesis of growth shortfall. PMID:23553156

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

Dynamic modeling of green algae cultivation in a photobioreactor for sustainable biodiesel production.

PubMed

Del Rio-Chanona, Ehecatl A; Liu, Jiao; Wagner, Jonathan L; Zhang, Dongda; Meng, Yingying; Xue, Song; Shah, Nilay

2018-02-01

Biodiesel produced from microalgae has been extensively studied due to its potentially outstanding advantages over traditional transportation fuels. In order to facilitate its industrialization and improve the process profitability, it is vital to construct highly accurate models capable of predicting the complex behavior of the investigated biosystem for process optimization and control, which forms the current research goal. Three original contributions are described in this paper. Firstly, a dynamic model is constructed to simulate the complicated effect of light intensity, nutrient supply and light attenuation on both biomass growth and biolipid production. Secondly, chlorophyll fluorescence, an instantly measurable variable and indicator of photosynthetic activity, is embedded into the model to monitor and update model accuracy especially for the purpose of future process optimal control, and its correlation between intracellular nitrogen content is quantified, which to the best of our knowledge has never been addressed so far. Thirdly, a thorough experimental verification is conducted under different scenarios including both continuous illumination and light/dark cycle conditions to testify the model predictive capability particularly for long-term operation, and it is concluded that the current model is characterized by a high level of predictive capability. Based on the model, the optimal light intensity for algal biomass growth and lipid synthesis is estimated. This work, therefore, paves the way to forward future process design and real-time optimization. © 2017 Wiley Periodicals, Inc.

Auralization Architectures for NASA?s Next Generation Aircraft Noise Prediction Program

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Lopes, Leonard V.; Burley, Casey L.; Aumann, Aric R.

2013-01-01

Aircraft community noise is a significant concern due to continued growth in air traffic, increasingly stringent environmental goals, and operational limitations imposed by airport authorities. The assessment of human response to noise from future aircraft can only be afforded through laboratory testing using simulated flyover noise. Recent work by the authors demonstrated the ability to auralize predicted flyover noise for a state-of-the-art reference aircraft and a future hybrid wing body aircraft concept. This auralization used source noise predictions from NASA's Aircraft NOise Prediction Program (ANOPP) as input. The results from this process demonstrated that auralization based upon system noise predictions is consistent with, and complementary to, system noise predictions alone. To further develop and validate the auralization process, improvements to the interfaces between the synthesis capability and the system noise tools are required. This paper describes the key elements required for accurate noise synthesis and introduces auralization architectures for use with the next-generation ANOPP (ANOPP2). The architectures are built around a new auralization library and its associated Application Programming Interface (API) that utilize ANOPP2 APIs to access data required for auralization. The architectures are designed to make the process of auralizing flyover noise a common element of system noise prediction.

Large-scale dynamo growth rates from numerical simulations and implications for mean-field theories

NASA Astrophysics Data System (ADS)

Park, Kiwan; Blackman, Eric G.; Subramanian, Kandaswamy

2013-05-01

Understanding large-scale magnetic field growth in turbulent plasmas in the magnetohydrodynamic limit is a goal of magnetic dynamo theory. In particular, assessing how well large-scale helical field growth and saturation in simulations match those predicted by existing theories is important for progress. Using numerical simulations of isotropically forced turbulence without large-scale shear with its implications, we focus on several additional aspects of this comparison: (1) Leading mean-field dynamo theories which break the field into large and small scales predict that large-scale helical field growth rates are determined by the difference between kinetic helicity and current helicity with no dependence on the nonhelical energy in small-scale magnetic fields. Our simulations show that the growth rate of the large-scale field from fully helical forcing is indeed unaffected by the presence or absence of small-scale magnetic fields amplified in a precursor nonhelical dynamo. However, because the precursor nonhelical dynamo in our simulations produced fields that were strongly subequipartition with respect to the kinetic energy, we cannot yet rule out the potential influence of stronger nonhelical small-scale fields. (2) We have identified two features in our simulations which cannot be explained by the most minimalist versions of two-scale mean-field theory: (i) fully helical small-scale forcing produces significant nonhelical large-scale magnetic energy and (ii) the saturation of the large-scale field growth is time delayed with respect to what minimalist theory predicts. We comment on desirable generalizations to the theory in this context and future desired work.

Large-scale dynamo growth rates from numerical simulations and implications for mean-field theories.

PubMed

Park, Kiwan; Blackman, Eric G; Subramanian, Kandaswamy

2013-05-01

Understanding large-scale magnetic field growth in turbulent plasmas in the magnetohydrodynamic limit is a goal of magnetic dynamo theory. In particular, assessing how well large-scale helical field growth and saturation in simulations match those predicted by existing theories is important for progress. Using numerical simulations of isotropically forced turbulence without large-scale shear with its implications, we focus on several additional aspects of this comparison: (1) Leading mean-field dynamo theories which break the field into large and small scales predict that large-scale helical field growth rates are determined by the difference between kinetic helicity and current helicity with no dependence on the nonhelical energy in small-scale magnetic fields. Our simulations show that the growth rate of the large-scale field from fully helical forcing is indeed unaffected by the presence or absence of small-scale magnetic fields amplified in a precursor nonhelical dynamo. However, because the precursor nonhelical dynamo in our simulations produced fields that were strongly subequipartition with respect to the kinetic energy, we cannot yet rule out the potential influence of stronger nonhelical small-scale fields. (2) We have identified two features in our simulations which cannot be explained by the most minimalist versions of two-scale mean-field theory: (i) fully helical small-scale forcing produces significant nonhelical large-scale magnetic energy and (ii) the saturation of the large-scale field growth is time delayed with respect to what minimalist theory predicts. We comment on desirable generalizations to the theory in this context and future desired work.

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.

A boundary current drives synchronous growth of marine fishes across tropical and temperate latitudes.

PubMed

Ong, Joyce J L; Rountrey, Adam N; Black, Bryan A; Nguyen, Hoang Minh; Coulson, Peter G; Newman, Stephen J; Wakefield, Corey B; Meeuwig, Jessica J; Meekan, Mark G

2018-05-01

Entrainment of growth patterns of multiple species to single climatic drivers can lower ecosystem resilience and increase the risk of species extinction during stressful climatic events. However, predictions of the effects of climate change on the productivity and dynamics of marine fishes are hampered by a lack of historical data on growth patterns. We use otolith biochronologies to show that the strength of a boundary current, modulated by the El Niño-Southern Oscillation, accounted for almost half of the shared variance in annual growth patterns of five of six species of tropical and temperate marine fishes across 23° of latitude (3000 km) in Western Australia. Stronger flow during La Niña years drove increased growth of five species, whereas weaker flow during El Niño years reduced growth. Our work is the first to link the growth patterns of multiple fishes with a single oceanographic/climate phenomenon at large spatial scales and across multiple climate zones, habitat types, trophic levels and depth ranges. Extreme La Niña and El Niño events are predicted to occur more frequently in the future and these are likely to have implications for these vulnerable ecosystems, such as a limited capacity of the marine taxa to recover from stressful climatic events. © 2018 John Wiley & Sons Ltd.

Modeling Allometric Relationships in Leaves of Young Rapeseed (Brassica napus L.) Grown at Different Temperature Treatments

PubMed Central

Tian, Tian; Wu, Lingtong; Henke, Michael; Ali, Basharat; Zhou, Weijun; Buck-Sorlin, Gerhard

2017-01-01

Functional–structural plant modeling (FSPM) is a fast and dynamic method to predict plant growth under varying environmental conditions. Temperature is a primary factor affecting the rate of plant development. In the present study, we used three different temperature treatments (10/14°C, 18/22°C, and 26/30°C) to test the effect of temperature on growth and development of rapeseed (Brassica napus L.) seedlings. Plants were sampled at regular intervals (every 3 days) to obtain growth data during the length of the experiment (1 month in total). Total leaf dry mass, leaf area, leaf mass per area (LMA), width-length ratio, and the ratio of petiole length to leaf blade length (PBR), were determined and statistically analyzed, and contributed to a morphometric database. LMA under high temperature was significantly smaller than LMA under medium and low temperature, while leaves at high temperature were significantly broader. An FSPM of rapeseed seedlings featuring a growth function used for leaf extension and biomass accumulation was implemented by combining measurement with literature data. The model delivered new insights into growth and development dynamics of winter oilseed rape seedlings. The present version of the model mainly focuses on the growth of plant leaves. However, future extensions of the model could be used in practice to better predict plant growth in spring and potential cold damage of the crop. PMID:28377775

Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change.

PubMed

Bestion, Elvire; Teyssier, Aimeric; Richard, Murielle; Clobert, Jean; Cote, Julien

2015-10-01

Evidence has accumulated in recent decades on the drastic impact of climate change on biodiversity. Warming temperatures have induced changes in species physiology, phenology, and have decreased body size. Such modifications can impact population dynamics and could lead to changes in life cycle and demography. More specifically, conceptual frameworks predict that global warming will severely threaten tropical ectotherms while temperate ectotherms should resist or even benefit from higher temperatures. However, experimental studies measuring the impacts of future warming trends on temperate ectotherms' life cycle and population persistence are lacking. Here we investigate the impacts of future climates on a model vertebrate ectotherm species using a large-scale warming experiment. We manipulated climatic conditions in 18 seminatural populations over two years to obtain a present climate treatment and a warm climate treatment matching IPCC predictions for future climate. Warmer temperatures caused a faster body growth, an earlier reproductive onset, and an increased voltinism, leading to a highly accelerated life cycle but also to a decrease in adult survival. A matrix population model predicts that warm climate populations in our experiment should go extinct in around 20 y. Comparing our experimental climatic conditions to conditions encountered by populations across Europe, we suggest that warming climates should threaten a significant number of populations at the southern range of the distribution. Our findings stress the importance of experimental approaches on the entire life cycle to more accurately predict population and species persistence in future climates.

Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change

PubMed Central

Bestion, Elvire; Teyssier, Aimeric; Richard, Murielle; Clobert, Jean; Cote, Julien

2015-01-01

Evidence has accumulated in recent decades on the drastic impact of climate change on biodiversity. Warming temperatures have induced changes in species physiology, phenology, and have decreased body size. Such modifications can impact population dynamics and could lead to changes in life cycle and demography. More specifically, conceptual frameworks predict that global warming will severely threaten tropical ectotherms while temperate ectotherms should resist or even benefit from higher temperatures. However, experimental studies measuring the impacts of future warming trends on temperate ectotherms' life cycle and population persistence are lacking. Here we investigate the impacts of future climates on a model vertebrate ectotherm species using a large-scale warming experiment. We manipulated climatic conditions in 18 seminatural populations over two years to obtain a present climate treatment and a warm climate treatment matching IPCC predictions for future climate. Warmer temperatures caused a faster body growth, an earlier reproductive onset, and an increased voltinism, leading to a highly accelerated life cycle but also to a decrease in adult survival. A matrix population model predicts that warm climate populations in our experiment should go extinct in around 20 y. Comparing our experimental climatic conditions to conditions encountered by populations across Europe, we suggest that warming climates should threaten a significant number of populations at the southern range of the distribution. Our findings stress the importance of experimental approaches on the entire life cycle to more accurately predict population and species persistence in future climates. PMID:26501958

Impact of the 3 °C temperature rise on bacterial growth and carbon transfer towards higher trophic levels: Empirical models for the Adriatic Sea

NASA Astrophysics Data System (ADS)

Šolić, Mladen; Krstulović, Nada; Šantić, Danijela; Šestanović, Stefanija; Kušpilić, Grozdan; Bojanić, Natalia; Ordulj, Marin; Jozić, Slaven; Vrdoljak, Ana

2017-09-01

The Mediterranean Sea (including the Adriatic Sea) has been identified as a 'hotspot' for climate change, with the prediction of the increase in water temperature of 2-4 °C over the next few decades. Being mainly oligotrophic, and strongly phosphorus limited, the Adriatic Sea is characterized by the important role of the microbial food web in production and transfer of biomass and energy towards higher trophic levels. We hypothesized that predicted 3 °C temperature rise in the near future might cause an increase of bacterial production and bacterial losses to grazers, which could significantly enlarge the trophic base for metazoans. This empirical study is based on a combined 'space-for-time substitution' analysis (which is performed on 3583 data sets) and on an experimental approach (36 in situ grazing experiments performed at different temperatures). It showed that the predicted 3 °C temperature increase (which is a result of global warming) in the near future could cause a significant increase in bacterial growth at temperatures lower than 16 °C (during the colder winter-spring period, as well as in the deeper layers). The effect of temperature on bacterial growth could be additionally doubled in conditions without phosphorus limitation. Furthermore, a 3 °C increase in temperature could double the grazing on bacteria by heterotrophic nanoflagellate (HNF) and ciliate predators and it could increase the proportion of bacterial production transferred to the metazoan food web by 42%. Therefore, it is expected that global warming may further strengthen the role of the microbial food web in a carbon cycle in the Adriatic Sea.

Predicting response to EGFR inhibitors in metastatic colorectal cancer: current practice and future directions.

PubMed

Shankaran, Veena; Obel, Jennifer; Benson, Al B

2010-01-01

The identification of KRAS mutational status as a predictive marker of response to antibodies against the epidermal growth factor receptor (EGFR) has been one of the most significant and practice-changing recent advances in colorectal cancer research. Recently, data suggesting a potential role for other markers (including BRAF mutations, loss of phosphatase and tension homologue deleted on chromosome ten expression, and phosphatidylinositol-3-kinase-AKT pathway mutations) in predicting response to anti-EGFR therapy have emerged. Ongoing clinical trials and correlative analyses are essential to definitively identify predictive markers and develop therapeutic strategies for patients who may not derive benefit from anti-EGFR therapy. This article reviews recent clinical trials supporting the predictive role of KRAS, recent changes to clinical guidelines and pharmaceutical labeling, investigational predictive molecular markers, and newer clinical trials targeting patients with mutated KRAS.

Hot Academic Jobs of the Future: Try These Fields

ERIC Educational Resources Information Center

Roberts, Lee

2009-01-01

At a time when the academic job market is looking bleak, the author asked career experts and economic forecasters to predict where faculty job growth could come in the next decade. Many agreed that job prospects will be dim because of budget cuts and diminishing faculty pension funds that have made professors less likely to retire. In addition,…

Pocket Handbook on Reliability

DTIC Science & Technology

1975-09-01

exponencial distributions Weibull distribution, -xtimating reliability, confidence intervals, relia- bility growth, 0. P- curves, Bayesian analysis. 20 A S...introduction for those not familiar with reliability and a good refresher for those who are currently working in the area. LEWIS NERI, CHIEF...includes one or both of the following objectives: a) prediction of the current system reliability, b) projection on the system reliability for someI future

Above-Campus Services: Shaping the Promise of Cloud Computing for Higher Education

ERIC Educational Resources Information Center

Wheeler, Brad; Waggener, Shelton

2009-01-01

The concept of today's cloud computing may date back to 1961, when John McCarthy, retired Stanford professor and Turing Award winner, delivered a speech at MIT's Centennial. In that speech, he predicted that in the future, computing would become a "public utility." Yet for colleges and universities, the recent growth of pervasive, very high speed…

The U.S. forest sector in 2030: Markets and competitors

Treesearch

James A. Turner; Joseph Buongiorno; Shushuai Zhu; Jeffrey P. Prestemon

2005-01-01

The Global Forest Products Model was used to project international forest sector developments, conditional on the latest RPA Timber Assessment of future domestic changes in the United States. While the United States, Japan, and Europe were predicted to remain major importers of forest products out to 2030, the rapid economic growth of China would make it the world...

Educational Support for Orphans and Vulnerable Children in Primary Schools: Challenges and Interventions

ERIC Educational Resources Information Center

Mwoma, Teresa; Pillay, Jace

2016-01-01

Educational status is an important indicator of children's wellbeing and future life opportunities. It can predict growth potential and economic viability of a state. While this is an ideal situation for all children, the case may be different for orphans and vulnerable children (OVC) due to the challenges they go through on a daily basis. This…

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

A Hierarchical Analysis of Tree Growth and Environmental Drivers Across Eastern US Temperate Forests

NASA Astrophysics Data System (ADS)

Mantooth, J.; Dietze, M.

2014-12-01

Improving predictions of how forests in the eastern United States will respond to future global change requires a better understanding of the drivers of variability in tree growth rates. Current inventory data lack the temporal resolution to characterize interannual variability, while existing growth records lack the extent required to assess spatial scales of variability. Therefore, we established a network of forest inventory plots across ten sites across the eastern US, and measured growth in adult trees using increment cores. Sites were chosen to maximize climate space explored, while within sites, plots were spread across primary environmental gradients to explore landscape-level variability in growth. Using the annual growth record available from tree cores, we explored the responses of trees to multiple environmental covariates over multiple spatial and temporal scales. We hypothesized that within and across sites growth rates vary among species, and that intraspecific growth rates increase with temperature along a species' range. We also hypothesized that trees show synchrony in growth responses to landscape-scale climatic changes. Initial analyses of growth increments indicate that across sites, trees with intermediate shade tolerance, e.g. Red Oak (Quercus rubra), tend to have the highest growth rates. At the site level, there is evidence for synchrony in response to large-scale climatic events (e.g. prolonged drought and above average temperatures). However, growth responses to climate at the landscape scale have yet to be detected. Our current analysis utilizes hierarchical Bayesian state-space modeling to focus on growth responses of adult trees to environmental covariates at multiple spatial and temporal scales. This predictive model of tree growth currently incorporates observed effects at the individual, plot, site, and landscape scale. Current analysis using this model shows a potential slowing of growth in the past decade for two sites in the northeastern US (Harvard Forest and Bartlett Experimental Forest), however more work is required to determine the robustness of this trend. Finally, these observations are being incorporated into ecosystem models using the Brown Dog informatics tools and the Predictive Ecosystem Analyzer (PEcAn) data assimilation workflow.

Biophysical modelling of intra-ring variations in tracheid features and wood density of Pinus pinaster trees exposed to seasonal droughts.

PubMed

Wilkinson, Sarah; Ogée, Jérôme; Domec, Jean-Christophe; Rayment, Mark; Wingate, Lisa

2015-03-01

Process-based models that link seasonally varying environmental signals to morphological features within tree rings are essential tools to predict tree growth response and commercially important wood quality traits under future climate scenarios. This study evaluated model portrayal of radial growth and wood anatomy observations within a mature maritime pine (Pinus pinaster (L.) Aït.) stand exposed to seasonal droughts. Intra-annual variations in tracheid anatomy and wood density were identified through image analysis and X-ray densitometry on stem cores covering the growth period 1999-2010. A cambial growth model was integrated with modelled plant water status and sugar availability from the soil-plant-atmosphere transfer model MuSICA to generate estimates of cell number, cell volume, cell mass and wood density on a weekly time step. The model successfully predicted inter-annual variations in cell number, ring width and maximum wood density. The model was also able to predict the occurrence of special anatomical features such as intra-annual density fluctuations (IADFs) in growth rings. Since cell wall thickness remained surprisingly constant within and between growth rings, variations in wood density were primarily the result of variations in lumen diameter, both in the model and anatomical data. In the model, changes in plant water status were identified as the main driver of the IADFs through a direct effect on cell volume. The anatomy data also revealed that a trade-off existed between hydraulic safety and hydraulic efficiency. Although a simplified description of cambial physiology is presented, this integrated modelling approach shows potential value for identifying universal patterns of tree-ring growth and anatomical features over a broad climatic gradient. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Uniform shrub growth response to June temperature across the North Slope of Alaska

NASA Astrophysics Data System (ADS)

Ackerman, Daniel E.; Griffin, Daniel; Hobbie, Sarah E.; Popham, Kelly; Jones, Erin; Finlay, Jacques C.

2018-04-01

The expansion of woody shrubs in arctic tundra alters many aspects of high-latitude ecosystems, including carbon cycling and wildlife habitat. Dendroecology, the study of annual growth increments in woody plants, has shown promise in revealing how climate and environmental conditions interact with shrub growth to affect these key ecosystem properties. However, a predictive understanding of how shrub growth response to climate varies across the heterogeneous landscape remains elusive. Here we use individual-based mixed effects modeling to analyze 19 624 annual growth ring measurements in the stems of Salix pulchra (Cham.), a rapidly expanding deciduous shrub. Stem samples were collected at six sites throughout the North Slope of Alaska. Sites spanned four landscapes that varied in time since glaciation and hence in soil properties, such as nutrient availability, that we expected would modulate shrub growth response to climate. Ring growth was remarkably coherent among sites and responded positively to mean June temperature. The strength of this climate response varied slightly among glacial landscapes, but in contrast to expectations, this variability was not systematically correlated with landscape age. Additionally, shrubs at all sites exhibited diminishing marginal growth gains in response to increasing temperatures, indicative of alternative growth limiting mechanisms in particularly warm years, such as temperature-induced moisture limitation. Our results reveal a regionally-coherent and robust shrub growth response to early season growing temperature, with local soil properties contributing only a minor influence on shrub growth. Our conclusions strengthen predictions of changes to wildlife habitat and improve the representation of tundra vegetation dynamics in earth systems models in response to future arctic warming.

Modeling growth of three bakery product spoilage molds as a function of water activity, temperature and pH.

PubMed

Dagnas, Stéphane; Onno, Bernard; Membré, Jeanne-Marie

2014-09-01

The objective of this study was to quantify the effect of water activity, pH and storage temperature on the growth of Eurotium repens, Aspergillus niger and Penicillium corylophilum, isolated from spoiled bakery products. Moreover, the behaviors of these three mold species were compared to assess whether a general modeling framework may be set and re-used in future research on bakery spoilage molds. The mold growth was modeled by building two distinct Gamma-type secondary models: one on the lag time for growth and another one on the radial growth rate. A set of 428 experimental growth curves was generated. The effect of temperature (15-35 °C), water activity (0.80-0.98) and pH (3-7) was assessed. Results showed that it was not possible to apply the same set of secondary model equations to the three mold species given that the growth rate varied significantly with the factors pH and water activity. In contrast, the temperature effect on both growth rate and lag time of the three mold species was described by the same equation. The equation structure and model parameter values of the Gamma models were also compared per mold species to assess whether a relationship between lag time and growth rate existed. There was no correlation between the two growth responses for E. repens, but a slight one for A. niger and P. corylophilum. These findings will help in determining bakery product shelf-life and guiding future work in the predictive mycology field. Copyright © 2014 Elsevier B.V. All rights reserved.

State of the World 1984

NASA Astrophysics Data System (ADS)

Singer, S. Fred

Long before Ronald Reagan asked voters whether they were better off today than they were 4 years ago, many thoughtful people were asking whether the world as a whole was becoming a better place to live. The Malthusian point of view, restated by the Club of Rome's Limits to Growth, made an enormous impact on the world when it appeared in 1972. Its simplistic message, disguised in computer models, was that exponential growth cannot be maintained forever. Specifically, it predicted imminent exhaustion of food and natural resources and death from evergrowing pollution. Its successor volume, Global 2000, published with the encouragement of the Carter White House in 1980, was more restrained but also predicted general doom. It was responded to by The Resourceful Earth (sponsored by the Heritage Foundation), which views the future as rosy and contradicts Global 2000 on almost every point.

Bigger Data, Collaborative Tools and the Future of Predictive Drug Discovery

PubMed Central

Clark, Alex M.; Swamidass, S. Joshua; Litterman, Nadia; Williams, Antony J.

2014-01-01

Over the past decade we have seen a growth in the provision of chemistry data and cheminformatics tools as either free websites or software as a service (SaaS) commercial offerings. These have transformed how we find molecule-related data and use such tools in our research. There have also been efforts to improve collaboration between researchers either openly or through secure transactions using commercial tools. A major challenge in the future will be how such databases and software approaches handle larger amounts of data as it accumulates from high throughput screening and enables the user to draw insights, enable predictions and move projects forward. We now discuss how information from some drug discovery datasets can be made more accessible and how privacy of data should not overwhelm the desire to share it at an appropriate time with collaborators. We also discuss additional software tools that could be made available and provide our thoughts on the future of predictive drug discovery in this age of big data. We use some examples from our own research on neglected diseases, collaborations, mobile apps and algorithm development to illustrate these ideas. PMID:24943138

Predicting tree biomass growth in the temperate-boreal ecotone: is tree size, age, competition or climate response most important?

USGS Publications Warehouse

Foster, Jane R.; Finley, Andrew O.; D'Amato, Anthony W.; Bradford, John B.; Banerjee, Sudipto

2016-01-01

As global temperatures rise, variation in annual climate is also changing, with unknown consequences for forest biomes. Growing forests have the ability to capture atmospheric CO2and thereby slow rising CO2 concentrations. Forests’ ongoing ability to sequester C depends on how tree communities respond to changes in climate variation. Much of what we know about tree and forest response to climate variation comes from tree-ring records. Yet typical tree-ring datasets and models do not capture the diversity of climate responses that exist within and among trees and species. We address this issue using a model that estimates individual tree response to climate variables while accounting for variation in individuals’ size, age, competitive status, and spatially structured latent covariates. Our model allows for inference about variance within and among species. We quantify how variables influence aboveground biomass growth of individual trees from a representative sample of 15 northern or southern tree species growing in a transition zone between boreal and temperate biomes. Individual trees varied in their growth response to fluctuating mean annual temperature and summer moisture stress. The variation among individuals within a species was wider than mean differences among species. The effects of mean temperature and summer moisture stress interacted, such that warm years produced positive responses to summer moisture availability and cool years produced negative responses. As climate models project significant increases in annual temperatures, growth of species likeAcer saccharum, Quercus rubra, and Picea glauca will vary more in response to summer moisture stress than in the past. The magnitude of biomass growth variation in response to annual climate was 92–95% smaller than responses to tree size and age. This means that measuring or predicting the physical structure of current and future forests could tell us more about future C dynamics than growth responses related to climate change alone.

Predicting tree biomass growth in the temperate-boreal ecotone: Is tree size, age, competition, or climate response most important?

PubMed

Foster, Jane R; Finley, Andrew O; D'Amato, Anthony W; Bradford, John B; Banerjee, Sudipto

2016-06-01

As global temperatures rise, variation in annual climate is also changing, with unknown consequences for forest biomes. Growing forests have the ability to capture atmospheric CO2 and thereby slow rising CO2 concentrations. Forests' ongoing ability to sequester C depends on how tree communities respond to changes in climate variation. Much of what we know about tree and forest response to climate variation comes from tree-ring records. Yet typical tree-ring datasets and models do not capture the diversity of climate responses that exist within and among trees and species. We address this issue using a model that estimates individual tree response to climate variables while accounting for variation in individuals' size, age, competitive status, and spatially structured latent covariates. Our model allows for inference about variance within and among species. We quantify how variables influence aboveground biomass growth of individual trees from a representative sample of 15 northern or southern tree species growing in a transition zone between boreal and temperate biomes. Individual trees varied in their growth response to fluctuating mean annual temperature and summer moisture stress. The variation among individuals within a species was wider than mean differences among species. The effects of mean temperature and summer moisture stress interacted, such that warm years produced positive responses to summer moisture availability and cool years produced negative responses. As climate models project significant increases in annual temperatures, growth of species like Acer saccharum, Quercus rubra, and Picea glauca will vary more in response to summer moisture stress than in the past. The magnitude of biomass growth variation in response to annual climate was 92-95% smaller than responses to tree size and age. This means that measuring or predicting the physical structure of current and future forests could tell us more about future C dynamics than growth responses related to climate change alone. © 2015 John Wiley & Sons Ltd.

Predicting impacts of future human population growth and development on occupancy rates of forest-dependent birds

USGS Publications Warehouse

Brown, Michelle L.; Donovan, Therese; Schwenk, W. Scott; Theobald, David M.

2014-01-01

Forest loss and fragmentation are among the largest threats to forest-dwelling wildlife species today, and projected increases in human population growth are expected to increase these threats in the next century. We combined spatially-explicit growth models with wildlife distribution models to predict the effects of human development on 5 forest-dependent bird species in Vermont, New Hampshire, and Massachusetts, USA. We used single-species occupancy models to derive the probability of occupancy for each species across the study area in the years 2000 and 2050. Over half a million new housing units were predicted to be added to the landscape. The maximum change in housing density was nearly 30 houses per hectare; however, 30% of the towns in the study area were projected to add less than 1 housing unit per hectare. In the face of predicted human growth, the overall occupancy of each species decreased by as much as 38% (ranging from 19% to 38% declines in the worst-case scenario) in the year 2050. These declines were greater outside of protected areas than within protected lands. Ninety-seven percent of towns experienced some decline in species occupancy within their borders, highlighting the value of spatially-explicit models. The mean decrease in occupancy probability within towns ranged from 3% for hairy woodpecker to 8% for ovenbird and hermit thrush. Reductions in occupancy probability occurred on the perimeters of cities and towns where exurban development is predicted to increase in the study area. This spatial approach to wildlife planning provides data to evaluate trade-offs between development scenarios and forest-dependent wildlife species.

Multimodality Tumor Delineation and Predictive Modelling via Fuzzy-Fusion Deformable Models and Biological Potential Functions

NASA Astrophysics Data System (ADS)

Wasserman, Richard Marc

The radiation therapy treatment planning (RTTP) process may be subdivided into three planning stages: gross tumor delineation, clinical target delineation, and modality dependent target definition. The research presented will focus on the first two planning tasks. A gross tumor target delineation methodology is proposed which focuses on the integration of MRI, CT, and PET imaging data towards the generation of a mathematically optimal tumor boundary. The solution to this problem is formulated within a framework integrating concepts from the fields of deformable modelling, region growing, fuzzy logic, and data fusion. The resulting fuzzy fusion algorithm can integrate both edge and region information from multiple medical modalities to delineate optimal regions of pathological tissue content. The subclinical boundaries of an infiltrating neoplasm cannot be determined explicitly via traditional imaging methods and are often defined to extend a fixed distance from the gross tumor boundary. In order to improve the clinical target definition process an estimation technique is proposed via which tumor growth may be modelled and subclinical growth predicted. An in vivo, macroscopic primary brain tumor growth model is presented, which may be fit to each patient undergoing treatment, allowing for the prediction of future growth and consequently the ability to estimate subclinical local invasion. Additionally, the patient specific in vivo tumor model will be of significant utility in multiple diagnostic clinical applications.

Plasticity in habitat use determines metabolic response of fish to global warming in stratified lakes.

PubMed

Busch, Susan; Kirillin, Georgiy; Mehner, Thomas

2012-09-01

We used a coupled lake physics and bioenergetics-based foraging model to evaluate how the plasticity in habitat use modifies the seasonal metabolic response of two sympatric cold-water fishes (vendace and Fontane cisco, Coregonus spp.) under a global warming scenario for the year 2100. In different simulations, the vertically migrating species performed either a plastic strategy (behavioral thermoregulation) by shifting their population depth at night to maintain the temperatures occupied at current in-situ observations, or a fixed strategy (no thermoregulation) by keeping their occupied depths at night but facing modified temperatures. The lake physics model predicted higher temperatures above 20 m and lower temperatures below 20 m in response to warming. Using temperature-zooplankton relationships, the density of zooplankton prey was predicted to increase at the surface, but to decrease in hypolimnetic waters. Simulating the fixed strategy, growth was enhanced only for the deeper-living cisco due to the shift in thermal regime at about 20 m. In contrast, simulating the plastic strategy, individual growth of cisco and young vendace was predicted to increase compared to growth currently observed in the lake. Only growth rates of older vendace are reduced under future global warming scenarios irrespective of the behavioral strategy. However, performing behavioral thermoregulation would drive both species into the same depth layers, and hence will erode vertical microhabitat segregation and intensify inter-specific competition between the coexisting coregonids.

Analysis of optimality in natural and perturbed metabolic networks

PubMed Central

Segrè, Daniel; Vitkup, Dennis; Church, George M.

2002-01-01

An important goal of whole-cell computational modeling is to integrate detailed biochemical information with biological intuition to produce testable predictions. Based on the premise that prokaryotes such as Escherichia coli have maximized their growth performance along evolution, flux balance analysis (FBA) predicts metabolic flux distributions at steady state by using linear programming. Corroborating earlier results, we show that recent intracellular flux data for wild-type E. coli JM101 display excellent agreement with FBA predictions. Although the assumption of optimality for a wild-type bacterium is justifiable, the same argument may not be valid for genetically engineered knockouts or other bacterial strains that were not exposed to long-term evolutionary pressure. We address this point by introducing the method of minimization of metabolic adjustment (MOMA), whereby we test the hypothesis that knockout metabolic fluxes undergo a minimal redistribution with respect to the flux configuration of the wild type. MOMA employs quadratic programming to identify a point in flux space, which is closest to the wild-type point, compatibly with the gene deletion constraint. Comparing MOMA and FBA predictions to experimental flux data for E. coli pyruvate kinase mutant PB25, we find that MOMA displays a significantly higher correlation than FBA. Our method is further supported by experimental data for E. coli knockout growth rates. It can therefore be used for predicting the behavior of perturbed metabolic networks, whose growth performance is in general suboptimal. MOMA and its possible future extensions may be useful in understanding the evolutionary optimization of metabolism. PMID:12415116

Climate-diameter growth relationships of black spruce and jack pine trees in boreal Ontario, Canada.

PubMed

Subedi, Nirmal; Sharma, Mahadev

2013-02-01

To predict the long-term effects of climate change - global warming and changes in precipitation - on the diameter (radial) growth of jack pine (Pinus banksiana Lamb.) and black spruce (Picea mariana [Mill.] B.S.P.) trees in boreal Ontario, we modified an existing diameter growth model to include climate variables. Diameter chronologies of 927 jack pine and 1173 black spruce trees, growing in the area from 47°N to 50°N and 80°W to 92°W, were used to develop diameter growth models in a nonlinear mixed-effects approach. Our results showed that the variables long-term average of mean growing season temperature, precipitation during wettest quarter, and total precipitation during growing season were significant (alpha = 0.05) in explaining variation in diameter growth of the sample trees. Model results indicated that higher temperatures during the growing season would increase the diameter growth of jack pine trees, but decrease that of black spruce trees. More precipitation during the wettest quarter would favor the diameter growth of both species. On the other hand, a wetter growing season, which may decrease radiation inputs, increase nutrient leaching, and reduce the decomposition rate, would reduce the diameter growth of both species. Moreover, our results indicated that future (2041-2070) diameter growth rate may differ from current (1971-2000) growth rates for both species, with conditions being more favorable for jack pine than black spruce trees. Expected future changes in the growth rate of boreal trees need to be considered in forest management decisions. We recommend that knowledge of climate-growth relationships, as represented by models, be combined with learning from adaptive management to reduce the risks and uncertainties associated with forest management decisions. © 2012 Blackwell Publishing Ltd.

Pan-Tropical Analysis of Climate Effects on Seasonal Tree Growth

PubMed Central

Wagner, Fabien; Rossi, Vivien; Aubry-Kientz, Mélaine; Bonal, Damien; Dalitz, Helmut; Gliniars, Robert; Stahl, Clément; Trabucco, Antonio; Hérault, Bruno

2014-01-01

Climate models predict a range of changes in tropical forest regions, including increased average temperatures, decreased total precipitation, reduced soil moisture and alterations in seasonal climate variations. These changes are directly related to the increase in anthropogenic greenhouse gas concentrations, primarily CO2. Assessing seasonal forest growth responses to climate is of utmost importance because woody tissues, produced by photosynthesis from atmospheric CO2, water and light, constitute the main component of carbon sequestration in the forest ecosystem. In this paper, we combine intra-annual tree growth measurements from published tree growth data and the corresponding monthly climate data for 25 pan-tropical forest sites. This meta-analysis is designed to find the shared climate drivers of tree growth and their relative importance across pan-tropical forests in order to improve carbon uptake models in a global change context. Tree growth reveals significant intra-annual seasonality at seasonally dry sites or in wet tropical forests. Of the overall variation in tree growth, 28.7% was explained by the site effect, i.e. the tree growth average per site. The best predictive model included four climate variables: precipitation, solar radiation (estimated with extrasolar radiation reaching the atmosphere), temperature amplitude and relative soil water content. This model explained more than 50% of the tree growth variations across tropical forests. Precipitation and solar radiation are the main seasonal drivers of tree growth, causing 19.8% and 16.3% of the tree growth variations. Both have a significant positive association with tree growth. These findings suggest that forest productivity due to tropical tree growth will be reduced in the future if climate extremes, such as droughts, become more frequent. PMID:24670981

Pan-tropical analysis of climate effects on seasonal tree growth.

PubMed

Wagner, Fabien; Rossi, Vivien; Aubry-Kientz, Mélaine; Bonal, Damien; Dalitz, Helmut; Gliniars, Robert; Stahl, Clément; Trabucco, Antonio; Hérault, Bruno

2014-01-01

Climate models predict a range of changes in tropical forest regions, including increased average temperatures, decreased total precipitation, reduced soil moisture and alterations in seasonal climate variations. These changes are directly related to the increase in anthropogenic greenhouse gas concentrations, primarily CO2. Assessing seasonal forest growth responses to climate is of utmost importance because woody tissues, produced by photosynthesis from atmospheric CO2, water and light, constitute the main component of carbon sequestration in the forest ecosystem. In this paper, we combine intra-annual tree growth measurements from published tree growth data and the corresponding monthly climate data for 25 pan-tropical forest sites. This meta-analysis is designed to find the shared climate drivers of tree growth and their relative importance across pan-tropical forests in order to improve carbon uptake models in a global change context. Tree growth reveals significant intra-annual seasonality at seasonally dry sites or in wet tropical forests. Of the overall variation in tree growth, 28.7% was explained by the site effect, i.e. the tree growth average per site. The best predictive model included four climate variables: precipitation, solar radiation (estimated with extrasolar radiation reaching the atmosphere), temperature amplitude and relative soil water content. This model explained more than 50% of the tree growth variations across tropical forests. Precipitation and solar radiation are the main seasonal drivers of tree growth, causing 19.8% and 16.3% of the tree growth variations. Both have a significant positive association with tree growth. These findings suggest that forest productivity due to tropical tree growth will be reduced in the future if climate extremes, such as droughts, become more frequent.

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.

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.

A Synthesis Of Cosmic X-ray And Infrared Background

NASA Astrophysics Data System (ADS)

Shi, Yong; Helou, G.; Armus, L.; Stierwalt, S.

2012-01-01

We present a synthesis model of cosmic IR and X-ray background, with the goal to derive a complete census of cosmic evolution of star formation (SF) and black-hole (BH) growth by complementing advantages of X-ray and IR surveys to each other. By assuming that individual galaxies are experiencing both SF and BH accretion, our model decomposes the total IR LF into SF and BH components while taking into account the luminosity-dependent SED and its dispersion of the SF component, and the extinction-dependent SED of the BH component. The best-fit parameters are derived by fitting to the number counts and redshift distributions at X-ray including both hard and soft bands, and mid-IR to submm bands including IRAS, Spitzer, Herschel, SCUBA, Aztec and MAMBO. Based on the fit result, our models provide a series of predictions on galaxy evolution and black-hole growth. For evolution of infrared galaxies, the model predicts that the total infrared luminosity function is best described through evolution in both luminosity and density. For evolution of AGN populations, the model predicts that the evolution of X-ray LF also shows luminosity and density dependent, that the type-1/type-2 AGN fraction is a function of both luminosity and redshift, and that the Compton-thick AGN number density evolves strongly with redshift, contributing about 20% to the total cosmic BH growth. For BH growth in IR galaxies, the model predicts that the majority of BH growth at z>1 occurs in infrared luminous galaxies and the AGN fraction as a function of IR survey is a strong function of the survey depth, ranging from >50% at bright end to below 10% at faint end. We also evaluates various AGN selection techniques at X-ray and IR wavelengths and offer predictions for future missions at X-ray and IR.

Innovation network

PubMed Central

Acemoglu, Daron; Akcigit, Ufuk; Kerr, William R.

2016-01-01

Technological progress builds upon itself, with the expansion of invention in one domain propelling future work in linked fields. Our analysis uses 1.8 million US patents and their citation properties to map the innovation network and its strength. Past innovation network structures are calculated using citation patterns across technology classes during 1975–1994. The interaction of this preexisting network structure with patent growth in upstream technology fields has strong predictive power on future innovation after 1995. This pattern is consistent with the idea that when there is more past upstream innovation for a particular technology class to build on, then that technology class innovates more. PMID:27681628

Early biometric lag in the prediction of small for gestational age neonates and preeclampsia.

PubMed

Schwartz, Nadav; Pessel, Cara; Coletta, Jaclyn; Krieger, Abba M; Timor-Tritsch, Ilan E

2011-01-01

An early fetal growth lag may be a marker of future complications. We sought to determine the utility of early biometric variables in predicting adverse pregnancy outcomes. In this retrospective cohort study, the crown-rump length at 11 to 14 weeks and the head circumference, biparietal diameter, abdominal circumference, femur length, humerus length, transverse cerebellar diameter, and estimated fetal weight at 18 to 24 weeks were converted to an estimated gestational age using published regression formulas. Sonographic fetal growth (difference between each biometric gestational age and the crown-rump length gestational age) minus expected fetal growth (number of days elapsed between the two scans) yielded the biometric growth lag. These lags were tested as predictors of small for gestational age (SGA) neonates (≤10th percentile) and preeclampsia. A total of 245 patients were included. Thirty-two (13.1%) delivered an SGA neonate, and 43 (17.6%) had the composite outcome. The head circumference, biparietal diameter, abdominal circumference, and estimated fetal weight lags were identified as significant predictors of SGA neonates after adjusted analyses (P < .05). The addition of either the estimated fetal weight or abdominal circumference lag to maternal characteristics alone significantly improved the performance of the predictive model, achieving areas under the curve of 0.72 and 0.74, respectively. No significant association was found between the biometric lag variables and the development of preeclampsia. Routinely available biometric data can be used to improve the prediction of adverse outcomes such as SGA. These biometric lags should be considered in efforts to develop screening algorithms for adverse outcomes.

Invasive plants and their ecological strategies: Prediction and explanation of woody plant invasion in New England

USGS Publications Warehouse

Herron, P.M.; Martine, C.T.; Latimer, A.M.; Leicht-Young, S. A.

2007-01-01

Effective management of introduced species requires the early identification of species that pose a significant threat of becoming invasive. To better understand the invasive ecology of species in New England, USA, we compiled a character data set with which to compare non-native species that are known invaders to non-native species that are not currently known to be invasive. In contrast to previous biological trait-based models, we employed a Bayesian hierarchical analysis to identify sets of plant traits associated with invasiveness for each of three growth forms (vines, shrubs, and trees). The resulting models identify a suite of 'invasive traits' highlighting the ecology associated with invasiveness for each of three growth forms. The most effective predictors of invasiveness that emerged from our model were 'invasive elsewhere', 'fast growth rate', 'native latitudinal range', and 'growth form'. The contrast among growth forms was pronounced. For example, 'wind dispersal' was positively correlated with invasiveness in trees, but negatively correlated in shrubs and vines. The predictive model was able to correctly classify invasive plants 67% of the time (22/33), and non-invasive plants 95% of the time (204/215). A number of potential future invasive species in New England that deserve management consideration were identified. ?? 2007 The Authors.

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.

Assessment for fuel consumption and exhaust emissions of China's vehicles: future trends and policy implications.

PubMed

Wu, Yingying; Zhao, Peng; Zhang, Hongwei; Wang, Yuan; Mao, Guozhu

2012-01-01

In the recent years, China's auto industry develops rapidly, thus bringing a series of burdens to society and environment. This paper uses Logistic model to simulate the future trend of China's vehicle population and finds that China's auto industry would come into high speed development time during 2020-2050. Moreover, this paper predicts vehicles' fuel consumption and exhaust emissions (CO, HC, NO(x), and PM) and quantificationally evaluates related industry policies. It can be concluded that (1) by 2020, China should develop at least 47 million medium/heavy hybrid cars to prevent the growth of vehicle fuel consumption; (2) China should take the more stringent vehicle emission standard V over 2017-2021 to hold back the growth of exhaust emissions; (3) developing new energy vehicles is the most effective measure to ease the pressure brought by auto industry.

Assessment for Fuel Consumption and Exhaust Emissions of China's Vehicles: Future Trends and Policy Implications

PubMed Central

Zhao, Peng; Zhang, Hongwei; Wang, Yuan; Mao, Guozhu

2012-01-01

In the recent years, China's auto industry develops rapidly, thus bringing a series of burdens to society and environment. This paper uses Logistic model to simulate the future trend of China's vehicle population and finds that China's auto industry would come into high speed development time during 2020–2050. Moreover, this paper predicts vehicles' fuel consumption and exhaust emissions (CO, HC, NOx, and PM) and quantificationally evaluates related industry policies. It can be concluded that (1) by 2020, China should develop at least 47 million medium/heavy hybrid cars to prevent the growth of vehicle fuel consumption; (2) China should take the more stringent vehicle emission standard V over 2017–2021 to hold back the growth of exhaust emissions; (3) developing new energy vehicles is the most effective measure to ease the pressure brought by auto industry. PMID:23365524

Darcy's law predicts widespread forest mortalityunder climate warming

NASA Astrophysics Data System (ADS)

Allen, C. D.; McDowell, N. G.

2015-12-01

Drought and heat-induced tree mortality is accelerating in many forest biomes as a consequence of a warming climate, resulting in a threat to global forests unlike any in recorded history. Forests store the majority of terrestrial carbon, thus their loss may have significant and sustained impacts on the global carbon cycle. We used a hydraulic corollary to Darcy's law, a core principle of vascular plant physiology, to predict characteristics of plants that will survive and die during drought under warmer future climates. Plants that are tall with isohydric stomatal regulation, low hydraulic conductance, and high leaf area are most likely to die from future drought stress. Thus, tall trees of old-growth forests are at the greatest risk of loss, which has ominous implications for terrestrial carbon storage. This application of Darcy's law indicates today's forests generally should be replaced by shorter and more xeric plants, owing to future warmer droughts and associated wildfires and pest attacks. The Darcy's corollary also provides a simple, robust framework for informing forest management interventions needed to promote the survival of current forests. There are assumptions and omissions in this theoretical prediction, as well as new evidence supporting its predictions, both of which I will review. Given the robustness of Darcy's law for predictions of vascular plant function, we conclude with high certainty that today's forests are going to be subject to continued increases in mortality rates that will result in substantial reorganization of their structure and carbon storage.

Growth response and acclimation of CO2 exchange characteristics to elevated temperatures in tropical tree seedlings.

PubMed

Cheesman, Alexander W; Winter, Klaus

2013-09-01

Predictions of how tropical forests will respond to future climate change are constrained by the paucity of data on the performance of tropical species under elevated growth temperatures. In particular, little is known about the potential of tropical species to acclimate physiologically to future increases in temperature. Seedlings of 10 neo-tropical tree species from different functional groups were cultivated in controlled-environment chambers under four day/night temperature regimes between 30/22 °C and 39/31 °C. Under well-watered conditions, all species showed optimal growth at temperatures above those currently found in their native range. While non-pioneer species experienced catastrophic failure or a substantially reduced growth rate under the highest temperature regime employed (i.e. daily average of 35 °C), growth in three lowland pioneers showed only a marginal reduction. In a subsequent experiment, three species (Ficus insipida, Ormosia macrocalyx, and Ochroma pyramidale) were cultivated at two temperatures determined as sub- and superoptimal for growth, but which resulted in similar biomass accumulation despite a 6°C difference in growth temperature. Through reciprocal transfer and temperature adjustment, the role of thermal acclimation in photosynthesis and respiration was investigated. Acclimation potential varied among species, with two distinct patterns of respiration acclimation identified. The study highlights the role of both inherent temperature tolerance and thermal acclimation in determining the ability of tropical tree species to cope with enhanced temperatures.

Future Energy: The Use of Hydrogen May Be Inevitable

ERIC Educational Resources Information Center

Bockris, John O'M.

2006-01-01

The predictions by the Department of Energy indicate the maximum of the rate of supply of oil will be reached around 2021, but this neglects the effect of the rapid growth of China and India. It will be necessary to use coal, natural gas, nuclear power, or renewables to supplement, and, after 2021, to replace oil. If coal is used, it can be…

Application of a Hybrid Forest Growth Model to Evaluate Climate Change Impacts on Productivity, Nutrient Cycling and Mortality in a Montane Forest Ecosystem.

PubMed

Seely, Brad; Welham, Clive; Scoullar, Kim

2015-01-01

Climate change introduces considerable uncertainty in forest management planning and outcomes, potentially undermining efforts at achieving sustainable practices. Here, we describe the development and application of the FORECAST Climate model. Constructed using a hybrid simulation approach, the model includes an explicit representation of the effect of temperature and moisture availability on tree growth and survival, litter decomposition, and nutrient cycling. The model also includes a representation of the impact of increasing atmospheric CO2 on water use efficiency, but no direct CO2 fertilization effect. FORECAST Climate was evaluated for its ability to reproduce the effects of historical climate on Douglas-fir and lodgepole pine growth in a montane forest in southern British Columbia, Canada, as measured using tree ring analysis. The model was subsequently used to project the long-term impacts of alternative future climate change scenarios on forest productivity in young and established stands. There was a close association between predicted sapwood production and measured tree ring chronologies, providing confidence that model is able to predict the relative impact of annual climate variability on tree productivity. Simulations of future climate change suggest a modest increase in productivity in young stands of both species related to an increase in growing season length. In contrast, results showed a negative impact on stemwood biomass production (particularly in the case of lodgepole pine) for established stands due to increased moisture stress mortality.

Application of a Hybrid Forest Growth Model to Evaluate Climate Change Impacts on Productivity, Nutrient Cycling and Mortality in a Montane Forest Ecosystem

PubMed Central

Seely, Brad; Welham, Clive; Scoullar, Kim

2015-01-01

Climate change introduces considerable uncertainty in forest management planning and outcomes, potentially undermining efforts at achieving sustainable practices. Here, we describe the development and application of the FORECAST Climate model. Constructed using a hybrid simulation approach, the model includes an explicit representation of the effect of temperature and moisture availability on tree growth and survival, litter decomposition, and nutrient cycling. The model also includes a representation of the impact of increasing atmospheric CO2 on water use efficiency, but no direct CO2 fertilization effect. FORECAST Climate was evaluated for its ability to reproduce the effects of historical climate on Douglas-fir and lodgepole pine growth in a montane forest in southern British Columbia, Canada, as measured using tree ring analysis. The model was subsequently used to project the long-term impacts of alternative future climate change scenarios on forest productivity in young and established stands. There was a close association between predicted sapwood production and measured tree ring chronologies, providing confidence that model is able to predict the relative impact of annual climate variability on tree productivity. Simulations of future climate change suggest a modest increase in productivity in young stands of both species related to an increase in growing season length. In contrast, results showed a negative impact on stemwood biomass production (particularly in the case of lodgepole pine) for established stands due to increased moisture stress mortality. PMID:26267446

Factors influencing hypertrophy of the left lateral liver lobe after portal vein embolization.

PubMed

Malinowski, Maciej; Stary, Victoria; Lock, Johan F; Schulz, Antje; Jara, Maximilian; Seehofer, Daniel; Gebauer, Bernhard; Denecke, Timm; Geisel, Dominik; Neuhaus, Peter; Stockmann, Martin

2015-02-01

Portal vein embolization (PVE) before extended right hepatectomy leads to an increase of the future liver remnant (FLR) volume, but predictive factors for sufficient hypertrophy are still unclear. The purpose of this study was to investigate parameters influencing the growth of FLR. Patients undergoing PVE prior hepatic resection were evaluated. PVE was done using polyvinyl alcohol particles only. Volumetric analysis was performed before embolization and before hepatectomy. Success of PVE was determined as percental growth of the future liver remnant. Seventy-seven patients were included, and three cohorts were formed according to the hypertrophy of FLR. FLR increased from 448.2 ± 187 to 475.5 ± 191 in the poor, from 315.3 ± 86 to 469.1 ± 142 in the moderate, and from 283.4 ± 68 to 400.4 ± 110 in the good hypertrophy group. More cases of recanalization of the portal vein were observed in patients with poor hypertrophy (p = 0.016). Small FLR before PVE predict higher growth of the FLR (p = 0.006). Duration between PVE and surgery differed significantly: 22 (poor) vs. 32 (good) days (p = 0.040). No recanalization, small initial FLR and longer time were assessed with better FLR hypertrophy. More sufficient PVE techniques and postponed hepatectomy might improve the outcome. Small initial FLR should not be a disclosure for curative hepatectomy.

Revisiting the Estimation of Dinosaur Growth Rates

PubMed Central

Myhrvold, Nathan P.

2013-01-01

Previous growth-rate studies covering 14 dinosaur taxa, as represented by 31 data sets, are critically examined and reanalyzed by using improved statistical techniques. The examination reveals that some previously reported results cannot be replicated by using the methods originally reported; results from new methods are in many cases different, in both the quantitative rates and the qualitative nature of the growth, from results in the prior literature. Asymptotic growth curves, which have been hypothesized to be ubiquitous, are shown to provide best fits for only four of the 14 taxa. Possible reasons for non-asymptotic growth patterns are discussed; they include systematic errors in the age-estimation process and, more likely, a bias toward younger ages among the specimens analyzed. Analysis of the data sets finds that only three taxa include specimens that could be considered skeletally mature (i.e., having attained 90% of maximum body size predicted by asymptotic curve fits), and eleven taxa are quite immature, with the largest specimen having attained less than 62% of predicted asymptotic size. The three taxa that include skeletally mature specimens are included in the four taxa that are best fit by asymptotic curves. The totality of results presented here suggests that previous estimates of both maximum dinosaur growth rates and maximum dinosaur sizes have little statistical support. Suggestions for future research are presented. PMID:24358133

A coupled model approach to reduce nonpoint-source pollution resulting from predicted urban growth: A case study in the Ambos Nogales watershed

USGS Publications Warehouse

Norman, L.M.; Guertin, D.P.; Feller, M.

2008-01-01

The development of new approaches for understanding processes of urban development and their environmental effects, as well as strategies for sustainable management, is essential in expanding metropolitan areas. This study illustrates the potential of linking urban growth and watershed models to identify problem areas and support long-term watershed planning. Sediment is a primary source of nonpoint-source pollution in surface waters. In urban areas, sediment is intermingled with other surface debris in transport. In an effort to forecast the effects of development on surface-water quality, changes predicted in urban areas by the SLEUTH urban growth model were applied in the context of erosion-sedimentation models (Universal Soil Loss Equation and Spatially Explicit Delivery Models). The models are used to simulate the effect of excluding hot-spot areas of erosion and sedimentation from future urban growth and to predict the impacts of alternative erosion-control scenarios. Ambos Nogales, meaning 'both Nogaleses,' is a name commonly used for the twin border cities of Nogales, Arizona and Nogales, Sonora, Mexico. The Ambos Nogales watershed has experienced a decrease in water quality as a result of urban development in the twin-city area. Population growth rates in Ambos Nogales are high and the resources set in place to accommodate the rapid population influx will soon become overburdened. Because of its remote location and binational governance, monitoring and planning across the border is compromised. One scenario described in this research portrays an improvement in water quality through the identification of high-risk areas using models that simulate their protection from development and replanting with native grasses, while permitting the predicted and inevitable growth elsewhere. This is meant to add to the body of knowledge about forecasting the impact potential of urbanization on sediment delivery to streams for sustainable development, which can be accomplished in a virtual environment. Copyright ?? 2008 by Bellwether Publishing, Ltd. All rights reserved.

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.

The Future of Geomagnetic Storm Predictions: Implications from Recent Solar and Interplanetary Observations

NASA Technical Reports Server (NTRS)

Tsurutani, B. T.; Gonzalez, W. D.

1995-01-01

Within the last 7-8 years, there has been a substantial growth in out knowledge of the solar and interplanetary causes of geomagnetic storms at Earth. This review article will not attempt to cover all of the work done during this period. This can be found elsewhere. Our emphasis here will be on recent efforts that expose important, presently unanswered questions that must be addressed and solved before true predictability of storms can be possible. Hopefully, this article will encourage some readers to join this effort and perhaps make major contributions to the field.

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

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.

Integrated PK-PD and agent-based modeling in oncology.

PubMed

Wang, Zhihui; Butner, Joseph D; Cristini, Vittorio; Deisboeck, Thomas S

2015-04-01

Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed.

Integrated PK-PD and Agent-Based Modeling in Oncology

PubMed Central

Wang, Zhihui; Butner, Joseph D.; Cristini, Vittorio

2016-01-01

Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed. PMID:25588379

Early mathematical competencies and later achievement: insights from the Longitudinal Study of Australian Children

NASA Astrophysics Data System (ADS)

MacDonald, Amy; Carmichael, Colin

2017-11-01

International research suggests that early mathematical competence predicts later mathematical achievement. In this article, we explore the relationship between mathematical competencies at 4-5 years, as measured by teacher ratings, and later results on Years 3, 5, 7 and 9 National Assessment Program - Literacy and Numeracy (NAPLAN) numeracy tests. Data from a nationally representative sample of 2343 children participating in the Longitudinal Study of Australian Children (LSAC) are examined. In line with international studies, we report moderate correlations between preschool-entry mathematics and later NAPLAN numeracy test results. However, analysis of individual growth trajectories indicates that early mathematics predicts the initial (Year 3) level, but not subsequent growth. This suggests that early mathematical competencies are important for enhancing achievement in early schooling, but that the quality of mathematics education provided in the schooling years is critical for future development.

Longitudinal prediction of language emergence in infants at high and low risk for autism spectrum disorder.

PubMed

Edmunds, Sarah R; Ibañez, Lisa V; Warren, Zachary; Messinger, Daniel S; Stone, Wendy L

2017-02-01

This study used a prospective longitudinal design to examine the early developmental pathways that underlie language growth in infants at high risk (n = 50) and low risk (n = 34) for autism spectrum disorder in the first 18 months of life. While motor imitation and responding to joint attention (RJA) have both been found to predict expressive language in children with autism spectrum disorder and those with typical development, the longitudinal relation between these capacities has not yet been identified. As hypothesized, results revealed that 15-month RJA mediated the association between 12-month motor imitation and 18-month expressive vocabulary, even after controlling for earlier levels of RJA and vocabulary. These results provide new information about the developmental sequencing of skills relevant to language growth that may inform future intervention efforts for children at risk for language delay or other developmental challenges.

pCO2 effects on species composition and growth of an estuarine phytoplankton community

NASA Astrophysics Data System (ADS)

Grear, Jason S.; Rynearson, Tatiana A.; Montalbano, Amanda L.; Govenar, Breea; Menden-Deuer, Susanne

2017-05-01

The effects of ongoing changes in ocean carbonate chemistry on plankton ecology have important implications for food webs and biogeochemical cycling. However, conflicting results have emerged regarding species-specific responses to pCO2 enrichment and thus community responses have been difficult to predict. To assess community level effects (e.g., production) of altered carbonate chemistry, studies are needed that capitalize on the benefits of controlled experiments but also retain features of intact ecosystems that may exacerbate or ameliorate the effects observed in single-species or single cohort experiments. We performed incubations of natural plankton communities from Narragansett Bay, RI, USA in winter at ambient bay temperatures (5-13 °C), light and nutrient concentrations. Three levels of controlled and constant CO2 concentrations were imposed, simulating past, present and future conditions at mean pCO2 levels of 224, 361, and 724 μatm respectively. Samples for carbonate analysis, chlorophyll a, plankton size-abundance, and plankton species composition were collected daily and phytoplankton growth rates in three different size fractions (<5, 5-20, and >20 μm) were measured at the end of the 7-day incubation period. Community composition changed during the incubation period with major increases in relative diatom abundance, which were similar across pCO2 treatments. At the end of the experiment, 24-hr growth responses to pCO2 levels varied as a function of cell size. The smallest size fraction (<5 μm) grew faster at the elevated pCO2 level. In contrast, the 5-20 μm size fraction grew fastest in the Present treatment and there were no significant differences in growth rate among treatments in the >20 μm size fraction. Cell size distribution shifted toward smaller cells in both the Past and Future treatments but remained unchanged in the Present treatment. Similarity in Past and Future treatments for cell size distribution and growth rate (5-20 μm size fraction) illustrate non-monotonic effects of altered pCO2 on ecological indicators and may be related to opposing physiological effects of high CO2 and low pH both within and among species. Interaction of these effects with other factors (e.g., nutrients, light, temperature, grazing, initial species composition) may explain variability among published studies. The absence of clear treatment-specific effects at the community level suggests that extrapolation of species-specific responses or experiments with only present day and future pCO2 treatments levels could produce misleading predictions of ocean acidification impacts on plankton production.

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.

Modeling the Effects of Climate Change on Whitebark Pine Along the Pacific Crest Trail

NASA Astrophysics Data System (ADS)

Anderson, R. S.; Nguyen, A.; Gill, N.; Kannan, S.; Patadia, N.; Meyer, M.; Schmidt, C.

2012-12-01

The Pacific Crest Trail (PCT), one of eight National Scenic Trails, stretches 2,650 miles from Mexico to the Canadian border. At high elevations along this trail, within Inyo and Sierra National Forests, populations of whitebark pine (Pinus albicaulis) have been diminishing due to infestation of the mountain pine beetle (Dendroctonus ponderosae) and are threatened due to a changing climate. Understanding the current and future condition of whitebark pine is a primary goal of forest managers due to its high ecological and economic importance, and it is currently a candidate for protection under the Endangered Species Act (ESA). Using satellite imagery, we analyzed the rate and spatial extent of whitebark pine tree mortality from 1984 to 2011 using the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) program. Climate data, soil properties, and biological features of the whitebark pine were incorporated in the Physiological Principles to Predict Growth (3-PG) model to predict future rates of growth and assess its applicability in modeling natural whitebark pine processes. Finally, the Random Forest algorithm was used with topographic data alongside recent and future climate data from the IPCC A2 and B1 climate scenarios for the years 2030, 2060, and 2090 to model the future distribution of whitebark pine. LandTrendr results indicate beetle related mortality covering 14,940 km2 of forest, 2,880 km2 of which are within whitebark pine forest. By 2090, our results show that under the A2 climate scenario, whitebark pine suitable habitat may be reduced by as much as 99.97% by the year 2090 within our study area. Under the B1 climate scenario, which has decreased CO2 emissions, 13.54% more habitat would be preserved in 2090.

Fatigue Life Prediction Based on Crack Closure and Equivalent Initial Flaw Size

PubMed Central

Wang, Qiang; Zhang, Wei; Jiang, Shan

2015-01-01

Failure analysis and fatigue life prediction are necessary and critical for engineering structural materials. In this paper, a general methodology is proposed to predict fatigue life of smooth and circular-hole specimens, in which the crack closure model and equivalent initial flaw size (EIFS) concept are employed. Different effects of crack closure on small crack growth region and long crack growth region are considered in the proposed method. The EIFS is determined by the fatigue limit and fatigue threshold stress intensity factor △Kth. Fatigue limit is directly obtained from experimental data, and △Kth is calculated by using a back-extrapolation method. Experimental data for smooth and circular-hole specimens in three different alloys (Al2024-T3, Al7075-T6 and Ti-6Al-4V) under multiple stress ratios are used to validate the method. In the validation section, Semi-circular surface crack and quarter-circular corner crack are assumed to be the initial crack shapes for the smooth and circular-hole specimens, respectively. A good agreement is observed between model predictions and experimental data. The detailed analysis and discussion are performed on the proposed model. Some conclusions and future work are given. PMID:28793625

Thermal Conductivity Prediction of Soil in Complex Plant Soil System using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Wardani, A. K.; Purqon, A.

2016-08-01

Thermal conductivity is one of thermal properties of soil in seed germination and plants growth. Different soil types have different thermal conductivity. One of soft-computing promising method to predict thermal conductivity of soil types is Artificial Neural Network (ANN). In this study, we estimate the thermal conductivity of soil prediction in a soil-plant complex systems using ANN. With a feed-forward multilayer trained with back-propagation with 4, 10 and 1 on the input, hidden and output layers respectively. Our input are heating time, temperature and thermal resistance with thermal conductivity of soil as a target. ANN prediction demonstrates a good agreement with Mean Squared Error-testing (MSEte) of 9.56 x 10-7 for soils with green beans and those of bare soils is 7.00 × 10-7 respectively Green beans grow only on black-clay soil with a thermal conductivity of 0.7 W/m K with a sufficient water content. Our results demonstrate that temperature, moisture content, colour, texture and structure of soil are greatly affect to the thermal conductivity of soil in seed germination and plant growth. In future, it is potentially applied to estimate more complex compositions of plant-soil systems.

Ups and downs of economics and econophysics — Facebook forecast

NASA Astrophysics Data System (ADS)

Gajic, Nenad; Budinski-Petkovic, Ljuba

2013-01-01

What is econophysics and its relationship with economics? What is the state of economics after the global economic crisis, and is there a future for the paradigm of market equilibrium, with imaginary perfect competition and rational agents? Can the next paradigm of economics adopt important assumptions derived from econophysics models: that markets are chaotic systems, striving to extremes as bubbles and crashes show, with psychologically motivated, statistically predictable individual behaviors? Is the future of econophysics, as predicted here, to disappear and become a part of economics? A good test of the current state of econophysics and its methods is the valuation of Facebook immediately after the initial public offering - this forecast indicates that Facebook is highly overvalued, and its IPO valuation of 104 billion dollars is mostly the new financial bubble based on the expectations of unlimited growth, although it’s easy to prove that Facebook is close to the upper limit of its users.

Can Perceptuo-Motor Skills Assessment Outcomes in Young Table Tennis Players (7-11 years) Predict Future Competition Participation and Performance? An Observational Prospective Study.

PubMed

Faber, Irene R; Elferink-Gemser, Marije T; Faber, Niels R; Oosterveld, Frits G J; Nijhuis-Van der Sanden, Maria W G

2016-01-01

Forecasting future performance in youth table tennis players based on current performance is complex due to, among other things, differences between youth players in growth, development, maturity, context and table tennis experience. Talent development programmes might benefit from an assessment of underlying perceptuo-motor skills for table tennis, which is hypothesized to determine the players' potential concerning the perceptuo-motor domain. The Dutch perceptuo-motor skills assessment intends to measure the perceptuo-motor potential for table tennis in youth players by assessing the underlying skills crucial for developing technical and tactical qualities. Untrained perceptuo-motor tasks are used as these are suggested to represent a player's future potential better than specific sport skills themselves as the latter depend on exposure to the sport itself. This study evaluated the value of the perceptuo-motor skills assessment for a talent developmental programme by evaluating its predictive validity for competition participation and performance in 48 young table tennis players (7-11 years). Players were tested on their perceptuo-motor skills once during a regional talent day, and the subsequent competition results were recorded half-yearly over a period of 2.5 years. Logistic regression analysis showed that test scores did not predict future competition participation (p >0.05). Yet, the Generalized Estimating Equations analysis, including the test items 'aiming at target', 'throwing a ball', and 'eye-hand coordination' in the best fitting model, revealed that the outcomes of the perceptuo-motor skills assessment were significant predictors for future competition results (R2 = 51%). Since the test age influences the perceptuo-motor skills assessment's outcome, another multivariable model was proposed including test age as a covariate (R2 = 53%). This evaluation demonstrates promising prospects for the perceptuo-motor skills assessment to be included in a talent development programme. Future studies are needed to clarify the predictive value in a larger sample of youth competition players over a longer period in time.

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.

Gratitude, hope, mindfulness and personal-growth initiative: buffers or risk factors for problem gambling?

PubMed

Loo, Jasmine M Y; Tsai, Jung-Shun; Raylu, Namrata; Oei, Tian P S

2014-01-01

The majority of prevention and intervention research in problem gambling (PG) has focused on identifying negative risk factors. However, not all at-risk individuals go on to develop anticipated disorders and many thrive in spite of them. In healthcare settings, PG and other disorders are typically conceptualized from the biomedical perspective that frame disorders as something negative residing within the individual and reduction in negativity is seen as success. Indeed, this problem-focused conceptualization may be adequate in many cases as reducing PG behaviour is undoubtedly an important outcome, but the focus on negativity alone is too narrow to capture the complexity of human behaviour. Hence, this study attempts to bridge the gap in literature by providing an evaluation of the predictive ability of the positive dispositions on problem gambling severity, gambling-related cognitions, and gambling urges. The positive psychological dispositions examined were curiosity, gratitude, hope, personal growth initiative, and mindfulness. Participants consisted of 801 Taiwanese Chinese students and community individuals (Mean age = 25.36 years). Higher levels of gratitude and hope have been found to predict lower PG, gambling-related cognitions, or gambling urges. Meanwhile, higher mindfulness predicted lower PG, but only among Chinese males. However, lower personal growth initiative predicted lower PG, gambling-related cognitions, and gambling urges. These analyses have small to medium effect sizes with significant predictions. Findings of this study have essential implications in understanding and treating Chinese problem gamblers. These positive dispositions should be addressed by mental health professionals in preventative and treatment programs among Chinese individuals. Further implications and suggestions for future research are discussed.

System dynamic modelling of industrial growth and landscape ecology in China.

PubMed

Xu, Jian; Kang, Jian; Shao, Long; Zhao, Tianyu

2015-09-15

With the rapid development of large industrial corridors in China, the landscape ecology of the country is currently being affected. Therefore, in this study, a system dynamic model with multi-dimensional nonlinear dynamic prediction function that considers industrial growth and landscape ecology is developed and verified to allow for more sustainable development. Firstly, relationships between industrial development and landscape ecology in China are examined, and five subsystems are then established: industry, population, urban economy, environment and landscape ecology. The main influencing factors are then examined for each subsystem to establish flow charts connecting those factors. Consequently, by connecting the subsystems, an overall industry growth and landscape ecology model is established. Using actual data and landscape index calculated based on GIS of the Ha-Da-Qi industrial corridor, a typical industrial corridor in China, over the period 2005-2009, the model is validated in terms of historical behaviour, logical structure and future prediction, where for 84.8% of the factors, the error rate of the model is less than 5%, the mean error rate of all factors is 2.96% and the error of the simulation test for the landscape ecology subsystem is less than 2%. Moreover, a model application has been made to consider the changes in landscape indices under four industrial development modes, and the optimal industrial growth plan has been examined for landscape ecological protection through the simulation prediction results over 2015-2020. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sibling Competition & Growth Tradeoffs. Biological vs. Statistical Significance

PubMed Central

Kramer, Karen L.; Veile, Amanda; Otárola-Castillo, Erik

2016-01-01

Early childhood growth has many downstream effects on future health and reproduction and is an important measure of offspring quality. While a tradeoff between family size and child growth outcomes is theoretically predicted in high-fertility societies, empirical evidence is mixed. This is often attributed to phenotypic variation in parental condition. However, inconsistent study results may also arise because family size confounds the potentially differential effects that older and younger siblings can have on young children’s growth. Additionally, inconsistent results might reflect that the biological significance associated with different growth trajectories is poorly understood. This paper addresses these concerns by tracking children’s monthly gains in height and weight from weaning to age five in a high fertility Maya community. We predict that: 1) as an aggregate measure family size will not have a major impact on child growth during the post weaning period; 2) competition from young siblings will negatively impact child growth during the post weaning period; 3) however because of their economic value, older siblings will have a negligible effect on young children’s growth. Accounting for parental condition, we use linear mixed models to evaluate the effects that family size, younger and older siblings have on children’s growth. Congruent with our expectations, it is younger siblings who have the most detrimental effect on children’s growth. While we find statistical evidence of a quantity/quality tradeoff effect, the biological significance of these results is negligible in early childhood. Our findings help to resolve why quantity/quality studies have had inconsistent results by showing that sibling competition varies with sibling age composition, not just family size, and that biological significance is distinct from statistical significance. PMID:26938742

Sibling Competition & Growth Tradeoffs. Biological vs. Statistical Significance.

PubMed

Kramer, Karen L; Veile, Amanda; Otárola-Castillo, Erik

2016-01-01

Early childhood growth has many downstream effects on future health and reproduction and is an important measure of offspring quality. While a tradeoff between family size and child growth outcomes is theoretically predicted in high-fertility societies, empirical evidence is mixed. This is often attributed to phenotypic variation in parental condition. However, inconsistent study results may also arise because family size confounds the potentially differential effects that older and younger siblings can have on young children's growth. Additionally, inconsistent results might reflect that the biological significance associated with different growth trajectories is poorly understood. This paper addresses these concerns by tracking children's monthly gains in height and weight from weaning to age five in a high fertility Maya community. We predict that: 1) as an aggregate measure family size will not have a major impact on child growth during the post weaning period; 2) competition from young siblings will negatively impact child growth during the post weaning period; 3) however because of their economic value, older siblings will have a negligible effect on young children's growth. Accounting for parental condition, we use linear mixed models to evaluate the effects that family size, younger and older siblings have on children's growth. Congruent with our expectations, it is younger siblings who have the most detrimental effect on children's growth. While we find statistical evidence of a quantity/quality tradeoff effect, the biological significance of these results is negligible in early childhood. Our findings help to resolve why quantity/quality studies have had inconsistent results by showing that sibling competition varies with sibling age composition, not just family size, and that biological significance is distinct from statistical significance.

Validation databases for simulation models: aboveground biomass and net primary productive, (NPP) estimation using eastwide FIA data

Treesearch

Jennifer C. Jenkins; Richard A. Birdsey

2000-01-01

As interest grows in the role of forest growth in the carbon cycle, and as simulation models are applied to predict future forest productivity at large spatial scales, the need for reliable and field-based data for evaluation of model estimates is clear. We created estimates of potential forest biomass and annual aboveground production for the Chesapeake Bay watershed...

An Experimental Study of Social and Psychological Aspects of Teleworking: The Implications for Tele-Education.

ERIC Educational Resources Information Center

Hobbs, Dave; Armstrong, James

The last few years have seen a growth in interest in the concept of distance-learning in the field of education and in the use of teleworking to provide a way of conducting work from home. Current predictions suggest that these could become very significant ways of learning and working in the future. The contention of this paper is that distance…

Kinetic Growth Rate after Portal Vein Embolization Predicts Posthepatectomy Outcomes: Toward Zero Liver-Related Mortality in Patients with Colorectal Liver Metastases and Small Future Liver Remnant

PubMed Central

Shindoh, Junichi; Truty, Mark J; Aloia, Thomas A; Curley, Steven A; Zimmitti, Giuseppe; Huang, Steven Y; Mahvash, Armeen; Gupta, Sanjay; Wallace, Michael J; Vauthey, Jean-Nicolas

2013-01-01

Background Standardized future liver remnant (sFLR) volume and degree of hypertrophy after portal vein embolization (PVE) have been recognized as significant predictors of surgical outcomes after major liver resection. However, regeneration rate of the FLR after PVE varies among individuals and its clinical significance is unknown. Study Design Degree of hypertrophy at initial volume assessment divided by number of weeks elapsed after PVE was defined as the kinetic growth rate (KGR). In 107 consecutive patients who underwent liver resection for colorectal liver metastases with a sFLR volume of greater than 20%, the ability of the KGR to predict overall and liver-specific postoperative morbidity and mortality was compared with sFLR volume and degree of hypertrophy. Results Using receiver operating characteristic analysis, the best cut-off values for sFLR volume, degree of hypertrophy, and KGR for predicting postoperative hepatic insufficiency were estimated as, respectively, 29.6%, 7.5%, and 2.0% per week. Among these, KGR was the most accurate predictor (area under the curve, 0.830 [0.736-0.923]; asymptotic significance, 0.002). KGR of less than 2% per week vs. ≥2% per week correlate with rates of hepatic insufficiency (21.6% vs. 0%, p = 0.0001) and liver-related 90-day mortality (8.1% vs. 0%, P=0.04). The predictive value of KGR was not influenced by sFLR volume or the timing of initial volume assessment when evaluated within 8 weeks after PVE. Conclusions KGR is a better predictor of postoperative morbidity and mortality after liver resection for small FLR than conventional measured volume parameters (sFLR volume and degree of hypertrophy). PMID:23219349

Tree-ring growth of Scots pine, Common beech and Pedunculate oak under future climate in northeastern Germany

NASA Astrophysics Data System (ADS)

Jurasinski, Gerald; Scharnweber, Tobias; Schröder, Christian; Lennartz, Bernd; Bauwe, Andreas

2017-04-01

Tree growth depends, among other factors, largely on the prevailing climatic conditions. Therefore, tree growth patterns are to be expected under climate change. Here, we analyze the tree-ring growth response of three major European tree species to projected future climate across a climatic (mostly precipitation) gradient in northeastern Germany. We used monthly data for temperature, precipitation, and the standardized precipitation evapotranspiration index (SPEI) over multiple time scales (1, 3, 6, 12, and 24 months) to construct models of tree-ring growth for Scots pine (Pinus syl- vestris L.) at three pure stands, and for Common beech (Fagus sylvatica L.) and Pedunculate oak (Quercus robur L.) at three mature mixed stands. The regression models were derived using a two-step approach based on partial least squares regression (PLSR) to extract potentially well explaining variables followed by ordinary least squares regression (OLSR) to consolidate the models to the least number of variables while retaining high explanatory power. The stability of the models was tested with a comprehensive calibration-verification scheme. All models were successfully verified with R2s ranging from 0.21 for the western pine stand to 0.62 for the beech stand in the east. For growth prediction, climate data forecasted until 2100 by the regional climate model WETTREG2010 based on the A1B Intergovernmental Panel on Climate Change (IPCC) emission scenario was used. For beech and oak, growth rates will likely decrease until the end of the 21st century. For pine, modeled growth trends vary and range from a slight growth increase to a weak decrease in growth rates depending on the position along the climatic gradient. The climatic gradient across the study area will possibly affect the future growth of oak with larger growth reductions towards the drier east. For beech, site-specific adaptations seem to override the influence of the climatic gradient. We conclude that in Northeastern Germany Scots pine has great potential to remain resilient to projected climate change without any greater impairment, whereas Common beech and Pedunculate oak will likely face lesser growth under the expected warmer and dryer climate conditions. The results call for an adaptation of forest management to mitigate the negative effects of climate change for beech and oak in the region.

Recombinant IGF-I: Past, present and future.

PubMed

Bright, George M

2016-06-01

Normal linear growth in humans requires GH and IGF-I. Diminished GH action resulting in reduced availability of IGF-I and IGF-binding proteins is the hallmarks of GH Insensitivity Syndromes (GHIS). The deficiencies are the perceived mechanisms for the growth failure of affected patients and the therapeutic targets for the restoration of normal growth. Early treatment attempts with pituitary-derived GH had limited effects in GHIS patients. Recombinant human insulin-like growth factor-I (rhIGF-I) treatment initially provides accelerated growth to GHIS children and provides substantial benefit. But, in general, catch up growth is less substantial with rhIGF-I treatment of GHIS than with rhGH treatment of GH Deficiency. Few classic GHIS patients have reached heights in the normal range (height SD score between -2.0 SD and +2.0 SD) with rhIGF-I monotherapy. A potential explanation is that while rhIGF-I treatment increases circulating concentrations of IGF-1 and IGFBP-3, such treatment reduces endogenous GH levels by negative feedback inhibition of pituitary GH release. In as much as both GH and IGF-I are required for good catch up growth, the loss of any residual GH signaling during IGF-I monotherapy in GHIS patients may attenuate possible catch up growth. Consistent with this explanation is the finding that, as predicted by the preclinical studies by Ross Clark, combination of rhGH & rhIGF-1 provides better growth responses than rhIGF-1 monotherapy in prepubertal children with short stature and low IGF-I levels despite normal stimulated GH responses. In the future, rhGH and rhIGF-I combination therapy can potentially improve growth outcomes over that seen with rhIGF-I monotherapy in all GHIS patients except in those with a total lack of functional GH signaling. Future alternative treatments for GHIS subjects may also include the use of post-growth hormone receptor signaling agonists which restore both GH signaling and IGF-I exposures or the addition of long-acting rhGH species to rhIGF-I. Additional etiologic factors for the growth failure in GHIS should be considered if the growth deficits of GHIS do not resolve with treatment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Life prediction and constitutive behavior

NASA Technical Reports Server (NTRS)

Halford, G. R.

1983-01-01

One of the primary drivers that prompted the initiation of the hot section technology (HOST) program was the recognized need for improved cyclic durability of costly hot section components. All too frequently, fatigue in one form or another was directly responsible for the less than desired durability, and prospects for the future weren't going to improve unless a significant effort was mounted to increase our knowledge and understanding of the elements governing cyclic crack initiation and propagation lifetime. Certainly one of the important factors is the ability to perform accurate structural stress-strain analyses on a routine basis to determine the magnitudes of the localized stresses and strains since it is these localized conditions that govern the initiation and crack growth processes. Developing the ability to more accurately predict crack initiation lifetimes and cyclic crack growth rates for the complex loading conditions found in turbine engine hot sections is of course the ultimate goal of the life prediction research efforts. It has been found convenient to divide the research efforts into those dealing with nominally isotropic and anisotropic alloys; the latter for application to directionally solidified and single crystal turbine blades.

Predicting First Grade Reading Performance from Kindergarten Response to Tier 1 Instruction

PubMed Central

Al Otaiba, Stephanie; Folsom, Jessica S.; Schatschneider, Christopher; Wanzek, Jeanne; Greulich, Luana; Meadows, Jane; Li, Zhi; Connor, Carol M

2010-01-01

Many schools are beginning to implement multi-tier response to intervention (RTI) models for the prevention of reading difficulties and to assist in the identification of students with learning disabilities (LD). The present study was part of our larger ongoing longitudinal RTI investigation within the Florida Learning Disabilities Center grant. This study used a longitudinal correlational design, conducted in 7 ethnically and socio-economically diverse schools. We observed reading instruction in 20 classrooms, examined response rates to kindergarten Tier 1 instruction, and predicted students’ first grade reading performance based upon kindergarten growth and end of year reading performance (n = 203). Teachers followed an explicit core reading program and overall, classroom instruction was rated as effective. Results indicate that controlling for students’ end of kindergarten reading, their growth across kindergarten on a variety of language and literacy measures suppressed predictions of first grade performance. Specifically, the steeper the students’ trajectory to a satisfactory outcome, the less likely they were to demonstrate good performance in first grade. Implications for future research and RTI implementation are discussed. PMID:21857718

Growth of left ventricular outflow tract and predictors of future re-intervention after repair for ventricular septal defect and aortic arch obstruction.

PubMed

Jijeh, Abdulraouf; Ismail, Muna; Alhabshan, Fahad

2017-09-01

Ventricular septal defect and aortic arch obstruction are usually associated with a narrow left ventricular outflow tract. The aim of the present study was to analyse the growth and predictors of future obstruction of the left ventricular outflow tract after surgical repair. We carried out a retrospective review of patients who underwent repair for ventricular septal defect and aortic arch obstruction - coarctation or interrupted aortic arch - between July, 2002 and June, 2013. Echocardiographic data were reviewed, and the need for re-intervention was evaluated. A total of 89 patients were included in this study. A significant left ventricular outflow tract growth was noticed after surgical repair. Preoperatively, the mean left ventricular outflow tract Z-score was -1.46±1 (range -5.5 to 1.1) and increased to a mean value of -0.7±1.3 (range -2.7 to 3.2) at last follow-up (p=0.0001), demonstrating relevant growth of the left ventricular outflow tract after repair for ventricular septal defect and aortic arch obstruction. After primary repair, 11 patients (12.3%) required re-intervention with surgical repair for left ventricular outflow tract obstruction after a mean period of 36±21 months. There were no significant differences in age, weight, and indexed aortic valve and left ventricular outflow tract measurements between those who developed obstruction and those who did not. Significant left ventricular outflow tract growth is expected after repair of ventricular septal defect and aortic arch obstruction. Small aortic valve and left ventricular outflow tract at diagnosis are not risk factors to predict the need for surgical re-intervention for left ventricular outflow tract obstruction in future.

Statistical short-term earthquake prediction.

PubMed

Kagan, Y Y; Knopoff, L

1987-06-19

A statistical procedure, derived from a theoretical model of fracture growth, is used to identify a foreshock sequence while it is in progress. As a predictor, the procedure reduces the average uncertainty in the rate of occurrence for a future strong earthquake by a factor of more than 1000 when compared with the Poisson rate of occurrence. About one-third of all main shocks with local magnitude greater than or equal to 4.0 in central California can be predicted in this way, starting from a 7-year database that has a lower magnitude cut off of 1.5. The time scale of such predictions is of the order of a few hours to a few days for foreshocks in the magnitude range from 2.0 to 5.0.

Elevated CO2 maintains grassland net carbon uptake under a future heat and drought extreme

PubMed Central

Roy, Jacques; Picon-Cochard, Catherine; Augusti, Angela; Benot, Marie-Lise; Thiery, Lionel; Darsonville, Olivier; Landais, Damien; Piel, Clément; Defossez, Marc; Devidal, Sébastien; Escape, Christophe; Ravel, Olivier; Fromin, Nathalie; Volaire, Florence; Milcu, Alexandru; Bahn, Michael; Soussana, Jean-François

2016-01-01

Extreme climatic events (ECEs) such as droughts and heat waves are predicted to increase in intensity and frequency and impact the terrestrial carbon balance. However, we lack direct experimental evidence of how the net carbon uptake of ecosystems is affected by ECEs under future elevated atmospheric CO2 concentrations (eCO2). Taking advantage of an advanced controlled environment facility for ecosystem research (Ecotron), we simulated eCO2 and extreme cooccurring heat and drought events as projected for the 2050s and analyzed their effects on the ecosystem-level carbon and water fluxes in a C3 grassland. Our results indicate that eCO2 not only slows down the decline of ecosystem carbon uptake during the ECE but also enhances its recovery after the ECE, as mediated by increases of root growth and plant nitrogen uptake induced by the ECE. These findings indicate that, in the predicted near future climate, eCO2 could mitigate the effects of extreme droughts and heat waves on ecosystem net carbon uptake. PMID:27185934

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.

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

Observed forest sensitivity to climate implies large changes in 21st century North American forest growth.

PubMed

Charney, Noah D; Babst, Flurin; Poulter, Benjamin; Record, Sydne; Trouet, Valerie M; Frank, David; Enquist, Brian J; Evans, Margaret E K

2016-09-01

Predicting long-term trends in forest growth requires accurate characterisation of how the relationship between forest productivity and climatic stress varies across climatic regimes. Using a network of over two million tree-ring observations spanning North America and a space-for-time substitution methodology, we forecast climate impacts on future forest growth. We explored differing scenarios of increased water-use efficiency (WUE) due to CO2 -fertilisation, which we simulated as increased effective precipitation. In our forecasts: (1) climate change negatively impacted forest growth rates in the interior west and positively impacted forest growth along the western, southeastern and northeastern coasts; (2) shifting climate sensitivities offset positive effects of warming on high-latitude forests, leaving no evidence for continued 'boreal greening'; and (3) it took a 72% WUE enhancement to compensate for continentally averaged growth declines under RCP 8.5. Our results highlight the importance of locally adapted forest management strategies to handle regional differences in growth responses to climate change. © 2016 John Wiley & Sons Ltd/CNRS.

A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area

USGS Publications Warehouse

Clarke, K.C.; Hoppen, S.; Gaydos, L.

1997-01-01

In this paper we describe a cellular automaton (CA) simulation model developed to predict urban growth as part of a project for estimating the regional and broader impact of urbanization on the San Francisco Bay area's climate. The rules of the model are more complex than those of a typical CA and involve the use of multiple data sources, including topography, road networks, and existing settlement distributions, and their modification over time. In addition, the control parameters of the model are allowed to self-modify: that is, the CA adapts itself to the circumstances it generates, in particular, during periods of rapid growth or stagnation. In addition, the model was written to allow the accumulation of probabilistic estimates based on Monte Carlo methods. Calibration of the model has been accomplished by the use of historical maps to compare model predictions of urbanization, based solely upon the distribution in year 1900, with observed data for years 1940, 1954, 1962, 1974, and 1990. The complexity of this model has made calibration a particularly demanding step. Lessons learned about the methods, measures, and strategies developed to calibrate the model may be of use in other environmental modeling contexts. With the calibration complete, the model is being used to generate a set of future scenarios for the San Francisco Bay area along with their probabilities based on the Monte Carlo version of the model. Animated dynamic mapping of the simulations will be used to allow visualization of the impact of future urban growth.

Aerobic scope fails to explain the detrimental effects on growth resulting from warming and elevated CO2 in Atlantic halibut.

PubMed

Gräns, Albin; Jutfelt, Fredrik; Sandblom, Erik; Jönsson, Elisabeth; Wiklander, Kerstin; Seth, Henrik; Olsson, Catharina; Dupont, Sam; Ortega-Martinez, Olga; Einarsdottir, Ingibjörg; Björnsson, Björn Thrandur; Sundell, Kristina; Axelsson, Michael

2014-03-01

As a consequence of increasing atmospheric CO2, the world's oceans are becoming warmer and more acidic. Whilst the ecological effects of these changes are poorly understood, it has been suggested that fish performance including growth will be reduced mainly as a result of limitations in oxygen transport capacity. Contrary to the predictions given by the oxygen- and capacity-limited thermal tolerance hypothesis, we show that aerobic scope and cardiac performance of Atlantic halibut (Hippoglossus hippoglossus) increase following 14-16 weeks exposure to elevated temperatures and even more so in combination with CO2-acidified seawater. However, the increase does not translate into improved growth, demonstrating that oxygen uptake is not the limiting factor for growth performance at high temperatures. Instead, long-term exposure to CO2-acidified seawater reduces growth at temperatures that are frequently encountered by this species in nature, indicating that elevated atmospheric CO2 levels may have serious implications on fish populations in the future.

Plant movements and climate warming: intraspecific variation in growth responses to nonlocal soils.

PubMed

De Frenne, Pieter; Coomes, David A; De Schrijver, An; Staelens, Jeroen; Alexander, Jake M; Bernhardt-Römermann, Markus; Brunet, Jörg; Chabrerie, Olivier; Chiarucci, Alessandro; den Ouden, Jan; Eckstein, R Lutz; Graae, Bente J; Gruwez, Robert; Hédl, Radim; Hermy, Martin; Kolb, Annette; Mårell, Anders; Mullender, Samantha M; Olsen, Siri L; Orczewska, Anna; Peterken, George; Petřík, Petr; Plue, Jan; Simonson, William D; Tomescu, Cezar V; Vangansbeke, Pieter; Verstraeten, Gorik; Vesterdal, Lars; Wulf, Monika; Verheyen, Kris

2014-04-01

Most range shift predictions focus on the dispersal phase of the colonization process. Because moving populations experience increasingly dissimilar nonclimatic environmental conditions as they track climate warming, it is also critical to test how individuals originating from contrasting thermal environments can establish in nonlocal sites. We assess the intraspecific variation in growth responses to nonlocal soils by planting a widespread grass of deciduous forests (Milium effusum) into an experimental common garden using combinations of seeds and soil sampled in 22 sites across its distributional range, and reflecting movement scenarios of up to 1600 km. Furthermore, to determine temperature and forest-structural effects, the plants and soils were experimentally warmed and shaded. We found significantly positive effects of the difference between the temperature of the sites of seed and soil collection on growth and seedling emergence rates. Migrant plants might thus encounter increasingly favourable soil conditions while tracking the isotherms towards currently 'colder' soils. These effects persisted under experimental warming. Rising temperatures and light availability generally enhanced plant performance. Our results suggest that abiotic and biotic soil characteristics can shape climate change-driven plant movements by affecting growth of nonlocal migrants, a mechanism which should be integrated into predictions of future range shifts. © 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.

Seasonal and Inter-annual Variation in Wood Production in Tropical Trees on Barro Colorado Island, Panama, is Related to Local Climate and Species Functional Traits

NASA Astrophysics Data System (ADS)

Cushman, K.; Muller-Landau, H. C.; Kellner, J. R.; Wright, S. J.; Condit, R.; Detto, M.; Tribble, C. M.

2015-12-01

Tropical forest carbon budgets play a major role in global carbon dynamics, but the responses of tropical forests to current and future inter-annual climatic variation remains highly uncertain. Better predictions of future tropical forest carbon fluxes require an improved understanding of how different species of tropical trees respond to changes in climate at seasonal and inter-annual temporal scales. We installed dendrometer bands on a size-stratified sample of 2000 trees in old growth forest on Barro Colorado Island, Panama, a moist lowland forest that experiences an annual dry season of approximately four months. Tree diameters were measured at the beginning and end of the rainy season since 2008. Additionally, we recorded the canopy illumination level, canopy intactness, and liana coverage of all trees during each census. We used linear mixed-effects models to evaluate how tree growth was related to seasonal and interannual variation in local climate, tree condition, and species identity, and how species identity effects related to tree functional traits. Climatic variables considered included precipitation, solar radiation, soil moisture, and climatological water deficit, and were all calculated from high-quality on-site measurements. Functional traits considered included wood density, maximum adult stature, deciduousness, and drought tolerance. We found that annual wood production was positively related to water availability, with higher growth in wetter years. Species varied in their response to seasonal water availability, with some species showing more pronounced reduction of growth during the dry season when water availability is limited. Interspecific variation in seasonal and interannual growth patterns was related to life-history strategies and species functional traits. The finding of higher growth in wetter years is consistent with previous tree ring studies conducted on a small subset of species with reliable annual rings. Together with previous findings that seed production at this site is higher in sunnier (and drier) years, this suggests strong climate-related shifts in allocation. This study highlights the importance of considering forest species composition and potential allocational shifts when predicting carbon fluxes in response to local climate variation.

Facing the Future: Effects of Short-Term Climate Extremes on Isoprene-Emitting and Nonemitting Poplar1

PubMed Central

Vanzo, Elisa; Jud, Werner; Li, Ziru; Albert, Andreas; Domagalska, Malgorzata A.; Ghirardo, Andrea; Niederbacher, Bishu; Frenzel, Juliane; Beemster, Gerrit T.S.; Asard, Han; Rennenberg, Heinz; Sharkey, Thomas D.; Hansel, Armin; Schnitzler, Jörg-Peter

2015-01-01

Isoprene emissions from poplar (Populus spp.) plantations can influence atmospheric chemistry and regional climate. These emissions respond strongly to temperature, [CO2], and drought, but the superimposed effect of these three climate change factors are, for the most part, unknown. Performing predicted climate change scenario simulations (periodic and chronic heat and drought spells [HDSs] applied under elevated [CO2]), we analyzed volatile organic compound emissions, photosynthetic performance, leaf growth, and overall carbon (C) gain of poplar genotypes emitting (IE) and nonemitting (NE) isoprene. We aimed (1) to evaluate the proposed beneficial effect of isoprene emission on plant stress mitigation and recovery capacity and (2) to estimate the cumulative net C gain under the projected future climate. During HDSs, the chloroplastidic electron transport rate of NE plants became impaired, while IE plants maintained high values similar to unstressed controls. During recovery from HDS episodes, IE plants reached higher daily net CO2 assimilation rates compared with NE genotypes. Irrespective of the genotype, plants undergoing chronic HDSs showed the lowest cumulative C gain. Under control conditions simulating ambient [CO2], the C gain was lower in the IE plants than in the NE plants. In summary, the data on the overall C gain and plant growth suggest that the beneficial function of isoprene emission in poplar might be of minor importance to mitigate predicted short-term climate extremes under elevated [CO2]. Moreover, we demonstrate that an analysis of the canopy-scale dynamics of isoprene emission and photosynthetic performance under multiple stresses is essential to understand the overall performance under proposed future conditions. PMID:26162427

Growth rates of three geographically separated strains of the ichthyotoxic Prymnesium parvum (Prymnesiophyceae) in response to six different pH levels

NASA Astrophysics Data System (ADS)

Lysgaard, Maria L.; Eckford-Soper, Lisa; Daugbjerg, Niels

2018-05-01

Continued anthropogenic carbon emissions are expected to cause a decline in global average pH of the oceans to a projected value of 7.8 by the end of the century. Understanding how harmful algal bloom (HAB) species will respond to lowered pH levels will be important when predicting future HAB events and their ecological consequences. In this study, we examined how manipulated pH levels affected the growth rate of three strains of Prymnesium parvum from North America, Denmark and Japan. Triplicate strains were grown under pH conditions ranging from 6.6 to 9.1 to simulate plausible future levels. Different tolerances were evident for all strains. Significantly higher growth rates were observed at pH 6.6-8.1 compared to growth rates at pH 8.6-9.1 and a lower pH limit was not observed. The Japanese strain (NIES-1017) had the highest maximum growth rate of 0.39 divisions day-1 at pH 6.6 but a low tolerance (0.22 divisions day-1) to high levels (pH 9.1) with growth declining markedly after pH 7.6. The Danish (SCCAP K-0081) and North American (UTEX LB 2797) strains had maximum growth rates of 0.26 and 0.35 divisions day-1, respectively between pH 6.6-8.1. Compared to the other two strains the Danish strain had a statistically lower growth rate across all pH treatments. Strain differences were either attributed to their provenance or the length of time the strain had been in culture.

The Role of Hydromagnetic Waves in the Magnetosphere and the Ionosphere

DTIC Science & Technology

1988-05-01

ionospheric heating ex- ( MINIX ) was carried out recently by the Kyoto Uni- periments [Stubbe and Kopka, 198! Stubbe et al., versity group in Japan to...ionospheric irregularities and other predicted netosphere with growth times of a few minutes. Our phenomena could not be produced in MINIX be- work...ionosphere: Project- HF produced electron density irregularities in the polar iono- MINIX for future solar power satellite, paper presented at 21st

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.

The joint influence of photoperiod and temperature during growth cessation and development of dormancy in white spruce (Picea glauca).

PubMed

Hamilton, Jill A; El Kayal, Walid; Hart, Ashley T; Runcie, Daniel E; Arango-Velez, Adriana; Cooke, Janice E K

2016-11-01

Timely responses to environmental cues enable the synchronization of phenological life-history transitions essential for the health and survival of north-temperate and boreal tree species. While photoperiodic cues will remain persistent under climate change, temperature cues may vary, contributing to possible asynchrony in signals influencing developmental and physiological transitions essential to forest health. Understanding the relative contribution of photoperiod and temperature as determinants of the transition from active growth to dormancy is important for informing adaptive forest management decisions that consider future climates. Using a combination of photoperiod (long = 20 h or short = 8 h day lengths) and temperature (warm = 22 °C/16 °C and cool = 8 °C/4 °C day/night, respectively) treatments, we used microscopy, physiology and modeling to comprehensively examine hallmark traits of the growth-dormancy transition-including bud formation, growth cessation, cold hardiness and gas exchange-within two provenances of white spruce [Picea glauca (Moench) Voss] spanning a broad latitude in Alberta, Canada. Following exposure to experimental treatments, seedlings were transferred to favorable conditions, and the depth of dormancy was assessed by determining the timing and ability of spruce seedlings to resume growth. Short photoperiods promoted bud development and growth cessation, whereas longer photoperiods extended the growing season through the induction of lammas growth. In contrast, cool temperatures under both photoperiodic conditions delayed bud development. Photoperiod strongly predicted the development of cold hardiness, whereas temperature predicted photosynthetic rates associated with active growth. White spruce was capable of attaining endodormancy, but its release was environmentally determined. Dormancy depth varied substantially across experimental treatments suggesting that environmental cues experienced within one season could affect growth in the following season, which is particularly important for a determinate species such as white spruce. The joint influence of these environmental cues points toward the importance of including local constant photoperiod and shifting temperature cues into predictive models that consider how climate change may affect northern forests. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Serum Amino Acid Profiles in Childhood Predict Triglyceride Level in Adulthood: A 7-Year Longitudinal Study in Girls.

PubMed

Wiklund, Petri; Zhang, Xiaobo; Tan, Xiao; Keinänen-Kiukaanniemi, Sirkka; Alen, Markku; Cheng, Sulin

2016-05-01

Branched-chain and aromatic amino acids are associated with high risk of developing dyslipidemia and type II diabetes in adults. This study aimed to examine whether serum amino acid profiles associate with triglyceride concentrations during pubertal growth and predict hypertriglyceridemia in early adulthood. This was a 7.5-year longitudinal study. The study was conducted at the Health Science Laboratory, University of Jyväskylä. A total of 396 nondiabetic Finnish girls aged 11.2 ± 0.8 years at the baseline participated in the study. Body composition was assessed by dual-energy x-ray absorptiometry; serum concentrations of glucose, insulin, and triglyceride by enzymatic photometric methods; and amino acids by nuclear magnetic resonance spectroscopy. Serum leucine and isoleucine correlated significantly with future triglyceride, independent of baseline triglyceride level (P < .05 for all). In early adulthood (at the age of 18 years), these amino acids were significantly associated with hypertriglyceridemia, whereas fat mass and homeostasis model assessment of insulin resistance were not. Leucine was the strongest determinant discriminating subjects with hypertriglyceridemia from those with normal triglyceride level (area under the curve, 0.822; 95% confidence interval, 0.740-0.903; P = .000001). Serum leucine and isoleucine were associated with future serum triglyceride levels in girls during pubertal growth and predicted hypertriglyceridemia in early adulthood. Therefore, these amino acid indices may serve as biomarkers to identify individuals at high risk for developing hypertriglyceridemia and cardiovascular disease later in life. Further studies are needed to elucidate the role these amino acids play in the lipid metabolism.

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Johnson, Hoyt; Khan, Maudood

2006-01-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Remote Sensing and Spatial Growth Modeling Coupled With Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Astrophysics Data System (ADS)

Quattrochi, D. A.; Estes, M. G.; Crosson, W. L.; Johnson, H.; Khan, M.

2006-05-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world's population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta's growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Changing Relationship Growth Belief: Intrapersonal and Interpersonal Consequences of Compassionate Goals

PubMed Central

Canevello, Amy; Crocker, Jennifer

2010-01-01

The belief that difficulties can lead to growth in relationships, or growth belief, has consequences for relationships (e.g., Knee, 1998). But what predicts change in this belief? We hypothesized that compassionate goals to support others (Crocker & Canevello, 2008) predict increased growth belief through increased need satisfaction. In Study 1, 199 college freshmen reported their friendship growth belief and goals. In Study 2, 65 roommate pairs reported their roommate growth belief, goals, and need satisfaction. Across studies, compassionate goals predicted increased growth belief. In Study 2, goals predicted increased perceived mutual need satisfaction, which predicted increased growth belief. Additionally, partners’ compassionate goals predicted actors’ increased growth belief. Results suggest that growth beliefs are shaped by goals – own and others’. PMID:21949478

The impact of future climate on historic interiors.

PubMed

Lankester, Paul; Brimblecombe, Peter

2012-02-15

The socio-economic significance of climate change is widely recognised. However, its potential to affect our cultural heritage has not been discussed in detail (i.e. not explicit in IPCC 4) even though the cultural impacts of future outdoor climate have been the focus of some European Commission projects (e.g. NOAH'S ARK) and World Heritage Centre reports. Recently there have been a few projects that have examined the changing environmental threats to tangible heritage indoors (e.g. Preparing Historic Collections for Climate Change and Climate for Culture). Here we predict future indoor temperature and humidity, and damage arising from changes to climate in historic rooms in Southern England with little climate control, using simple building simulations coupled with high resolution (~5 km) climate predictions. The calculations suggest an increase in indoor temperature over the next century that is slightly less than that outdoors. Annual relative humidity shows little change, but the seasonal cycles suggest drier summers and slightly damper winters indoors. Damage from mould growth and pests is likely to increase in the future, while humidity driven dimensional change to materials (e.g. wood) should decrease somewhat. The results allow collection managers to prepare for the impact of long-term climate change, putting strategic measures in place to prevent increased damage, and thus preserve our heritage for future generations. Copyright © 2011 Elsevier B.V. All rights reserved.

Resources and economic growth: the American future--a dialogue. [Debate of geologist, physicist, and systems analyst

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

Meadows, D.L.; Weinberg, A.M.; Boyd, J.

Geologist James Boyd, physicist Alvin Weinberg, and systems analyst Dennis Meadows participated in a debate at which they forecast the cost and availability of world resources. Highlights of the debate and questions and comments from their audience are presented here. A range of optimism is evident in the predictions. Boyd foresees that energy and resource problems will be solved by technology, while Meadows contends that no solutions are possible until institutional and political constraints are lifted to allow resource development. Weinberg takes a middle view and proposes substitution of new resources for those, like fossil fuels, that are nearing depletion.more » The role of the market system is debated with disagreement over whether energy development should or can respond to a free market--and whether per capita energy consumption will increase or decline with limited economic growth. Policies governing access to fossil fuels and metals in the future are felt to be central to the issue. (DCK)« less

Stressful Life Events and Predictors of Post-traumatic Growth among High-Risk Early Emerging Adults.

PubMed

Arpawong, Thalida E; Rohrbach, Louise A; Milam, Joel E; Unger, Jennifer B; Land, Helen; Sun, Ping; Spruijt-Metz, Donna; Sussman, Steve

2016-01-01

Stressful life events (SLEs) may elicit positive psychosocial change among youth, referred to as Post-traumatic Growth (PTG). We assessed types of SLEs experienced, degree to which participants reported PTG, and variables predicting PTG across 24 months among a sample of high risk, ethnically diverse early emerging adults. Participants were recruited from alternative high schools ( n = 564; mean age=16.8; 65% Hispanic). Multi-level regression models were constructed to examine the impact of environmental (SLE quantity, severity) and personal factors (hedonic ability, perceived stress, developmental stage, future time orientation) on a composite score of PTG. The majority of participants reported positive changes resulted from their most life-altering SLE of the past two years. Predictors of PTG included fewer SLEs, less general stress, having a future time perspective, and greater identification with the developmental stage of Emerging Adulthood. Findings suggest intervention targets to foster positive adaptation among early emerging adults who experience frequent SLEs.

Model selection and constraints from holographic dark energy scenarios

NASA Astrophysics Data System (ADS)

Akhlaghi, I. A.; Malekjani, M.; Basilakos, S.; Haghi, H.

2018-07-01

In this study, we combine the expansion and the growth data in order to investigate the ability of the three most popular holographic dark energy models, namely event future horizon, Ricci scale, and Granda-Oliveros IR cutoffs, to fit the data. Using a standard χ2 minimization method, we place tight constraints on the free parameters of the models. Based on the values of the Akaike and Bayesian information criteria, we find that two out of three holographic dark energy models are disfavoured by the data, because they predict a non-negligible amount of fractional dark energy density at early enough times. Although the growth rate data are relatively consistent with the holographic dark energy models which are based on Ricci scale and Granda-Oliveros IR cutoffs, the combined analysis provides strong indications against these models. Finally, we find that the model for which the holographic dark energy is related with the future horizon is consistent with the combined observational data.

The voluntary community health movement in India: a strengths, weaknesses, opportunities, and threats (SWOT) analysis.

PubMed

Sharma, M; Bhatia, G

1996-12-01

There has been a prolific growth of voluntary organizations in India since independence in 1947. One of the major areas of this growth has been in the field of community health. The purpose of this article is to historically trace the voluntary movement in community health in India, analyze the current status, and predict future trends of voluntary efforts. A review of the literature in the form of a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis was the method of this study. Some of the key trends which emerged as the priority areas for progress and for strengthening voluntary organizations in the future were enhancing linkages between health and development; building upon collective force; greater utilization of participatory training; establishing egalitarian and effectual linkages for decision making at the international level; developing self-reliant community-based models; and the need for attaining holistic empowerment at individual, organizational, and community levels through "duty consciousness" as opposed to merely asking for rights.

Molecular and cellular biology of cerebral arteriovenous malformations: a review of current concepts and future trends in treatment.

PubMed

Rangel-Castilla, Leonardo; Russin, Jonathan J; Martinez-Del-Campo, Eduardo; Soriano-Baron, Hector; Spetzler, Robert F; Nakaji, Peter

2014-09-01

Arteriovenous malformations (AVMs) are classically described as congenital static lesions. However, in addition to rupturing, AVMs can undergo growth, remodeling, and regression. These phenomena are directly related to cellular, molecular, and physiological processes. Understanding these relationships is essential to direct future diagnostic and therapeutic strategies. The authors performed a search of the contemporary literature to review current information regarding the molecular and cellular biology of AVMs and how this biology will impact their potential future management. A PubMed search was performed using the key words "genetic," "molecular," "brain," "cerebral," "arteriovenous," "malformation," "rupture," "management," "embolization," and "radiosurgery." Only English-language papers were considered. The reference lists of all papers selected for full-text assessment were reviewed. Current concepts in genetic polymorphisms, growth factors, angiopoietins, apoptosis, endothelial cells, pathophysiology, clinical syndromes, medical treatment (including tetracycline and microRNA-18a), radiation therapy, endovascular embolization, and surgical treatment as they apply to AVMs are discussed. Understanding the complex cellular biology, physiology, hemodynamics, and flow-related phenomena of AVMs is critical for defining and predicting their behavior, developing novel drug treatments, and improving endovascular and surgical therapies.

Declining Radial Growth Response of Coastal Forests to Hurricanes and Nor'easters

NASA Astrophysics Data System (ADS)

Fernandes, Arnold; Rollinson, Christine R.; Kearney, William S.; Dietze, Michael C.; Fagherazzi, Sergio

2018-03-01

The Mid-Atlantic coastal forests in Virginia are stressed by episodic disturbance from hurricanes and nor'easters. Using annual tree ring data, we adopt a dendroclimatic and statistical modeling approach to understand the response and resilience of a coastal pine forest to extreme storm events, over the past few decades. Results indicate that radial growth of trees in the study area is influenced by age, regional climate trends, and individual tree effects but dominated periodically by growth disturbance due to storms. We evaluated seven local extreme storm events to understand the effect of nor'easters and hurricanes on radial growth. A general decline in radial growth was observed in the year of the extreme storm and 3 years following it, after which the radial growth started recovering. The decline in radial growth showed a statistically significant correlation with the magnitude of the extreme storm (storm surge height and wind speed). This study contributes to understanding declining tree growth response and resilience of coastal forests to past disturbances. Given the potential increase in hurricanes and storm surge severity in the region, this can help predict vegetation response patterns to similar disturbances in the future.

Growth Scenarios for the City of Guangzhou, China: Transferability and Confirmability

NASA Astrophysics Data System (ADS)

Lehner, A.; Kraus, V.; Wei, C.; Steinnocher, K.

2016-09-01

This work deals with the development of urban growth scenarios and the prevision of the spatial distribution of built-up area and population for the urban area of the city of Guangzhou in China. Using freely-available data, including remotely sensed data as well as census data from the ground, expenditure of time and costs shall remain low. Guangzhou, one of the biggest cities within the Pearl River Delta, has faced an enormous economic and urban growth during the last three decades. Due to its economical and spatial characteristics it is a promising candidate for urban growth scenarios. The monitoring and prediction of urban growth comprises data of population and give them a spatial representation. The model, originally applied for the Indian city Ahmedabad, is used for urban growth scenarios. Therefore, transferability and confirmability of the model are evaluated. Challenges that may occur by transferring a model for urban growth from one region to another are discussed. With proposing the use of urban remote sensing and freely available data, urban planners shall be fitted with a comprehensible and simple tool to be able to contribute to the future challenge Smart Growth.

The Flexible Solar Utility. Preparing for Solar's Impacts to Utility Planning and Operations

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

Sterling, John; Davidovich, Ted; Cory, Karlynn

2015-09-01

This paper seeks to provide a flexible utility roadmap for identifying the steps that need to be taken to place the utility in the best position for addressing solar in the future. Solar growth and the emergence of new technologies will change the electric utility of tomorrow. Although not every utility, region, or market will change in the same way or magnitude, developing a path forward will be needed to reach the Electric System of the Future in the coming decades. In this report, a series of potential future states are identified that could result in drastically different energy mixesmore » and profiles: 1) Business as Usual, 2) Low Carbon, Centralized Generation, 3) Rapid Distributed Energy Resource Growth, 4) Interactivity of Both the Grid and Demand, and 5) Grid or Load Defection. Complicating this process are a series of emerging disruptions; decisions or events that will cause the electric sector to change. Understanding and preparing for these items is critical for the transformation to any of the future states to be successful. Predicting which future state will predominate 15 years from now is not possible; however, utilities still will need to look ahead and try to anticipate how factors will impact their planning, operations, and business models. In order to dig into the potential transformations facing the utility industry, the authors conducted a series of utility interviews, held a working session at a major industry solar conference, and conducted a quantitative survey. To focus conversations, the authors leveraged the Rapid Distributed Energy Resource (DER) Growth future to draw out how utilities would have to adapt from current processes and procedures in order to manage and thrive in that new environment. Distributed solar was investigated specifically, and could serve as a proxy resource for all distributed generation (DG). It can also provide the foundation for all DERs.« less

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.

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

Ahmed, K.; Tonks, M.; Zhang, Y.

A detailed phase field model for the effect of pore drag on grain growth kinetics was implemented in MARMOT. The model takes into consideration both the curvature-driven grain boundary motion and pore migration by surface diffusion. As such, the model accounts for the interaction between pore and grain boundary kinetics, which tends to retard the grain growth process. Our 2D and 3D simulations demonstrate that the model capture all possible pore-grain boundary interactions proposed in theoretical models. For high enough surface mobility, the pores move along with the migrating boundary as a quasi-rigid-body, albeit hindering its migration rate compared tomore » the pore-free case. For less mobile pores, the migrating boundary can separate from the pores. For the pore-controlled grain growth kinetics, the model predicts a strong dependence of the growth rate on the number of pores, pore size, and surface diffusivity in agreement with theroretical models. An evolution equation for the grain size that includes these parameters was derived and showed to agree well with numerical solution. It shows a smooth transition from boundary-controlled kinetics to pore-controlled kinetics as the surface diffusivity decreases or the number of pores or their size increases. This equation can be utilized in BISON to give accurate estimate for the grain size evolution. This will be accomplished in the near future. The effect of solute drag and anisotropy of grain boundary on grain growth will be investigated in future studies.« less

Modeling Studies of PVT Growth of ZnSe: Current Status and Future Course

NASA Technical Reports Server (NTRS)

Ramachandran, N.; Su, Ching-Hua

1999-01-01

Bulk growth of wide band gap II-VI semiconductors by physical vapor transport (PVT) has been developed and refined over the past several years at NASA Marshall Space Flight Center. Results from a modeling study of PVT crystal growth of ZnSe are reported in this paper. The PVT process is numerically investigated using a two-dimensional formulation of the governing equations and associated boundary conditions. Both the incompressible Boussinesq approximation and a compressible model are tested to determine the influence of gravity on the process and to discern the differences between the two approaches. The influence of a residual gas is included in the models. The results show that both the incompressible and compressible approximations provide comparable results and the presence of a residual gas tends to measurably reduce the mass flux in the system. Detailed flow, thermal and concentration profiles are provided. The simulations show that the Stefan flux dominates the system flow field and the subtle gravitational effects can be gauged by subtracting this flux from the calculated profiles. Shear flows, due to solutal buoyancy, of the order of 50 microns/s for the liorizont,-d growth orientation and 10 microns/s for the vertical orientation are predicted. Whether these flows can fully account for the observed gravity related growth morphological effects and inhomogeneous solute and dopant distributions is a matter of conjecture. A template for future modeling efforts in this area is suggested which incorporates a mathematical approach to the tracking of the growth front based on energy of formation concepts.

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.

Past and predicted future effects of housing growth on open space conservation opportunity areas and habitat connectivity around National Wildlife Refuges

USGS Publications Warehouse

Hamilton, Christopher M.; Baumann, Matthias; Pidgeon, Anna M.; Helmers, David P.; Thogmartin, Wayne E.; Heglund, Patricia J.; Radeloff, Volker C.

2016-01-01

ContextHousing growth can alter suitability of matrix habitats around protected areas, strongly affecting movements of organisms and, consequently, threatening connectivity of protected area networks.ObjectivesOur goal was to quantify distribution and growth of housing around the U.S. Fish and Wildlife Service National Wildlife Refuge System. This is important information for conservation planning, particularly given promotion of habitat connectivity as a climate change adaptation measure.MethodsWe quantified housing growth from 1940 to 2000 and projected future growth to 2030 within three distances from refuges, identifying very low housing density open space, “opportunity areas” (contiguous areas with <6.17 houses/km2), both nationally and by USFWS administrative region. Additionally, we quantified number and area of habitat corridors within these opportunity areas in 2000.ResultsOur results indicated that the number and area of open space opportunity areas generally decreased with increasing distance from refuges and with the passage of time. Furthermore, total area in habitat corridors was much lower than in opportunity areas. In addition, the number of corridors sometimes exceeded number of opportunity areas as a result of habitat fragmentation, indicating corridors are likely vulnerable to land use change. Finally, regional differences were strong and indicated some refuges may have experienced so much housing growth already that they are effectively too isolated to adapt to climate change, while others may require extensive habitat restoration work.ConclusionsWildlife refuges are increasingly isolated by residential housing development, potentially constraining the movement of wildlife and, therefore, their ability to adapt to a changing climate.

Bayesian Knowledge Fusion in Prognostics and Health Management—A Case Study

NASA Astrophysics Data System (ADS)

Rabiei, Masoud; Modarres, Mohammad; Mohammad-Djafari, Ali

2011-03-01

In the past few years, a research effort has been in progress at University of Maryland to develop a Bayesian framework based on Physics of Failure (PoF) for risk assessment and fleet management of aging airframes. Despite significant achievements in modelling of crack growth behavior using fracture mechanics, it is still of great interest to find practical techniques for monitoring the crack growth instances using nondestructive inspection and to integrate such inspection results with the fracture mechanics models to improve the predictions. The ultimate goal of this effort is to develop an integrated probabilistic framework for utilizing all of the available information to come up with enhanced (less uncertain) predictions for structural health of the aircraft in future missions. Such information includes material level fatigue models and test data, health monitoring measurements and inspection field data. In this paper, a case study of using Bayesian fusion technique for integrating information from multiple sources in a structural health management problem is presented.

Darcy's law predicts widespread forest mortality under climate warming

NASA Astrophysics Data System (ADS)

McDowell, Nathan G.; Allen, Craig D.

2015-07-01

Drought and heat-induced tree mortality is accelerating in many forest biomes as a consequence of a warming climate, resulting in a threat to global forests unlike any in recorded history. Forests store the majority of terrestrial carbon, thus their loss may have significant and sustained impacts on the global carbon cycle. We use a hydraulic corollary to Darcy’s law, a core principle of vascular plant physiology, to predict characteristics of plants that will survive and die during drought under warmer future climates. Plants that are tall with isohydric stomatal regulation, low hydraulic conductance, and high leaf area are most likely to die from future drought stress. Thus, tall trees of old-growth forests are at the greatest risk of loss, which has ominous implications for terrestrial carbon storage. This application of Darcy’s law indicates today’s forests generally should be replaced by shorter and more xeric plants, owing to future warmer droughts and associated wildfires and pest attacks. The Darcy’s corollary also provides a simple, robust framework for informing forest management interventions needed to promote the survival of current forests. Given the robustness of Darcy’s law for predictions of vascular plant function, we conclude with high certainty that today’s forests are going to be subject to continued increases in mortality rates that will result in substantial reorganization of their structure and carbon storage.

Envisioning Nano Release Dynamics in a Changing World: Using Dynamic Probabilistic Modeling to Assess Future Environmental Emissions of Engineered Nanomaterials.

PubMed

Sun, Tian Yin; Mitrano, Denise M; Bornhöft, Nikolaus A; Scheringer, Martin; Hungerbühler, Konrad; Nowack, Bernd

2017-03-07

The need for an environmental risk assessment for engineered nanomaterials (ENM) necessitates the knowledge about their environmental emissions. Material flow models (MFA) have been used to provide predicted environmental emissions but most current nano-MFA models consider neither the rapid development of ENM production nor the fact that a large proportion of ENM are entering an in-use stock and are released from products over time (i.e., have a lag phase). Here we use dynamic probabilistic material flow modeling to predict scenarios of the future flows of four ENM (nano-TiO 2 , nano-ZnO, nano-Ag and CNT) to environmental compartments and to quantify their amounts in (temporary) sinks such as the in-use stock and ("final") environmental sinks such as soil and sediment. In these scenarios, we estimate likely future amounts if the use and distribution of ENM in products continues along current trends (i.e., a business-as-usual approach) and predict the effect of hypothetical trends in the market development of nanomaterials, such as the emergence of a new widely used product or the ban on certain substances, on the flows of nanomaterials to the environment in years to come. We show that depending on the scenario and the product type affected, significant changes of the flows occur over time, driven by the growth of stocks and delayed release dynamics.

Darcy’s law predicts widespread forest mortality under climate warming

USGS Publications Warehouse

McDowell, Nate G.; Allen, Craig D.

2015-01-01

Drought and heat-induced tree mortality is accelerating in many forest biomes as a consequence of a warming climate, resulting in a threat to global forests unlike any in recorded history. Forests store the majority of terrestrial carbon, thus their loss may have significant and sustained impacts on the global carbon cycle. We use a hydraulic corollary to Darcy’s law, a core principle of vascular plant physiology, to predict characteristics of plants that will survive and die during drought under warmer future climates. Plants that are tall with isohydric stomatal regulation, low hydraulic conductance, and high leaf area are most likely to die from future drought stress. Thus, tall trees of old-growth forests are at the greatest risk of loss, which has ominous implications for terrestrial carbon storage. This application of Darcy’s law indicates today’s forests generally should be replaced by shorter and more xeric plants, owing to future warmer droughts and associated wildfires and pest attacks. The Darcy’s corollary also provides a simple, robust framework for informing forest management interventions needed to promote the survival of current forests. Given the robustness of Darcy’s law for predictions of vascular plant function, we conclude with high certainty that today’s forests are going to be subject to continued increases in mortality rates that will result in substantial reorganization of their structure and carbon storage.

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.

Climate change risk to forests in China associated with warming.

PubMed

Yin, Yunhe; Ma, Danyang; Wu, Shaohong

2018-01-11

Variations in forest net primary productivity (NPP) reflects the combined effects of key climate variables on ecosystem structure and function, especially on the carbon cycle. We performed risk analysis indicated by the magnitude of future negative anomalies in NPP in comparison with the natural interannual variability to investigate the impact of future climatic projections on forests in China. Results from the multi-model ensemble showed that climate change risk of decreases in forest NPP would be more significant in higher emission scenario in China. Under relatively low emission scenarios, the total area of risk was predicted to decline, while for RCP8.5, it was predicted to first decrease and then increase after the middle of 21st century. The rapid temperature increases predicted under the RCP8.5 scenario would be probably unfavorable for forest vegetation growth in the long term. High-level risk area was likely to increase except RCP2.6. The percentage area at high risk was predicted to increase from 5.39% (2021-2050) to 27.62% (2071-2099) under RCP8.5. Climate change risk to forests was mostly concentrated in southern subtropical and tropical regions, generally significant under high emission scenario of RCP8.5, which was mainly attributed to the intensified dryness in south China.

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.

Brain Structural Integrity and Intrinsic Functional Connectivity Forecast 6 Year Longitudinal Growth in Children's Numerical Abilities.

PubMed

Evans, Tanya M; Kochalka, John; Ngoon, Tricia J; Wu, Sarah S; Qin, Shaozheng; Battista, Christian; Menon, Vinod

2015-08-19

Early numerical proficiency lays the foundation for acquiring quantitative skills essential in today's technological society. Identification of cognitive and brain markers associated with long-term growth of children's basic numerical computation abilities is therefore of utmost importance. Previous attempts to relate brain structure and function to numerical competency have focused on behavioral measures from a single time point. Thus, little is known about the brain predictors of individual differences in growth trajectories of numerical abilities. Using a longitudinal design, with multimodal imaging and machine-learning algorithms, we investigated whether brain structure and intrinsic connectivity in early childhood are predictive of 6 year outcomes in numerical abilities spanning childhood and adolescence. Gray matter volume at age 8 in distributed brain regions, including the ventrotemporal occipital cortex (VTOC), the posterior parietal cortex, and the prefrontal cortex, predicted longitudinal gains in numerical, but not reading, abilities. Remarkably, intrinsic connectivity analysis revealed that the strength of functional coupling among these regions also predicted gains in numerical abilities, providing novel evidence for a network of brain regions that works in concert to promote numerical skill acquisition. VTOC connectivity with posterior parietal, anterior temporal, and dorsolateral prefrontal cortices emerged as the most extensive network predicting individual gains in numerical abilities. Crucially, behavioral measures of mathematics, IQ, working memory, and reading did not predict children's gains in numerical abilities. Our study identifies, for the first time, functional circuits in the human brain that scaffold the development of numerical skills, and highlights potential biomarkers for identifying children at risk for learning difficulties. Children show substantial individual differences in math abilities and ease of math learning. Early numerical abilities provide the foundation for future academic and professional success in an increasingly technological society. Understanding the early identification of poor math skills has therefore taken on great significance. This work provides important new insights into brain structure and connectivity measures that can predict longitudinal growth of children's math skills over a 6 year period, and may eventually aid in the early identification of children who might benefit from targeted interventions. Copyright © 2015 the authors 0270-6474/15/3511743-08$15.00/0.

Energy efficient engine: Propulsion system-aircraft integration evaluation

NASA Technical Reports Server (NTRS)

Owens, R. E.

1979-01-01

Flight performance and operating economics of future commercial transports utilizing the energy efficient engine were assessed as well as the probability of meeting NASA's goals for TSFC, DOC, noise, and emissions. Results of the initial propulsion systems aircraft integration evaluation presented include estimates of engine performance, predictions of fuel burns, operating costs of the flight propulsion system installed in seven selected advanced study commercial transports, estimates of noise and emissions, considerations of thrust growth, and the achievement-probability analysis.

Cross-continent comparisons reveal differing environmental drivers of growth of the coral reef fish, Lutjanus bohar

NASA Astrophysics Data System (ADS)

Ong, Joyce J. L.; Rountrey, Adam N.; Marriott, Ross J.; Newman, Stephen J.; Meeuwig, Jessica J.; Meekan, Mark G.

2017-03-01

Biochronologies provide important insights into the growth responses of fishes to past variability in physical and biological environments and, in so doing, allow modelling of likely responses to climate change in the future. We examined spatial variability in the key drivers of inter-annual growth patterns of a widespread, tropical snapper, Lutjanus bohar, at similar tropical latitudes on the north-western and north-eastern coasts of the continent of Australia. For this study, we developed biochronologies from otoliths that provided proxies of somatic growth and these were analysed using mixed-effects models to examine the historical drivers of growth. Our analyses demonstrated that growth patterns of fish were driven by different climatic and biological factors in each region, including Pacific Ocean climate indices, regional sea level and the size structure of the fish community. Our results showed that the local oceanographic and biological context of reef systems strongly influenced the growth of L. bohar and that a single age-related growth trend cannot be assumed for separate populations of this species that are likely to experience different environmental conditions. Generalised predictions about the growth response of fishes to climate change will thus require adequate characterisation of the spatial variability in growth determinants likely to be found throughout the range of species that have cosmopolitan distributions.

Envisaging the Regulation of Alkaloid Biosynthesis and Associated Growth Kinetics in Hairy Roots of Vinca minor Through the Function of Artificial Neural Network.

PubMed

Verma, Priyanka; Anjum, Shahin; Khan, Shamshad Ahmad; Roy, Sudeep; Odstrcilik, Jan; Mathur, Ajay Kumar

2016-03-01

Artificial neural network based modeling is a generic approach to understand and correlate different complex parameters of biological systems for improving the desired output. In addition, some new inferences can also be predicted in a shorter time with less cost and labor. As terpenoid indole alkaloid pathway in Vinca minor is very less investigated or elucidated, a strategy of elicitation with hydroxylase and acetyltransferase along with incorporation of various precursors from primary shikimate and secoiridoid pools via simultaneous employment of cyclooxygenase inhibitor was performed in the hairy roots of V. minor. This led to the increment in biomass accumulation, total alkaloid concentration, and vincamine production in selected treatments. The resultant experimental values were correlated with algorithm approaches of artificial neural network that assisted in finding the yield of vincamine, alkaloids, and growth kinetics using number of elicits. The inputs were the hydroxylase/acetyltransferase elicitors and cyclooxygenase inhibitor along with various precursors from shikimate and secoiridoid pools and the outputs were growth index (GI), alkaloids, and vincamine. The approach incorporates two MATLAB codes; GRNN and FFBPNN. Growth kinetic studies revealed that shikimate and tryptophan supplementation triggers biomass accumulation (GI = 440.2 to 540.5); while maximum alkaloid (3.7 % dry wt.) and vincamine production (0.017 ± 0.001 % dry wt.) was obtained on supplementation of secologanin along with tryptophan, naproxen, hydrogen peroxide, and acetic anhydride. The study shows that experimental and predicted values strongly correlate each other. The correlation coefficient for growth index (GI), alkaloids, and vincamine was found to be 0.9997, 0.9980, 0.9511 in GRNN and 0.9725, 0.9444, 0.9422 in FFBPNN, respectively. GRNN provided greater similarity between the target and predicted dataset in comparison to FFBPNN. The findings can provide future insights to calculate growth index, alkaloids, and vincamine in combination to different elicits.

iTREE: Long-term variability of tree growth in a changing environment - identifying physiological mechanisms using stable C and O isotopes in tree rings.

NASA Astrophysics Data System (ADS)

Siegwolf, R. T. W.; Buchmann, N.; Frank, D.; Joos, F.; Kahmen, A.; Treydte, K.; Leuenberger, M.; Saurer, M.

2012-04-01

Trees play are a critical role in the carbon cycle - their photosynthetic assimilation is one of the largest terrestrial carbon fluxes and their standing biomass represents the largest carbon pool of the terrestrial biosphere. Understanding how tree physiology and growth respond to long-term environmental change is pivotal to predict the magnitude and direction of the terrestrial carbon sink. iTREE is an interdisciplinary research framework to capitalize on synergies among leading dendroclimatologists, plant physiologists, isotope specialists, and global carbon cycle modelers with the objectives of reducing uncertainties related to tree/forest growth in the context of changing natural environments. Cross-cutting themes in our project are tree rings, stable isotopes, and mechanistic modelling. We will (i) establish a European network of tree-ring based isotope time-series to retrodict interannual to long-term tree physiological changes, (ii) conduct laboratory and field experiments to adapt a mechanistic isotope model to derive plant physiological variables from tree-ring isotopes, (iii) implement this model into a dynamic global vegetation model, and perform subsequent model-data validation exercises to refine model representation of plant physiological processes and (iv) attribute long-term variation in tree growth to plant physiological and environmental drivers, and identify how our refined knowledge revises predictions of the coupled carbon-cycle climate system. We will contribute to i) advanced quantifications of long-term variation in tree growth across Central Europe, ii) novel long-term information on key physiological processes that underlie variations in tree growth, and iii) improved carbon cycle models that can be employed to revise predictions of the coupled carbon-cycle climate system. Hence iTREE will significantly contribute towards a seamless understanding of the responses of terrestrial ecosystems to long-term environmental change, and ultimately help reduce uncertainties of the magnitude and direction of the past and future terrestrial carbon sink.

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.

Ocean acidification reverses the positive effects of seawater pH fluctuations on growth and photosynthesis of the habitat-forming kelp, Ecklonia radiata.

PubMed

Britton, Damon; Cornwall, Christopher E; Revill, Andrew T; Hurd, Catriona L; Johnson, Craig R

2016-05-27

Ocean acidification (OA) is the reduction in seawater pH due to the absorption of human-released CO2 by the world's oceans. The average surface oceanic pH is predicted to decline by 0.4 units by 2100. However, kelp metabolically modifies seawater pH via photosynthesis and respiration in some temperate coastal systems, resulting in daily pH fluctuations of up to ±0.45 units. It is unknown how these fluctuations in pH influence the growth and physiology of the kelp, or how this might change with OA. In laboratory experiments that mimicked the most extreme pH fluctuations measured within beds of the canopy-forming kelp Ecklonia radiata in Tasmania, the growth and photosynthetic rates of juvenile E. radiata were greater under fluctuating pH (8.4 in the day, 7.8 at night) than in static pH treatments (8.4, 8.1, 7.8). However, pH fluctuations had no effect on growth rates and a negative effect on photosynthesis when the mean pH of each treatment was reduced by 0.3 units. Currently, pH fluctuations have a positive effect on E. radiata but this effect could be reversed in the future under OA, which is likely to impact the future ecological dynamics and productivity of habitats dominated by E. radiata.

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

Targeting Epidermal Growth Factor Receptor-Related Signaling Pathways in Pancreatic Cancer.

PubMed

Philip, Philip A; Lutz, Manfred P

2015-10-01

Pancreatic cancer is aggressive, chemoresistant, and characterized by complex and poorly understood molecular biology. The epidermal growth factor receptor (EGFR) pathway is frequently activated in pancreatic cancer; therefore, it is a rational target for new treatments. However, the EGFR tyrosine kinase inhibitor erlotinib is currently the only targeted therapy to demonstrate a very modest survival benefit when added to gemcitabine in the treatment of patients with advanced pancreatic cancer. There is no molecular biomarker to predict the outcome of erlotinib treatment, although rash may be predictive of improved survival; EGFR expression does not predict the biologic activity of anti-EGFR drugs in pancreatic cancer, and no EGFR mutations are identified as enabling the selection of patients likely to benefit from treatment. Here, we review clinical studies of EGFR-targeted therapies in combination with conventional cytotoxic regimens or multitargeted strategies in advanced pancreatic cancer, as well as research directed at molecules downstream of EGFR as alternatives or adjuncts to receptor targeting. Limitations of preclinical models, patient selection, and trial design, as well as the complex mechanisms underlying resistance to EGFR-targeted agents, are discussed. Future clinical trials must incorporate translational research end points to aid patient selection and circumvent resistance to EGFR inhibitors.

Does Demand for Breast Augmentation Reflect National Financial Trends?

PubMed

Kearney, L; Dolan, R T; Clover, A J; Kelly, E J; O'Broin, E; O'Shaughnessy, M; O'Sullivan, S T

2017-04-01

Aesthetic plastic surgery is a consumer-driven industry, subject to influence by financial forces. A changing economic environment may thus impact on the demand for surgery. The aim of this study was to explore trends in demand for bilateral breast augmentation (BBA) in consecutively presenting patients over an 11-year period and to examine if a correlation exists between these trends and changes in Gross Domestic Product (GDP), a key economic indicator. This study revealed a correlation between annual number of breast augmentation procedures performed and GDP values (r 2  = 0.34, p value = 0.059). Additionally, predicted number of BBA procedures, based on predicted GDP growth in Ireland, strongly correlated with actual number of BBA performed (r 2  = 0.93, p value = 0.000001). Predicted GDP growth can potentially forecast future demand for BBA in our cohort allowing plastic surgeons to modify their practice accordingly. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

The Changing Science of Urban Transportation Planning

NASA Astrophysics Data System (ADS)

Kloster, Tom

2010-03-01

The last half of the 20th Century was the age of the automobile, and the development of bigger and faster roads defined urban planning for more than 50 years. During this period, transportation planners developed sophisticated behavior models to help predict future travel patterns in an attempt to keep pace with ever-growing congestion and public demand for more roads. By the 1990s, however, it was clear that eliminating congestion with new road capacity was an unattainable outcome, and had unintended effects that were never considered when the automobile era first emerged. Today, public expectations are rapidly evolving beyond ``building our way out'' of congestion, and toward more complex definitions of desired outcomes in transportation planning. In this new century, planners must improve behavior models to predict not only the travel patterns of the future, but also the subsequent environmental, social and public health effects associated with growth and changes in travel behavior, and provide alternative transportation solutions that respond to these broader outcomes.

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.

Ecological investigations: vegetation studies, preliminary findings

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

Olgeirson, E.R.; Martin, R.B.

1978-09-01

The objective of the vegetation studies conducted on the research site is to produce a descriptive data base that can be applied to determinations of carrying capacity of the site and surrounding area. Additional information obtained about parameters that influence vegetation growth and maintenance of soil nutrients, and moisture and temperature regimes help define dynamic relationships that must be understood to effect successful revegetation and habitat rehabilitation. The descriptive vegetation baseline also provides a point of departure for design of future monitoring programs, and predictive models and strategies to be used in dealing with impact mitigation; in turn, monitoring programsmore » and predictive modeling form the bases for making distinctions between natural trends and man-induced perturbations.« less

The ethics of the Texas death penalty and its impact on a prolonged appeals process.

PubMed

Pearlman, T

1998-01-01

Society remains sharply divided as to the deterrent value of capital punishment. Following the reintroduction of the death penalty in the United States, Texas law mandates the affirmative predictability of future dangerousness beyond a reasonable doubt before a jury can impose the ultimate penalty for capital murder. The validity of prediction of dangerousness has been challenged in three Texas landmark cases before the U.S. Supreme Court. The case of Karla Faye Tucker highlights the moral controversy that occurs when execution follows an appeals process stretching over more than a decade, during which time personality growth and the effects of prison rehabilitation may have eliminated or curbed criminal tendencies.

Overgeneral autobiographical memory predicts changes in depression in a community sample.

PubMed

Van Daele, Tom; Griffith, James W; Van den Bergh, Omer; Hermans, Dirk

2014-01-01

This study investigated whether overgeneral autobiographical memory (OGM) predicts the course of symptoms of depression and anxiety in a community sample, after 5, 6, 12 and 18 months. Participants (N=156) completed the Autobiographical Memory Test and the Depression Anxiety Stress Scales-21 (DASS-21) at baseline and were subsequently reassessed using the DASS-21 at four time points over a period of 18 months. Using latent growth curve modelling, we found that OGM was associated with a linear increase in depression. We were unable to detect changes over time in anxiety. OGM may be an important marker to identify people at risk for depression in the future, but more research is needed with anxiety.

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.

Can Perceptuo-Motor Skills Assessment Outcomes in Young Table Tennis Players (7–11 years) Predict Future Competition Participation and Performance? An Observational Prospective Study

PubMed Central

2016-01-01

Forecasting future performance in youth table tennis players based on current performance is complex due to, among other things, differences between youth players in growth, development, maturity, context and table tennis experience. Talent development programmes might benefit from an assessment of underlying perceptuo-motor skills for table tennis, which is hypothesized to determine the players’ potential concerning the perceptuo-motor domain. The Dutch perceptuo-motor skills assessment intends to measure the perceptuo-motor potential for table tennis in youth players by assessing the underlying skills crucial for developing technical and tactical qualities. Untrained perceptuo-motor tasks are used as these are suggested to represent a player’s future potential better than specific sport skills themselves as the latter depend on exposure to the sport itself. This study evaluated the value of the perceptuo-motor skills assessment for a talent developmental programme by evaluating its predictive validity for competition participation and performance in 48 young table tennis players (7–11 years). Players were tested on their perceptuo-motor skills once during a regional talent day, and the subsequent competition results were recorded half-yearly over a period of 2.5 years. Logistic regression analysis showed that test scores did not predict future competition participation (p >0.05). Yet, the Generalized Estimating Equations analysis, including the test items ‘aiming at target’, ‘throwing a ball’, and ‘eye-hand coordination’ in the best fitting model, revealed that the outcomes of the perceptuo-motor skills assessment were significant predictors for future competition results (R2 = 51%). Since the test age influences the perceptuo-motor skills assessment’s outcome, another multivariable model was proposed including test age as a covariate (R2 = 53%). This evaluation demonstrates promising prospects for the perceptuo-motor skills assessment to be included in a talent development programme. Future studies are needed to clarify the predictive value in a larger sample of youth competition players over a longer period in time. PMID:26863212

Growth form-dependent response to physical disturbance and thermal stress in Acropora corals

NASA Astrophysics Data System (ADS)

Muko, S.; Arakaki, S.; Nagao, M.; Sakai, Kazuhiko

2013-03-01

To predict the community structure in response to changing environmental conditions, it is necessary to know the species-specific reaction and relative impact strength of each disturbance. We investigated the coral communities in two sites, an exposed and a protected site, at Iriomote Island, Japan, from 2005 to 2008. During the study period, a cyclone and thermal stress were observed. All Acropora colonies, classified into four morphologies (arborescent, tabular, corymbose, and digitate), were identified and tracked through time to calculate the annual mortality and growth rate. The mortality of all Acropora colonies in the protected site was lower than that in the exposed site during the period without disturbances. Extremely higher mortality due to bleaching was observed in tabular and corymbose Acropora, compared to other growth forms, at the protected sites after thermal stress. In contrast, physical disturbance by a tropical cyclone induced the highest mortality in arborescent and digitate corals at the exposed site. Moreover, arborescent corals exhibited a remarkable decline 1 year after the tropical cyclone at the exposed site. The growth of colonies that survived coral bleaching did not decrease in the following year compared to previous year for all growth forms, but the growth of arborescent and tabular remnant corals at the exposed site declined severely after the tropical cyclone compared to previous year. The delayed mortality and lowered growth rate after the tropical cyclone were probably due to the damage caused by the tropical cyclone. These results indicate that the cyclone had a greater impact on fragile corals than expected. This study provides useful information for the evaluation of Acropora coral response to progressing global warming conditions, which are predicted to increase in frequency and intensity in the near future.

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,

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

Facing the Future: Effects of Short-Term Climate Extremes on Isoprene-Emitting and Nonemitting Poplar.

PubMed

Vanzo, Elisa; Jud, Werner; Li, Ziru; Albert, Andreas; Domagalska, Malgorzata A; Ghirardo, Andrea; Niederbacher, Bishu; Frenzel, Juliane; Beemster, Gerrit T S; Asard, Han; Rennenberg, Heinz; Sharkey, Thomas D; Hansel, Armin; Schnitzler, Jörg-Peter

2015-09-01

Isoprene emissions from poplar (Populus spp.) plantations can influence atmospheric chemistry and regional climate. These emissions respond strongly to temperature, [CO2], and drought, but the superimposed effect of these three climate change factors are, for the most part, unknown. Performing predicted climate change scenario simulations (periodic and chronic heat and drought spells [HDSs] applied under elevated [CO2]), we analyzed volatile organic compound emissions, photosynthetic performance, leaf growth, and overall carbon (C) gain of poplar genotypes emitting (IE) and nonemitting (NE) isoprene. We aimed (1) to evaluate the proposed beneficial effect of isoprene emission on plant stress mitigation and recovery capacity and (2) to estimate the cumulative net C gain under the projected future climate. During HDSs, the chloroplastidic electron transport rate of NE plants became impaired, while IE plants maintained high values similar to unstressed controls. During recovery from HDS episodes, IE plants reached higher daily net CO2 assimilation rates compared with NE genotypes. Irrespective of the genotype, plants undergoing chronic HDSs showed the lowest cumulative C gain. Under control conditions simulating ambient [CO2], the C gain was lower in the IE plants than in the NE plants. In summary, the data on the overall C gain and plant growth suggest that the beneficial function of isoprene emission in poplar might be of minor importance to mitigate predicted short-term climate extremes under elevated [CO2]. Moreover, we demonstrate that an analysis of the canopy-scale dynamics of isoprene emission and photosynthetic performance under multiple stresses is essential to understand the overall performance under proposed future conditions. © 2015 American Society of Plant Biologists. All Rights Reserved.

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.

Forecasting Impacts of Climate Change on Indicators of British Columbia's Biodiversity

NASA Astrophysics Data System (ADS)

Holmes, Keith Richard

Understanding the relationships between biodiversity and climate is essential for predicting the impact of climate change on broad-scale landscape processes. Utilizing indirect indicators of biodiversity derived from remotely sensed imagery, we present an approach to forecast shifts in the spatial distribution of biodiversity. Indirect indicators, such as remotely sensed plant productivity metrics, representing landscape seasonality, minimum growth, and total greenness have been linked to species richness over broad spatial scales, providing unique capacity for biodiversity modeling. Our goal is to map future spatial distributions of plant productivity metrics based on expected climate change and to quantify anticipated change to park habitat in British Columbia. Using an archival dataset sourced from the Advanced Very High Resolution Radiometer (AVHRR) satellite from the years 1987 to 2007 at 1km spatial resolution, corresponding historical climate data, and regression tree modeling, we developed regional models of the relationships between climate and annual productivity growth. Historical interconnections between climate and annual productivity were coupled with three climate change scenarios modeled by the Canadian Centre for Climate Modeling and Analysis (CCCma) to predict and map productivity components to the year 2065. Results indicate we can expect a warmer and wetter environment, which may lead to increased productivity in the north and higher elevations. Overall, seasonality is expected to decrease and greenness productivity metrics are expected to increase. The Coastal Mountains and high elevation edge habitats across British Columbia are forecasted to experience the greatest amount of change. In the future, protected areas may have potential higher greenness and lower seasonality as represented by indirect biodiversity indicators. The predictive model highlights potential gaps in protection along the central interior and Rocky Mountains. Protected areas are expected to experience the greatest change with indirect indicators located along mountainous elevations of British Columbia. Our indirect indicator approach to predict change in biodiversity provides resource managers with information to mitigate and adapt to future habitat dynamics. Spatially specific recommendations from our dataset provide information necessary for management. For instance, knowing there is a projected depletion of habitat representation in the East Rocky Mountains, sensitive species in the threatened Mountain Hemlock ecozone, or preservation of rare habitats in the decreasing greenness of the southern interior region is essential information for managers tasked with long term biodiversity conservation. Forecasting productivity levels, linked to the distribution of species richness, presents a novel approach for understanding the future implications of climate change on broad scale biodiversity.

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

Campbell, J. E.; Berry, J. A.; Seibt, U.

Growth in terrestrial gross primary production (GPP) may provide a feedback for climate change, but there is still strong disagreement on the extent to which biogeochemical processes may suppress this GPP growth at the ecosystem to continental scales. The consequent uncertainty in modeling of future carbon storage by the terrestrial biosphere constitutes one of the largest unknowns in global climate projections for the next century. Here we provide a global, measurement-based estimate of historical GPP growth using long-term atmospheric carbonyl sulfide (COS) records derived from ice core, firn, and ambient air samples. We interpret these records using a model thatmore » relates changes in the COS concentration to changes in its sources and sinks, the largest of which is proportional to GPP. The COS history was most consistent with simulations that assume a large historical GPP growth. Carbon-climate models that assume little to no GPP growth predicted trajectories of COS concentration over the anthropogenic era that differ from those observed. Continued COS monitoring may be useful for detecting ongoing changes in GPP while extending the ice core record to glacial cycles could provide further opportunities to evaluate earth system models.« less

Model parameter-related optimal perturbations and their contributions to El Niño prediction errors

NASA Astrophysics Data System (ADS)

Tao, Ling-Jiang; Gao, Chuan; Zhang, Rong-Hua

2018-04-01

Errors in initial conditions and model parameters (MPs) are the main sources that limit the accuracy of ENSO predictions. In addition to exploring the initial error-induced prediction errors, model errors are equally important in determining prediction performance. In this paper, the MP-related optimal errors that can cause prominent error growth in ENSO predictions are investigated using an intermediate coupled model (ICM) and a conditional nonlinear optimal perturbation (CNOP) approach. Two MPs related to the Bjerknes feedback are considered in the CNOP analysis: one involves the SST-surface wind coupling ({α _τ } ), and the other involves the thermocline effect on the SST ({α _{Te}} ). The MP-related optimal perturbations (denoted as CNOP-P) are found uniformly positive and restrained in a small region: the {α _τ } component is mainly concentrated in the central equatorial Pacific, and the {α _{Te}} component is mainly located in the eastern cold tongue region. This kind of CNOP-P enhances the strength of the Bjerknes feedback and induces an El Niño- or La Niña-like error evolution, resulting in an El Niño-like systematic bias in this model. The CNOP-P is also found to play a role in the spring predictability barrier (SPB) for ENSO predictions. Evidently, such error growth is primarily attributed to MP errors in small areas based on the localized distribution of CNOP-P. Further sensitivity experiments firmly indicate that ENSO simulations are sensitive to the representation of SST-surface wind coupling in the central Pacific and to the thermocline effect in the eastern Pacific in the ICM. These results provide guidance and theoretical support for the future improvement in numerical models to reduce the systematic bias and SPB phenomenon in ENSO predictions.

Consequences of genetic change in farm animals on food intake and feeding behaviour.

PubMed

Emmans, G; Kyriazakis, I

2001-02-01

Selection in commercial populations on aspects of output, such as for growth rate in poultry. against fatness and for growth rate in pigs, and for milk yield in cows, has had very barge effects on such outputs over the past 50 years. Partly because of the cost of recording intake, there has been little or no selection for food intake or feeding behaviour. In order to predict the effects of such past, and future, selection on intake it is necessary to have some suitable theoretical framework. Intake needs to be predicted in order to make rational feeding and environmental decisions. The idea that an animal will eat 'to meet its requirements' has proved useful and continues to be fruitful. An important part of the idea is that the animal (genotype) can be described in a way that is sufficient for the accurate prediction of its outputs over time. Such descriptions can be combined with a set of nutritional constants to calculate requirements. There appears to have been no change in the nutritional constants under selection for output. Under such selection it is simplest to assume that changes in intake follow from the changes in output rates, so that intake changes become entirely predictable. It is suggested that other ways that have been proposed for predicting intake cannot be successful in predicting the effects of selection. Feeding behaviour is seen as being the means that the animal uses to attain its intake rather than being the means by which that intake can be predicted. Thus, the organisation of feeding behaviour can be used to predict neither intake nor the effects of selection on it.

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

The Predicted Growth of the Low Earth Orbit Space Debris Environment: An Assessment of Future Risk for Spacecraft

NASA Technical Reports Server (NTRS)

Krisko, Paula H.

2007-01-01

Space debris is a worldwide-recognized issue concerning the safety of commercial, military, and exploration spacecraft. The space debris environment includes both naturally occuring meteoroids and objects in Earth orbit that are generated by human activity, termed orbital debris. Space agencies around the world are addressing the dangers of debris collisions to both crewed and robotic spacecraft. In the United States, the Orbital Debris Program Office at the NASA Johnson Space Center leads the effort to categorize debris, predict its growth, and formulate mitigation policy for the environment from low Earth orbit (LEO) through geosynchronous orbit (GEO). This paper presents recent results derived from the NASA long-term debris environment model, LEGEND. It includes the revised NASA sodium potassium droplet model, newly corrected for a factor of two over-estimation of the droplet population. The study indicates a LEO environment that is already highly collisionally active among orbital debris larger than 1 cm in size. Most of the modeled collision events are non-catastrophic (i.e., They lead to a cratering of the target, but no large scale fragmentation.). But they are potentially mission-ending, and take place between impactors smaller than 10 cm and targets larger than 10 cm. Given the small size of the impactor these events would likely be undetectable by present-day measurement means. The activity continues into the future as would be expected. Impact rates of about four per year are predicted by the current study within the next 30 years, with the majority of targets being abandoned intacts (spent upper stages and spacecraft). Still, operational spacecraft do show a small collisional activity, one that increases over time as the small fragment population increases.

Transition Models for Engineering Calculations

NASA Technical Reports Server (NTRS)

Fraser, C. J.

2007-01-01

While future theoretical and conceptual developments may promote a better understanding of the physical processes involved in the latter stages of boundary layer transition, the designers of rotodynamic machinery and other fluid dynamic devices need effective transition models now. This presentation will therefore center around the development of of some transition models which have been developed as design aids to improve the prediction codes used in the performance evaluation of gas turbine blading. All models are based on Narasimba's concentrated breakdown and spot growth.

Nuclear option

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

Olson, P.S.

The energy demand complexion of this country is always changing and promises to change in the future. The nuclear industry is responding to changing energy demands through standards writing activities. Since the oil embargo of 1973, there has been a change in the mix of fuels contributing to energy growth in this country; virtually all of the energy growth has come from coal and nuclear power. The predicted expansion of coal use by 1985, over 1977 level, is 37%, while the use of oil is expected to decline by 17%. Use of nuclear power is expected to increase 62% frommore » the 1977 level. The feasibility of using nuclear energy to meet the needs of the USA for electric power is discussed.« less

Markov Modeling of Component Fault Growth over a Derived Domain of Feasible Output Control Effort Modifications

NASA Technical Reports Server (NTRS)

Bole, Brian; Goebel, Kai; Vachtsevanos, George

2012-01-01

This paper introduces a novel Markov process formulation of stochastic fault growth modeling, in order to facilitate the development and analysis of prognostics-based control adaptation. A metric representing the relative deviation between the nominal output of a system and the net output that is actually enacted by an implemented prognostics-based control routine, will be used to define the action space of the formulated Markov process. The state space of the Markov process will be defined in terms of an abstracted metric representing the relative health remaining in each of the system s components. The proposed formulation of component fault dynamics will conveniently relate feasible system output performance modifications to predictions of future component health deterioration.

Future methane emissions from the heavy-duty natural gas transportation sector for stasis, high, medium, and low scenarios in 2035.

PubMed

Clark, Nigel N; Johnson, Derek R; McKain, David L; Wayne, W Scott; Li, Hailin; Rudek, Joseph; Mongold, Ronald A; Sandoval, Cesar; Covington, April N; Hailer, John T

2017-12-01

Today's heavy-duty natural gas-fueled fleet is estimated to represent less than 2% of the total fleet. However, over the next couple of decades, predictions are that the percentage could grow to represent as much as 50%. Although fueling switching to natural gas could provide a climate benefit relative to diesel fuel, the potential for emissions of methane (a potent greenhouse gas) from natural gas-fueled vehicles has been identified as a concern. Since today's heavy-duty natural gas-fueled fleet penetration is low, today's total fleet-wide emissions will be also be low regardless of per vehicle emissions. However, predicted growth could result in a significant quantity of methane emissions. To evaluate this potential and identify effective options for minimizing emissions, future growth scenarios of heavy-duty natural gas-fueled vehicles, and compressed natural gas and liquefied natural gas fueling stations that serve them, have been developed for 2035, when the populations could be significant. The scenarios rely on the most recent measurement campaign of the latest manufactured technology, equipment, and vehicles reported in a companion paper as well as projections of technology and practice advances. These "pump-to-wheels"(PTW) projections do not include methane emissions outside of the bounds of the vehicles and fuel stations themselves and should not be confused with a complete wells-to-wheels analysis. Stasis, high, medium, and low scenario PTW emissions projections for 2035 were 1.32%, 0.67%, 0.33%, and 0.15% of the fuel used. The scenarios highlight that a large emissions reductions could be realized with closed crankcase operation, improved best practices, and implementation of vent mitigation technologies. Recognition of the potential pathways for emissions reductions could further enhance the heavy-duty transportation sectors ability to reduce carbon emissions. Newly collected pump-to-wheels methane emissions data for current natural gas technologies were combined with future market growth scenarios, estimated technology advancements, and best practices to examine the climate benefit of future fuel switching. The analysis indicates the necessary targets of efficiency, methane emissions, market penetration, and best practices necessary to enable a pathway for natural gas to reduce the carbon intensity of the heavy-duty transportation sector.

Future Climate Prediction of Urban Atmosphere in A Tropical Megacity: Utilization of RCP/SSP Scenarios with an Urban Growth Model

NASA Astrophysics Data System (ADS)

Darmanto, N. S.; Varquez, A. C. G.; Kanda, M.; Takakuwa, S.

2016-12-01

Economic development in Southeast Asia megacities leads to rapid transformation into more complicated urban configurations. These configurations, including building geometry, enhance aerodynamic drag thus reducing near-surface wind speeds. Roughness parameters representing building geometry, along with anthropogenic heat emissions, contribute to the formation of urban heat islands (UHI). All these have been reproduced successfully in the Weather Research and Forecasting (WRF) Model coupled with an improved single-layer urban canopy model incorporating a realistic distribution of urban parameters and anthropogenic heat emission in the Jakarta Greater Area. We apply this technology to climate change studies by introducing future urbanization defined by urban sprawl, vertical rise in buildings, and increase anthropogenic heat emission (AHE) due to population changes, into futuristic climate modelling. To simulate 2050s future climate, pseudo-global warming method was used which relied on current and ensembles of 5 CMIP5 GCMs for 2 representative concentration pathways (RCP), 2.6 and 8.5. To determine future urbanization level, 2050 population growth and energy consumption were estimated from shared socioeconomic pathways (SSP). This allows the estimation of future urban sprawl, building geometry, and AHE using the SLEUTH urban growth model and spatial growth assumptions. Two cases representing combinations of RCP and SSP were simulated in WRF: RCP2.6-SSP1 and RCP8.5-SSP3. Each case corresponds to best and worst-case scenarios of implementing adaptation and mitigation strategies, respectively. It was found that 2-m temperature of Jakarta will increase by 0.62°C (RCP2.6) and 1.44°C (RCP8.5) solely from background climate change; almost on the same magnitude as the background temperature increase of RCP2.6 (0.5°C) and RCP8.5 (1.2°C). Compared with previous studies, the result indicates that the effect of climate change on UHI in tropical cities may be lesser than cities located in the mid-latitudes. However, it is expected that the combined effect of urbanization and climate change will result to significant changes on future urban temperature. ACK: This research was supported by the Environment Research and Technology Development Fund (S-14) of the Ministry of the Environment, Japan.

Elevations in growth hormone and glucagon-like peptide-2 levels on admission are associated with increased mortality in trauma patients

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

Rowan, Matthew P.; Beckman, Darrick J.; Rizzo, Julie A.

Burn and trauma patients present a clinical challenge due to metabolic derangements and hypermetabolism that result in a prolonged catabolic state with impaired healing and secondary complications, including ventilator dependence. Previous work has shown that circulating levels of growth hormone (GH) are predictive of mortality in critically ill adults, but few studies have examined the prognostic potential of GH levels in adult trauma patients. Here, our objective is to investigate the utility of GH and other endocrine responses in the prediction of outcomes, we conducted a prospective, observational study of adult burn and trauma patients. We evaluated the serum concentrationmore » of GH, insulin-like growth factor 1 (IGF-1), IGF binding protein 3 (IGFBP-3), and glucagon-like peptide-2 (GLP-2) weekly for up to 6 weeks in 36 adult burn and trauma patients admitted between 2010 and 2013. As a result, non-survivors had significantly higher levels of GH and GLP-2 on admission than survivors. This study demonstrates that GH has potential as a predictor of mortality in critically ill trauma and burn patients. Future studies will focus on not only the role of GH, but also GLP-2, which was shown to correlate with mortality in this study with a goal of offering early, targeted therapeutic interventions aimed at decreasing mortality in the critically injured. GH and GLP-2 may have clinical utility for outcome prediction in adult trauma patients.« less

Elevations in growth hormone and glucagon-like peptide-2 levels on admission are associated with increased mortality in trauma patients

DOE PAGES

Rowan, Matthew P.; Beckman, Darrick J.; Rizzo, Julie A.; ...

2016-10-04

Burn and trauma patients present a clinical challenge due to metabolic derangements and hypermetabolism that result in a prolonged catabolic state with impaired healing and secondary complications, including ventilator dependence. Previous work has shown that circulating levels of growth hormone (GH) are predictive of mortality in critically ill adults, but few studies have examined the prognostic potential of GH levels in adult trauma patients. Here, our objective is to investigate the utility of GH and other endocrine responses in the prediction of outcomes, we conducted a prospective, observational study of adult burn and trauma patients. We evaluated the serum concentrationmore » of GH, insulin-like growth factor 1 (IGF-1), IGF binding protein 3 (IGFBP-3), and glucagon-like peptide-2 (GLP-2) weekly for up to 6 weeks in 36 adult burn and trauma patients admitted between 2010 and 2013. As a result, non-survivors had significantly higher levels of GH and GLP-2 on admission than survivors. This study demonstrates that GH has potential as a predictor of mortality in critically ill trauma and burn patients. Future studies will focus on not only the role of GH, but also GLP-2, which was shown to correlate with mortality in this study with a goal of offering early, targeted therapeutic interventions aimed at decreasing mortality in the critically injured. GH and GLP-2 may have clinical utility for outcome prediction in adult trauma patients.« less

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.

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

Remote Sensing and Spatial Growth Modeling Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Khan, Maudood

2006-01-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how ozone and air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.

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.

Detecting trends in academic research from a citation network using network representation learning

PubMed Central

Mori, Junichiro; Ochi, Masanao; Sakata, Ichiro

2018-01-01

Several network features and information retrieval methods have been proposed to elucidate the structure of citation networks and to detect important nodes. However, it is difficult to retrieve information related to trends in an academic field and to detect cutting-edge areas from the citation network. In this paper, we propose a novel framework that detects the trend as the growth direction of a citation network using network representation learning(NRL). We presume that the linear growth of citation network in latent space obtained by NRL is the result of the iterative edge additional process of a citation network. On APS datasets and papers of some domains of the Web of Science, we confirm the existence of trends by observing that an academic field grows in a specific direction linearly in latent space. Next, we calculate each node’s degree of trend-following as an indicator called the intrinsic publication year (IPY). As a result, there is a correlation between the indicator and the number of future citations. Furthermore, a word frequently used in the abstracts of cutting-edge papers (high-IPY paper) is likely to be used often in future publications. These results confirm the validity of the detected trend for predicting citation network growth. PMID:29782521

New insights from coral growth band studies in an era of rapid environmental change

NASA Astrophysics Data System (ADS)

Lough, Janice M.; Cooper, Timothy F.

2011-10-01

The rapid formation of calcium carbonate coral skeletons (calcification) fuelled by the coral-algal symbiosis is the backbone of tropical coral reef ecosystems. However, the efficacy of calcification is measurably influenced by the sea's physico-chemical environment, which is changing rapidly. Warming oceans have already led to increased frequency and severity of coral bleaching, and ocean acidification has a demonstrable potential to cause reduced rates of calcification. There is now general agreement that ocean warming and acidification are attributable to human activities increasing greenhouse gas concentrations in the atmosphere, and the large part of the extra carbon dioxide (the main greenhouse gas) that is absorbed by oceans. Certain massive corals provide historical perspectives on calcification through the presence of dateable annual density banding patterns. Each band is a page in an environmental archive that reveals past responses of growth (linear extension, skeletal density and calcification rate) and provides a basis for prediction of future of coral growth. A second major line of research focuses on the measurement of various geochemical tracers incorporated into the growth bands, allowing the reconstruction of past marine climate conditions (i.e. palaeoclimatology). Here, we focus on the structural properties of the annual density bands themselves (viz. density; linear extension), exploring their utility in providing both perspectives on the past and pointers to the future of calcification on coral reefs. We conclude that these types of coral growth records, though relatively neglected in recent years compared to the geochemical studies, remain immensely valuable aids to unravelling the consequences of anthropogenic climate change on coral reefs. Moreover, an understanding of coral growth processes is an essential pre-requisite for proper interpretation of studies of geochemical tracers in corals.

[Fast Detection of Camellia Sinensis Growth Process and Tea Quality Informations with Spectral Technology: A Review].

PubMed

Peng, Ji-yu; Song, Xing-lin; Liu, Fei; Bao, Yi-dan; He, Yong

2016-03-01

The research achievements and trends of spectral technology in fast detection of Camellia sinensis growth process information and tea quality information were being reviewed. Spectral technology is a kind of fast, nondestructive, efficient detection technology, which mainly contains infrared spectroscopy, fluorescence spectroscopy, Raman spectroscopy and mass spectroscopy. The rapid detection of Camellia sinensis growth process information and tea quality is helpful to realize the informatization and automation of tea production and ensure the tea quality and safety. This paper provides a review on its applications containing the detection of tea (Camellia sinensis) growing status(nitrogen, chlorophyll, diseases and insect pest), the discrimination of tea varieties, the grade discrimination of tea, the detection of tea internal quality (catechins, total polyphenols, caffeine, amino acid, pesticide residual and so on), the quality evaluation of tea beverage and tea by-product, the machinery of tea quality determination and discrimination. This paper briefly introduces the trends of the technology of the determination of tea growth process information, sensor and industrial application. In conclusion, spectral technology showed high potential to detect Camellia sinensis growth process information, to predict tea internal quality and to classify tea varieties and grades. Suitable chemometrics and preprocessing methods is helpful to improve the performance of the model and get rid of redundancy, which provides the possibility to develop the portable machinery. Future work is to develop the portable machinery and on-line detection system is recommended to improve the further application. The application and research achievement of spectral technology concerning about tea were outlined in this paper for the first time, which contained Camellia sinensis growth, tea production, the quality and safety of tea and by-produce and so on, as well as some problems to be solved and its future applicability in modern tea industrial.

Prediction of individual response to anticancer therapy: historical and future perspectives.

PubMed

Unger, Florian T; Witte, Irene; David, Kerstin A

2015-02-01

Since the introduction of chemotherapy for cancer treatment in the early 20th century considerable efforts have been made to maximize drug efficiency and at the same time minimize side effects. As there is a great interpatient variability in response to chemotherapy, the development of predictive biomarkers is an ambitious aim for the rapidly growing research area of personalized molecular medicine. The individual prediction of response will improve treatment and thus increase survival and life quality of patients. In the past, cell cultures were used as in vitro models to predict in vivo response to chemotherapy. Several in vitro chemosensitivity assays served as tools to measure miscellaneous endpoints such as DNA damage, apoptosis and cytotoxicity or growth inhibition. Twenty years ago, the development of high-throughput technologies, e.g. cDNA microarrays enabled a more detailed analysis of drug responses. Thousands of genes were screened and expression levels were correlated to drug responses. In addition, mutation analysis became more and more important for the prediction of therapeutic success. Today, as research enters the area of -omics technologies, identification of signaling pathways is a tool to understand molecular mechanism underlying drug resistance. Combining new tissue models, e.g. 3D organoid cultures with modern technologies for biomarker discovery will offer new opportunities to identify new drug targets and in parallel predict individual responses to anticancer therapy. In this review, we present different currently used chemosensitivity assays including 2D and 3D cell culture models and several -omics approaches for the discovery of predictive biomarkers. Furthermore, we discuss the potential of these assays and biomarkers to predict the clinical outcome of individual patients and future perspectives.

Validating growth and development of a seabird as an indicator of food availability: captive-reared Caspian Tern chicks fed ad libitum and restricted diets

USGS Publications Warehouse

Lyons, Donald E.; Roby, Daniel D.

2011-01-01

For seabirds raising young under conditions of limited food availability, reducing chick provisioning and chick growth rates are the primary means available to avoid abandonment of a breeding effort. For most seabirds, however, baseline data characterizing chick growth and development under known feeding conditions are unavailable, so it is difficult to evaluate chick nutritional status as it relates to foraging conditions near breeding colonies. To address this need, we examined the growth and development of young Caspian Terns (Hydroprogne caspia), a cosmopolitan, generalist piscivore, reared in captivity and fed ad libitum and restricted (ca. one-third lower caloric intake) diets. Ad libitum-fed chicks grew at similar rates and achieved a similar size at fledging as previously documented for chicks in the wild and had energetic demands that closely matched allometric predictions. We identified three general characteristics of food-restricted Caspian Tern chicks compared to ad libitum chicks: (1) lower age-specific body mass, (2) lower age-specific skeletal and feather size, such as wing chord length, and (3) heightened levels of corticosterone in blood, both for baseline levels and in response to acute stress. Effects of diet restriction on feather growth (10-11% slower growth in diet-restricted chicks) were less pronounced than effects on structural growth (37-52% slower growth) and body mass (24% lower at fledging age), apparently due to preferential allocation of food resources to maintain plumage growth. Our results suggest that measurements of chick body mass and feather development (e.g., wing chord or primary length) or measurement of corticosterone levels in the blood would allow useful evaluation of the nutritional status of chicks reared in the wild and of food availability in the foraging range of adults. Such evaluations could also inform demography studies (e.g., predict future recruitment) and assist in evaluating designated piscivorous waterbird conservation (colony) sites. ?? 2011 The Authors. Journal of Field Ornithology ?? 2011 Association of Field Ornithologists.

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

Dynamical system analysis of interacting models

NASA Astrophysics Data System (ADS)

Carneiro, S.; Borges, H. A.

2018-01-01

We perform a dynamical system analysis of a cosmological model with linear dependence between the vacuum density and the Hubble parameter, with constant-rate creation of dark matter. We show that the de Sitter spacetime is an asymptotically stable critical point, future limit of any expanding solution. Our analysis also shows that the Minkowski spacetime is an unstable critical point, which eventually collapses to a singularity. In this way, such a prescription for the vacuum decay not only predicts the correct future de Sitter limit, but also forbids the existence of a stable Minkowski universe. We also study the effect of matter creation on the growth of structures and their peculiar velocities, showing that it is inside the current errors of redshift space distortions observations.

Fire risk in San Diego County, California: A weighted Bayesian model approach

USGS Publications Warehouse

Kolden, Crystal A.; Weigel, Timothy J.

2007-01-01

Fire risk models are widely utilized to mitigate wildfire hazards, but models are often based on expert opinions of less understood fire-ignition and spread processes. In this study, we used an empirically derived weights-of-evidence model to assess what factors produce fire ignitions east of San Diego, California. We created and validated a dynamic model of fire-ignition risk based on land characteristics and existing fire-ignition history data, and predicted ignition risk for a future urbanization scenario. We then combined our empirical ignition-risk model with a fuzzy fire behavior-risk model developed by wildfire experts to create a hybrid model of overall fire risk. We found that roads influence fire ignitions and that future growth will increase risk in new rural development areas. We conclude that empirically derived risk models and hybrid models offer an alternative method to assess current and future fire risk based on management actions.

Nanotoxicity prediction using computational modelling - review and future directions

NASA Astrophysics Data System (ADS)

Saini, Bhavna; Srivastava, Sumit

2018-04-01

Nanomaterials has stimulated various outlooks for future in a number of industries and scientific ventures. A number of applications such as cosmetics, medicines, and electronics are employing nanomaterials due to their various compelling properties. The unending growth of nanomaterials usage in our daily life has escalated the health and environmental risks. Early nanotoxicity recognition is a big challenge. Various researches are going on in the field of nanotoxicity, which comprised of several problems such as inadequacy of proper datasets, lack of appropriate rules and characterization of nanomaterials. Computational modelling would be beneficial asset for nanomaterials researchers because it can foresee the toxicity, rest on previous experimental data. In this study, we have reviewed sufficient work demonstrating a proper pathway to proceed with QSAR analysis of Nanomaterials for toxicity modelling. The paper aims at providing comprehensive insight of Nano QSAR, various theories, tools and approaches used, along with an outline for future research directions to work on.

Predicting Future Reading Problems Based on Pre-reading Auditory Measures: A Longitudinal Study of Children with a Familial Risk of Dyslexia

PubMed Central

Law, Jeremy M.; Vandermosten, Maaike; Ghesquière, Pol; Wouters, Jan

2017-01-01

Purpose: This longitudinal study examines measures of temporal auditory processing in pre-reading children with a family risk of dyslexia. Specifically, it attempts to ascertain whether pre-reading auditory processing, speech perception, and phonological awareness (PA) reliably predict later literacy achievement. Additionally, this study retrospectively examines the presence of pre-reading auditory processing, speech perception, and PA impairments in children later found to be literacy impaired. Method: Forty-four pre-reading children with and without a family risk of dyslexia were assessed at three time points (kindergarten, first, and second grade). Auditory processing measures of rise time (RT) discrimination and frequency modulation (FM) along with speech perception, PA, and various literacy tasks were assessed. Results: Kindergarten RT uniquely contributed to growth in literacy in grades one and two, even after controlling for letter knowledge and PA. Highly significant concurrent and predictive correlations were observed with kindergarten RT significantly predicting first grade PA. Retrospective analysis demonstrated atypical performance in RT and PA at all three time points in children who later developed literacy impairments. Conclusions: Although significant, kindergarten auditory processing contributions to later literacy growth lack the power to be considered as a single-cause predictor; thus results support temporal processing deficits' contribution within a multiple deficit model of dyslexia. PMID:28223953

Probabilistic fatigue life prediction of metallic and composite materials

NASA Astrophysics Data System (ADS)

Xiang, Yibing

Fatigue is one of the most common failure modes for engineering structures, such as aircrafts, rotorcrafts and aviation transports. Both metallic materials and composite materials are widely used and affected by fatigue damage. Huge uncertainties arise from material properties, measurement noise, imperfect models, future anticipated loads and environmental conditions. These uncertainties are critical issues for accurate remaining useful life (RUL) prediction for engineering structures in service. Probabilistic fatigue prognosis considering various uncertainties is of great importance for structural safety. The objective of this study is to develop probabilistic fatigue life prediction models for metallic materials and composite materials. A fatigue model based on crack growth analysis and equivalent initial flaw size concept is proposed for metallic materials. Following this, the developed model is extended to include structural geometry effects (notch effect), environmental effects (corroded specimens) and manufacturing effects (shot peening effects). Due to the inhomogeneity and anisotropy, the fatigue model suitable for metallic materials cannot be directly applied to composite materials. A composite fatigue model life prediction is proposed based on a mixed-mode delamination growth model and a stiffness degradation law. After the development of deterministic fatigue models of metallic and composite materials, a general probabilistic life prediction methodology is developed. The proposed methodology combines an efficient Inverse First-Order Reliability Method (IFORM) for the uncertainty propogation in fatigue life prediction. An equivalent stresstransformation has been developed to enhance the computational efficiency under realistic random amplitude loading. A systematical reliability-based maintenance optimization framework is proposed for fatigue risk management and mitigation of engineering structures.

Developing a Long-Term Forest Gap Model to Predict the Behavior of California Pines, Oaks, and Cedars Under Climate Change and Other Disturbance Scenarios

NASA Astrophysics Data System (ADS)

Davis, S. L.; Moran, E.

2015-12-01

Many predictions about how trees will respond to climate change have been made, but these often rely on extrapolating into the future one of two extremes: purely correlative factors like climate, or purely physiological factors unique to a particular species or plant functional group. We are working towards a model that combines both phenotypic and genotypic traits to better predict responses of trees to climate change. We have worked to parameterize a neighborhood dynamics, individual tree forest-gap model called SORTIE-ND, using open data from both the USDA Forest Service Forest Inventory & Analysis (FIA) datasets in California and 30-yr old permanent plots established by the USGS. We generated individual species factors including stage-specific mortality and growth rates, and species-specific allometric equations for ten species, including Abies concolor, A. magnifica, Calocedrus decurrens, Pinus contorta, P. jeffreyi, P. lambertiana, P. monticola, P. ponderosa, and the two hardwoods Quercus chrysolepis and Q. kelloggii. During this process, we also developed two R packages to aid in parameter development for SORTIE-ND in other ecological systems. MakeMyForests is an R package that parses FIA datasets and calculates parameters based on the state averages of growth, light, and allometric parameters. disperseR is an R package that uses extensive plot data, with individual tree, sapling, and seedling measurements, to calculate finely tuned mortality and growth parameters for SORTIE-ND. Both are freely available on GitHub, and future updates will be available on CRAN. To validate the model, we withheld several plots from the 30-yr USGS data while calculating parameters. We tested for differences between the actual withheld data and the simulated forest data, in basal area, seedling density, seed dispersal, and species composition. The similarity of our model to the real system suggests that the model parameters we generated with our R packages accurately represent the system, and that our model can be extended to include changes in precipitation, temperature, and disturbance with very little manipulaton. We hope that our examples, R package development, and SORTIE-ND module development will enable other ecologists to utilize SORTIE-ND to predict changes in local and important ecoystems around the world.

Statistical modeling of daily and subdaily stream temperatures: Application to the Methow River Basin, Washington

NASA Astrophysics Data System (ADS)

Caldwell, R. J.; Gangopadhyay, S.; Bountry, J.; Lai, Y.; Elsner, M. M.

2013-07-01

Management of water temperatures in the Columbia River Basin (Washington) is critical because water projects have substantially altered the habitat of Endangered Species Act listed species, such as salmon, throughout the basin. This is most important in tributaries to the Columbia, such as the Methow River, where the spawning and rearing life stages of these cold water fishes occurs. Climate change projections generally predict increasing air temperatures across the western United States, with less confidence regarding shifts in precipitation. As air temperatures rise, we anticipate a corresponding increase in water temperatures, which may alter the timing and availability of habitat for fish reproduction and growth. To assess the impact of future climate change in the Methow River, we couple historical climate and future climate projections with a statistical modeling framework to predict daily mean stream temperatures. A K-nearest neighbor algorithm is also employed to: (i) adjust the climate projections for biases compared to the observed record and (ii) provide a reference for performing spatiotemporal disaggregation in future hydraulic modeling of stream habitat. The statistical models indicate the primary drivers of stream temperature are maximum and minimum air temperature and stream flow and show reasonable skill in predictability. When compared to the historical reference time period of 1916-2006, we conclude that increases in stream temperature are expected to occur at each subsequent time horizon representative of the year 2020, 2040, and 2080, with an increase of 0.8 ± 1.9°C by the year 2080.

The Effects of Food Limitation on Life History Tradeoffs in Pregnant Male Gulf Pipefish

PubMed Central

Paczolt, Kimberly A.; Jones, Adam G.

2015-01-01

Syngnathid fishes (pipefishes, seahorses and seadragons) are characterized by a unique mode of paternal care in which embryos develop on or in the male’s body, often within a structure known as a brood pouch. Evidence suggests that this pouch plays a role in mediating postcopulatory sexual selection and that males have some control over the events occurring within the pouch during the pregnancy. These observations lead to the prediction that males should invest differently in broods depending on the availability of food. Here, we use the Gulf pipefish to test this prediction by monitoring growth rate and offspring survivorship during the pregnancies of males under low- or high-food conditions. Our results show that pregnant males grow less rapidly on average than non-pregnant males, and pregnant males under low-food conditions grow less than pregnant males under high-food conditions. Offspring survivorship, on the other hand, does not differ between food treatments, suggesting that male Gulf pipefish sacrifice investment in somatic growth, and thus indirectly sacrifice future reproduction, in favor of current reproduction. However, a positive relationship between number of failed eggs and male growth rate in our low-food treatments suggests that undeveloped eggs reduce the pregnancy’s overall cost to the male compared to broods containing only viable offspring. PMID:25970284

The effects of food limitation on life history tradeoffs in pregnant male gulf pipefish.

PubMed

Paczolt, Kimberly A; Jones, Adam G

2015-01-01

Syngnathid fishes (pipefishes, seahorses and seadragons) are characterized by a unique mode of paternal care in which embryos develop on or in the male's body, often within a structure known as a brood pouch. Evidence suggests that this pouch plays a role in mediating postcopulatory sexual selection and that males have some control over the events occurring within the pouch during the pregnancy. These observations lead to the prediction that males should invest differently in broods depending on the availability of food. Here, we use the Gulf pipefish to test this prediction by monitoring growth rate and offspring survivorship during the pregnancies of males under low- or high-food conditions. Our results show that pregnant males grow less rapidly on average than non-pregnant males, and pregnant males under low-food conditions grow less than pregnant males under high-food conditions. Offspring survivorship, on the other hand, does not differ between food treatments, suggesting that male Gulf pipefish sacrifice investment in somatic growth, and thus indirectly sacrifice future reproduction, in favor of current reproduction. However, a positive relationship between number of failed eggs and male growth rate in our low-food treatments suggests that undeveloped eggs reduce the pregnancy's overall cost to the male compared to broods containing only viable offspring.

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.

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.

Effective Teaching Strategies for Predicting Reading Growth in English Language Learners

ERIC Educational Resources Information Center

Melgarejo, Melina

2017-01-01

The goal of the present study was to examine how effective use of teaching strategies predict reading growth among a sample of English Language Learners. The study specifically examined whether the types of teaching strategies that predict growth in decoding skills also predict growth in comprehension skills. The sample consisted of students in…

A crack-closure model for predicting fatigue-crack growth under aircraft spectrum loading

NASA Technical Reports Server (NTRS)

Newman, J. C., Jr.

1981-01-01

The development and application of an analytical model of cycle crack growth is presented that includes the effects of crack closure. The model was used to correlate crack growth rates under constant amplitude loading and to predict crack growth under aircraft spectrum loading on 2219-T851 aluminum alloy sheet material. The predicted crack growth lives agreed well with experimental data. The ratio of predicted to experimental lives ranged from 0.66 to 1.48. These predictions were made using data from an ASTM E24.06.01 Round Robin.

Life sciences today and tomorrow: emerging biotechnologies.

PubMed

Williamson, E Diane

2017-08-01

The purpose of this review is to survey current, emerging and predicted future biotechnologies which are impacting, or are likely to impact in the future on the life sciences, with a projection for the coming 20 years. This review is intended to discuss current and future technical strategies, and to explore areas of potential growth during the foreseeable future. Information technology approaches have been employed to gather and collate data. Twelve broad categories of biotechnology have been identified which are currently impacting the life sciences and will continue to do so. In some cases, technology areas are being pushed forward by the requirement to deal with contemporary questions such as the need to address the emergence of anti-microbial resistance. In other cases, the biotechnology application is made feasible by advances in allied fields in biophysics (e.g. biosensing) and biochemistry (e.g. bio-imaging). In all cases, the biotechnologies are underpinned by the rapidly advancing fields of information systems, electronic communications and the World Wide Web together with developments in computing power and the capacity to handle extensive biological data. A rationale and narrative is given for the identification of each technology as a growth area. These technologies have been categorized by major applications, and are discussed further. This review highlights: Biotechnology has far-reaching applications which impinge on every aspect of human existence. The applications of biotechnology are currently wide ranging and will become even more diverse in the future. Access to supercomputing facilities and the ability to manipulate large, complex biological datasets, will significantly enhance knowledge and biotechnological development.

The HSA in Your Future: Defined Contribution Retiree Medical Coverage.

PubMed

Towarnicky, Jack M

In 2004, when evaluating health savings account (HSA) business opportunities, I predicted: "Twenty-five years ago, no one had ever heard of 401(k); 25 years from now, everyone will have an HSA." Twelve years later, growth in HSA eligibility, participation, contributions and asset accumulations suggests we just might achieve that prediction. This article shares one plan sponsor's journey to help employees accumulate assets to fund medical costs-while employed and after retirement, It documents a 30-plus-year retiree health insurance transition from a defined benefit to a defined dollar structure and culminating in a full-replacement defined contribution structure using HSA-qualifying high-deductible health plans (HDHPs) and then redeploying/repurposing the HSA to incorporate a savings incentive for retiree medical costs.

Impacts of Low Salinity on Growth and Calcification in Baltic Sea Mytilus edulis x trossulus

NASA Astrophysics Data System (ADS)

Sanders, T.; Melzner, F.

2016-02-01

The Baltic Sea is characterized by a steep salinity gradient (25 psu - <5 psu) which is predicted to increase in the future due to increased precipitation. This provides an excellent biological system to study the effects of salinity and inorganic carbon supply on animal physiology. Mytilus edulis x trossulus is adapted to the low saline Baltic Sea, at the cost of slow body growth and reduced shell thickness. The explanation for the small size of Baltic mytilids has been attributed to tradeoffs in energy partitioning due to high energetic costs associated with osmoregulation. However, salinity may effect calcification mechanisms and reduce calcification and thus, body size and growth. To understand the mechanistic effects salinity has on calcification, energy budgets were quantified in larvae, juveniles and adults from 3 populations of Baltic Sea Mytilus spp. at different salinities (6, 11 and 16 psu). Net CaCO3 production at varying salinities and bicarbonate concentrations was also measured. Larvae from low salinity adapted populations (6 psu) had a 3-fold higher respiration rate compared to higher salinity populations. This was also accompanied by a delay of 48 hours in early shell formation. Reductions in growth and increases in metabolism were largest between 11 psu and 6 psu indicating that the predicted desalination of the Baltic will go along with huge energetic costs for mussel populations, potentially leading to loss of reefs in the Eastern Baltic. To investigate the mechanisms behind increased metabolic cost and decreased allocation to growth, energy budgets are presently being constrained in our three populations using modulations in food supply and temperature.

Forest responses to increasing aridity and warmth in the southwestern United States.

PubMed

Williams, A Park; Allen, Craig D; Millar, Constance I; Swetnam, Thomas W; Michaelsen, Joel; Still, Christopher J; Leavitt, Steven W

2010-12-14

In recent decades, intense droughts, insect outbreaks, and wildfires have led to decreasing tree growth and increasing mortality in many temperate forests. We compared annual tree-ring width data from 1,097 populations in the coterminous United States to climate data and evaluated site-specific tree responses to climate variations throughout the 20th century. For each population, we developed a climate-driven growth equation by using climate records to predict annual ring widths. Forests within the southwestern United States appear particularly sensitive to drought and warmth. We input 21st century climate projections to the equations to predict growth responses. Our results suggest that if temperature and aridity rise as they are projected to, southwestern trees will experience substantially reduced growth during this century. As tree growth declines, mortality rates may increase at many sites. Increases in wildfires and bark-beetle outbreaks in the most recent decade are likely related to extreme drought and high temperatures during this period. Using satellite imagery and aerial survey data, we conservatively calculate that ≈ 2.7% of southwestern forest and woodland area experienced substantial mortality due to wildfires from 1984 to 2006, and ≈ 7.6% experienced mortality associated with bark beetles from 1997 to 2008. We estimate that up to ≈ 18% of southwestern forest area (excluding woodlands) experienced mortality due to bark beetles or wildfire during this period. Expected climatic changes will alter future forest productivity, disturbance regimes, and species ranges throughout the Southwest. Emerging knowledge of these impending transitions informs efforts to adaptively manage southwestern forests.

Forest responses to increasing aridity and warmth in the southwestern United States

USGS Publications Warehouse

Williams, A.P.; Allen, Craig D.; Millar, C.I.; Swetnam, T.W.; Michaelsen, J.; Still, C.J.; Leavitt, Steven W.

2010-01-01

In recent decades, intense droughts, insect outbreaks, and wildfires have led to decreasing tree growth and increasing mortality in many temperate forests. We compared annual tree-ring width data from 1,097 populations in the coterminous United States to climate data and evaluated site-specific tree responses to climate variations throughout the 20th century. For each population, we developed a climate-driven growth equation by using climate records to predict annual ring widths. Forests within the southwestern United States appear particularly sensitive to drought and warmth. We input 21st century climate projections to the equations to predict growth responses. Our results suggest that if temperature and aridity rise as they are projected to, southwestern trees will experience substantially reduced growth during this century. As tree growth declines, mortality rates may increase at many sites. Increases in wildfires and bark-beetle outbreaks in the most recent decade are likely related to extreme drought and high temperatures during this period. Using satellite imagery and aerial survey data, we conservatively calculate that ≈2.7% of southwestern forest and woodland area experienced substantial mortality due to wildfires from 1984 to 2006, and ≈7.6% experienced mortality associated with bark beetles from 1997 to 2008. We estimate that up to ≈18% of southwestern forest area (excluding woodlands) experienced mortality due to bark beetles or wildfire during this period. Expected climatic changes will alter future forest productivity, disturbance regimes, and species ranges throughout the Southwest. Emerging knowledge of these impending transitions informs efforts to adaptively manage southwestern forests.

Total water storage dynamics derived from tree-ring records and terrestrial gravity observations

NASA Astrophysics Data System (ADS)

Creutzfeldt, Benjamin; Heinrich, Ingo; Merz, Bruno

2015-10-01

For both societal and ecological reasons, it is important to understand past and future subsurface water dynamics but estimating subsurface water storage is notoriously difficult. In this pilot study, we suggest the reconstruction of subsurface water dynamics by a multi-disciplinary approach combining hydrology, dendrochronology and geodesy. In a first step, nine complete years of high-precision gravimeter observations are used to estimate water storage changes in the subsurface at the Geodetic Observatory Wettzell in the Bavarian Forest, Germany. The record is extended to 63 years by calibrating a hydrological model against the 9 years of gravimeter observations. The relationship between tree-ring growth and water storage changes is evaluated as well as that between tree-ring growth and supplementary hydro-meteorological data. Results suggest that tree-ring growth is influenced primarily by subsurface water storage. Other variables related to the overall moisture status (e.g., Standardized Precipitation Index, Palmer Drought Severity Index, streamflow) are also strongly correlated with tree-ring width. While these indices are all indicators of water stored in the landscape, water storage changes of the subsurface estimated by depth-integral measurements give us the unique opportunity to directly reconstruct subsurface water storage dynamics from records of tree-ring width. Such long reconstructions will improve our knowledge of past water storage variations and our ability to predict future developments. Finally, knowing the relationship between subsurface storage dynamics and tree-ring growth improves the understanding of the different signal components contained in tree-ring chronologies.

Interactions of predominant insects and diseases with climate change in Douglas-fir forests of western Oregon and Washington, U.S.A.

PubMed

Agne, Michelle C; Beedlow, Peter A; Shaw, David C; Woodruff, David R; Lee, E Henry; Cline, Steven P; Comeleo, Randy L

2018-02-01

Forest disturbance regimes are beginning to show evidence of climate-mediated changes, such as increasing severity of droughts and insect outbreaks. We review the major insects and pathogens affecting the disturbance regime for coastal Douglas-fir forests in western Oregon and Washington State, USA, and ask how future climate changes may influence their role in disturbance ecology. Although the physiological constraints of light, temperature, and moisture largely control tree growth, episodic and chronic disturbances interacting with biological factors have substantial impacts on the structure and functioning of forest ecosystems in this region. Understanding insect and disease interactions is critical to predicting forest response to climate change and the consequences for ecosystem services, such as timber, clean water, fish and wildlife. We focused on future predictions for warmer wetter winters, hotter drier summers, and elevated atmospheric CO 2 to hypothesize the response of Douglas-fir forests to the major insects and diseases influencing this forest type: Douglas-fir beetle, Swiss needle cast, black stain root disease, and laminated root rot. We hypothesize that 1) Douglas-fir beetle and black stain root disease could become more prevalent with increasing, fire, temperature stress, and moisture stress, 2) future impacts of Swiss needle cast are difficult to predict due to uncertainties in May-July leaf wetness, but warmer winters could contribute to intensification at higher elevations, and 3) laminated root rot will be influenced primarily by forest management, rather than climatic change. Furthermore, these biotic disturbance agents interact in complex ways that are poorly understood. Consequently, to inform management decisions, insect and disease influences on disturbance regimes must be characterized specifically by forest type and region in order to accurately capture these interactions in light of future climate-mediated changes.

Urban Landscape Characterization Using Remote Sensing Data For Input into Air Quality Modeling

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Khan, Maudood

2005-01-01

The urban landscape is inherently complex and this complexity is not adequately captured in air quality models that are used to assess whether urban areas are in attainment of EPA air quality standards, particularly for ground level ozone. This inadequacy of air quality models to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well these models predict ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to meteorological and air quality models focusing on the Atlanta, Georgia metropolitan area as a case study. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the Community Multiscale Air Quality (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality.

An analysis of human-induced land transformations in the San Francisco Bay/Sacramento area

USGS Publications Warehouse

Kirtland, David A.; Gaydos, L.J.; Clarke, Keith; DeCola, Lee; Acevedo, William; Bell, Cindy

1994-01-01

Part of the U.S. Geological Survey's Global Change Research Program involvesstudying the area from the Pacific Ocean to the Sierra foothills to enhance understanding ofthe role that human activities play in global change. The study investigates the ways thathumans transform the land and the effects that changing the landscape may have on regionaland global systems. To accomplish this research, scientists are compiling records ofhistorical transformations in the region's land cover over the last 140 years, developing asimulation model to predict land cover change, and assembling a digital data set to analyzeand describe land transformations. The historical data regarding urban growth focusattention on the significant change the region underwent from 1850 to 1990. Animation isused to visualize a time series of the change in land cover. The historical change is beingused to calibrate a prototype cellular automata model, developed to predict changes in urbanland cover 100 years into the future. Future urban growth scenarios will be developed foranalyzing possible human-induced impacts on land cover at a regional scale. These data aidin documenting and understanding human-induced land transformations from both historical andpredictive perspectives. A descriptive analysis of the region is used to investigate therelationships among data characteristic of the region. These data consist of multilayertopography, climate, vegetation, and population data for a 256-km2 region of centralCalifornia. A variety of multivariate analysis tools are used to integrate the data inraster format from map contours, interpolated climate observations, satellite observations,and population estimates.

Monitoring Urban Land Cover/land Use Change in Algiers City Using Landsat Images (1987-2016)

NASA Astrophysics Data System (ADS)

Bouchachi, B.; Zhong, Y.

2017-09-01

Monitoring the Urban Land Cover/Land Use change detection is important as one of the main driving forces of environmental change because Urbanization is the biggest changes in form of Land, resulting in a decrease in cultivated areas. Using remote sensing ability to solve land resources problems. The purpose of this research is to map the urban areas at different times to monitor and predict possible urban changes, were studied the annual growth urban land during the last 29 years in Algiers City. Improving the productiveness of long-term training in land mapping, were have developed an approach by the following steps: 1) pre-processing for improvement of image characteristics; 2) extract training sample candidates based on the developed methods; and 3) Derive maps and analyzed of Algiers City on an annual basis from 1987 to 2016 using a Supervised Classifier Support Vector Machine (SVMs). Our result shows that the strategy of urban land followed in the region of Algiers City, developed areas mostly were extended to East, West, and South of Central Regions. The urban growth rate is linked with National Office of Statistics data. Future studies are required to understand the impact of urban rapid lands on social, economy and environmental sustainability, it will also close the gap in data of urbanism available, especially on the lack of reliable data, environmental and urban planning for each municipality in Algiers, develop experimental models to predict future land changes with statistically significant confidence.

Declining Coral Skeletal Extension for Forereef Colonies of Siderastrea siderea on the Mesoamerican Barrier Reef System, Southern Belize

PubMed Central

Castillo, Karl D.; Ries, Justin B.; Weiss, Jack M.

2011-01-01

Background Natural and anthropogenic stressors are predicted to have increasingly negative impacts on coral reefs. Understanding how these environmental stressors have impacted coral skeletal growth should improve our ability to predict how they may affect coral reefs in the future. We investigated century-scale variations in skeletal extension for the slow-growing massive scleractinian coral Siderastrea siderea inhabiting the forereef, backreef, and nearshore reefs of the Mesoamerican Barrier Reef System (MBRS) in the western Caribbean Sea. Methodology/Principal Findings Thirteen S. siderea cores were extracted, slabbed, and X-rayed. Annual skeletal extension was estimated from adjacent low- and high-density growth bands. Since the early 1900s, forereef S. siderea colonies have shifted from exhibiting the fastest to the slowest average annual skeletal extension, while values for backreef and nearshore colonies have remained relatively constant. The rates of change in annual skeletal extension were −0.020±0.005, 0.011±0.006, and −0.008±0.006 mm yr−1 per year [mean±SE] for forereef, backreef, and nearshore colonies respectively. These values for forereef and nearshore S. siderea were significantly lower by 0.031±0.008 and by 0.019±0.009 mm yr−1 per year, respectively, than for backreef colonies. However, only forereef S. siderea exhibited a statistically significant decline in annual skeletal extension over the last century. Conclusions/Significance Our results suggest that forereef S. siderea colonies are more susceptible to environmental stress than backreef and nearshore counterparts, which may have historically been exposed to higher natural baseline stressors. Alternatively, sediment plumes, nutrients, and pollution originating from watersheds of Guatemala and Honduras may disproportionately impact the forereef environment of the MBRS. We are presently reconstructing the history of environmental stressors that have impacted the MBRS to constrain the cause(s) of the observed reductions in coral skeletal growth. This should improve our ability to predict and potentially mitigate the effects of future environmental stressors on coral reef ecosystems. PMID:21359203

Plant Nitrogen Uptake in Terrestrial Biogeochemical Models

NASA Astrophysics Data System (ADS)

Marti Donati, A.; Cox, P.; Smith, M. J.; Purves, D.; Sitch, S.; Jones, C. D.

2013-12-01

Most terrestrial biogeochemical models featured in the last Intergovernmental Panel on Climate Change (IPPC) Assessment Report highlight the importance of the terrestrial Carbon sequestration and feedbacks between the terrestrial Carbon cycle and the climate system. However, these models have been criticized for overestimating predicted Carbon sequestration and its potential climate feedback when calculating the rate of future climate change because they do not account for the Carbon sequestration constraints caused by nutrient limitation, particularly Nitrogen (N). This is particularly relevant considering the existence of a substantial deficit of Nitrogen for plants in most areas of the world. To date, most climate models assume that plants have access to as much Nitrogen as needed, but ignore the nutrient requirements for new vegetation growth. Determining the natural demand and acquisition for Nitrogen and its associated resource optimization is key when accounting for the Carbon sequestration constrains caused by nutrient limitation. The few climate models that include C-N dynamics have illustrated that the stimulation of plant growth over the coming century may be significantly smaller than previously predicted. However, models exhibit wide differences in their predictive accuracy and lead to widely diverging and inconsistent projections accounting for an uncertain Carbon sequestration decrease due to Nitrogen limitation ranging from 7 to 64%. This reduction in growth is partially offset by an increase in the availability of nutrients resulting from an accelerated rate of decomposition of dead plants and other organic matter that occurring with a rise in temperature. However, this offset does not counterbalance the reduced level of plant growth calculated by natural nutrient limitations. Additionally, Nitrogen limitation is also expected to become more pronounced in some ecosystems as atmospheric CO2 concentration increases; resulting in less new growth and higher atmospheric CO2 concentrations than originally expected. This study compares the differences in the predictions of alternative models of plant N uptake found in different terrestrial biogeochemical models with the predictions from a new N-uptake model developed under the Joint UK Land Environment Simulator (JULES) framework. We implement a methodology for the construction, parameterization and evaluation of N uptake models to fully decompose all the N uptake component processes in terms of their parameter uncertainty and the accuracy of their predictions with respect to different empirical data sets. Acknowledgements This work has been funded by the European Commission FP7-PEOPLE-ITN-2008 Marie Curie Action: "Greencycles II: FP7-PEOPLE-ITN-2008 Marie Curie Action: "Networks for Initial Training"

Global Tree Range Shifts Under Forecasts from Two Alternative GCMs Using Two Future Scenarios

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Kumar, J.; Potter, K. M.; Hoffman, F. M.

2013-12-01

Global shifts in the environmentally suitable ranges of 215 tree species were predicted under forecasts from two GCMs (the Parallel Climate Model (PCM), and the Hadley Model), each under two IPCC future climatic scenarios (A1 and B1), each at two future dates (2050 and 2100). The analysis considers all global land surface at a resolution of 4 km2. A statistical multivariate clustering procedure was used to quantitatively delineate 30 thousand environmentally homogeneous ecoregions across present and 8 potential future global locations at once, using global maps of 17 environmental characteristics describing temperature, precipitation, soils, topography and solar insolation. Presence of each tree species on Forest Inventory Analysis (FIA) plots and in Global Biodiversity Information Facility (GBIF) samples was used to select a subset of suitable ecoregions from the full set of 30 thousand. Once identified, this suitable subset of ecoregions was compared to the known current range of the tree species under present conditions. Predicted present ranges correspond well with current understanding for all but a few of the 215 tree species. The subset of suitable ecoregions for each tree species can then be tracked into the future to determine whether the suitable home range for this species remains the same, moves, grows, shrinks, or disappears under each model/scenario combination. Occurrence and growth performance measurements for various tree species across the U.S. are limited to FIA plots. We present a new, general-purpose empirical imputation method which associates sparse measurements of dependent variables with particular multivariate clustered combinations of the independent variables, and then estimates values for unmeasured clusters, based on directional proximity in multidimensional data space, at both the cluster and map-cell levels of resolution. Using Associative Clustering, we scaled up the FIA point measurements into contonuous maps that show the expected growth and suitability for individual tree species across the continental US. Maps were generated for each tree species showing the Minimum Required Movement (MRM) straight-line distance from each currently suitable location to the geographically nearest "lifeboat" location having suitable conditions in the future. Locations that are the closest "lifeboats" for many MRM propagules originating from wide surrounding areas may constitute high-priority preservation targets as a refugium against climatic change.

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.

Computational predictions of energy materials using density functional theory

NASA Astrophysics Data System (ADS)

Jain, Anubhav; Shin, Yongwoo; Persson, Kristin A.

2016-01-01

In the search for new functional materials, quantum mechanics is an exciting starting point. The fundamental laws that govern the behaviour of electrons have the possibility, at the other end of the scale, to predict the performance of a material for a targeted application. In some cases, this is achievable using density functional theory (DFT). In this Review, we highlight DFT studies predicting energy-related materials that were subsequently confirmed experimentally. The attributes and limitations of DFT for the computational design of materials for lithium-ion batteries, hydrogen production and storage materials, superconductors, photovoltaics and thermoelectric materials are discussed. In the future, we expect that the accuracy of DFT-based methods will continue to improve and that growth in computing power will enable millions of materials to be virtually screened for specific applications. Thus, these examples represent a first glimpse of what may become a routine and integral step in materials discovery.

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.

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.

Recent growth of conifer species of western North America: Assessing spatial patterns of radial growth trends

USGS Publications Warehouse

McKenzie, D.; Hessl, Amy E.; Peterson, D.L.

2001-01-01

We explored spatial patterns of low-frequency variability in radial tree growth among western North American conifer species and identified predictors of the variability in these patterns. Using 185 sites from the International Tree-Ring Data Bank, each of which contained 10a??60 raw ring-width series, we rebuilt two chronologies for each site, using two conservative methods designed to retain any low-frequency variability associated with recent environmental change. We used factor analysis to identify regional low-frequency patterns in site chronologies and estimated the slope of the growth trend since 1850 at each site from a combination of linear regression and time-series techniques. This slope was the response variable in a regression-tree model to predict the effects of environmental gradients and species-level differences on growth trends. Growth patterns at 27 sites from the American Southwest were consistent with quasi-periodic patterns of drought. Either 12 or 32 of the 185 sites demonstrated patterns of increasing growth between 1850 and 1980 A.D., depending on the standardization technique used. Pronounced growth increases were associated with high-elevation sites (above 3000 m) and high-latitude sites in maritime climates. Future research focused on these high-elevation and high-latitude sites should address the precise mechanisms responsible for increased 20th century growth.

Refining the treatment of advanced nonsmall cell lung cancer

PubMed Central

Ogita, Shin; Wozniak, Antoinette J

2010-01-01

Metastatic nonsmall cell lung cancer (NSCLC) is a debilitating and deadly disease with virtually no chance for long-term survival. Chemotherapy has improved both survival and quality of life for patients with advanced disease. Overall survival of patients with metastatic NSCLC has gradually increased from 8 to 12 months over the past three decades with the introduction of new chemotherapeutic drugs and agents directed at novel targets in the cancer cell. Epidermal growth factor receptor and vascular endothelial growth factor are two such targets. Recent developments also include treatment based on histology and the use of maintenance therapy. It has been recognized that lung cancer is a very complex disease. It is common practice to include a number of scientific correlative studies in the design of clinical trials in order to determine predictive markers of benefit from treatment. This article will review the current approach to the treatment of advanced NSCLC including the use of chemotherapy and molecularly targeted agents. Future directions including the use of potentially predictive biomarkers and innovative clinical trials aimed at a more individualized approach to treatment will also be discussed. PMID:28210103

Dynamic modeling of Tampa Bay urban development using parallel computing

USGS Publications Warehouse

Xian, G.; Crane, M.; Steinwand, D.

2005-01-01

Urban land use and land cover has changed significantly in the environs of Tampa Bay, Florida, over the past 50 years. Extensive urbanization has created substantial change to the region's landscape and ecosystems. This paper uses a dynamic urban-growth model, SLEUTH, which applies six geospatial data themes (slope, land use, exclusion, urban extent, transportation, hillside), to study the process of urbanization and associated land use and land cover change in the Tampa Bay area. To reduce processing time and complete the modeling process within an acceptable period, the model is recoded and ported to a Beowulf cluster. The parallel-processing computer system accomplishes the massive amount of computation the modeling simulation requires. SLEUTH calibration process for the Tampa Bay urban growth simulation spends only 10 h CPU time. The model predicts future land use/cover change trends for Tampa Bay from 1992 to 2025. Urban extent is predicted to double in the Tampa Bay watershed between 1992 and 2025. Results show an upward trend of urbanization at the expense of a decline of 58% and 80% in agriculture and forested lands, respectively.

Global positive expectancies in adolescence and health-related behaviours: Longitudinal models of latent growth and cross-lagged effects

PubMed Central

Carvajal, Scott C.

2015-01-01

Constructs representative of global positive expectancies (GPE) such as dispositional optimism and hope have been theoretically and empirically linked to many positive mental and physical health outcomes. However such expectancies’ health implications for adolescents, as well as their trajectory over time, are less well understood than for adult populations. This study tested whether GPE predict the key indicators of adolescents’ future physical health status, their health-related behaviours. A prospective longitudinal study design was employed whereby a diverse population-based cohort (N = 744; mean age at baseline = 12) completed three surveys over approximately 18 months. Rigorous tests of causal predominance and reciprocal effects were conducted through latent growth and cross-panel structural equation models. Results showed GPE systematically decreased during the course of the study, yet higher initial levels of GPE predicted less alcohol drinking, healthier food choice and greater physical activity over time. GPE’s protective relationships towards health protective behaviours (vs. health risk behaviours that also included tobacco smoking) appear more independent from depressive symptomatology, and the primary findings were robust across socio-demographic groups. PMID:22149606

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.

Nonlinear Development and Secondary Instability of Traveling Crossflow Vortices

NASA Technical Reports Server (NTRS)

Li, Fei; Choudhari, Meelan M.; Duan, Lian; Chang, Chau-Lyan

2014-01-01

Transition research under NASA's Aeronautical Sciences Project seeks to develop a validated set of variable fidelity prediction tools with known strengths and limitations, so as to enable "sufficiently" accurate transition prediction and practical transition control for future vehicle concepts. This paper builds upon prior effort targeting the laminar breakdown mechanisms associated with stationary crossflow instability over a swept-wing configuration relevant to subsonic aircraft with laminar flow technology. Specifically, transition via secondary instability of traveling crossflow modes is investigated as an alternate scenario for transition. Results show that, for the parameter range investigated herein, secondary instability of traveling crossflow modes becomes insignificant in relation to the secondary instability of the stationary modes when the relative initial amplitudes of the traveling crossflow instability are lower than those of the stationary modes by approximately two orders of magnitudes or more. Linear growth predictions based on the secondary instability theory are found to agree well with those based on PSE and DNS, with the most significant discrepancies being limited to spatial regions of relatively weak secondary growth, i.e., regions where the primary disturbance amplitudes are smaller in comparison to its peak amplitude. Nonlinear effects on secondary instability evolution is also investigated and found to be initially stabilizing, prior to breakdown.

Beyond Bevacizumab: An Outlook to New Anti-Angiogenics for the Treatment of Ovarian Cancer.

PubMed

Mahner, Sven; Woelber, Linn; Mueller, Volkmar; Witzel, Isabell; Prieske, Katharina; Grimm, Donata; Keller-V Amsberg, Gunhild; Trillsch, Fabian

2015-01-01

In addition to the monoclonal vascular endothelial growth factor (VEGF) antibody bevacizumab, several alternative anti-angiogenic treatment strategies for ovarian cancer patients have been evaluated in clinical trials. Apart from targeting extracellular receptors by the antibody aflibercept or the peptibody trebananib, the multikinase inhibitors pazopanib, nintedanib, cediranib, sunitinib, and sorafenib were developed to interfere with VEGF receptors and multiple additional intracellular pathways. Nintedanib and pazopanib significantly improved progression-free survival in two positive phase III trials for first-line therapy. A reliable effect on overall survival could, however, not be observed for any anti-angiogenic first-line therapies so far. In terms of recurrent disease, two positive phase III trials revealed that trebananib and cediranib are effective anti-angiogenic agents for this indication. Patient selection and biomarker guided prediction of response seems to be a central aspect for future studies. Combining anti-angiogenics with other targeted therapies to possibly spare chemotherapy in certain constellations represents another very interesting future perspective for clinical trials. This short review gives an overview of current clinical trials for anti-angiogenic treatment strategies beyond bevacizumab. In this context, possible future perspectives combining anti-angiogenics with other targeted therapies and the need for specific biomarkers predicting response are elucidated.

Keep up or drown: adjustment of western Pacific coral reefs to sea-level rise in the 21st century

PubMed Central

van Woesik, R.; Golbuu, Y.; Roff, G.

2015-01-01

Since the Mid-Holocene, some 5000 years ago, coral reefs in the Pacific Ocean have been vertically constrained by sea level. Contemporary sea-level rise is releasing these constraints, providing accommodation space for vertical reef expansion. Here, we show that Porites microatolls, from reef-flat environments in Palau (western Pacific Ocean), are ‘keeping up’ with contemporary sea-level rise. Measurements of 570 reef-flat Porites microatolls at 10 locations around Palau revealed recent vertical skeletal extension (78±13 mm) over the last 6–8 years, which is consistent with the timing of the recent increase in sea level. We modelled whether microatoll growth rates will potentially ‘keep up’ with predicted sea-level rise in the near future, based upon average growth, and assuming a decline in growth for every 1°C increase in temperature. We then compared these estimated extension rates with rates of sea-level rise under four Representative Concentration Pathways (RCPs). Our model suggests that under low–mid RCP scenarios, reef-coral growth will keep up with sea-level rise, but if greenhouse gas concentrations exceed 670 ppm atmospheric CO2 levels and with +2.2°C sea-surface temperature by 2100 (RCP 6.0 W m−2), our predictions indicate that Porites microatolls will be unable to keep up with projected rates of sea-level rise in the twenty-first century. PMID:26587277

Can Tree Ring Analyses Predict Resilience of Black Spruce Forests to Fire in Interior Alaska?

NASA Astrophysics Data System (ADS)

Walker, X. J.; Johnstone, J. F.; Mack, M. C.

2015-12-01

Climate change has increased the occurrence, severity, and impact of disturbances on forested ecosystems worldwide. As such there is a growing need to identify factors that contribute to an ecosystem's ability to recover from disturbance, commonly referred to as ecosystem resilience. In trees, drought-induced growth declines may signal decreased ecosystem resilience if mature trees are able to survive in stressful environmental conditions that do not permit successful post-disturbance recruitment and survival. Here we explore links between ecosystem resilience and the growth-climate relationships of pre-fire trees, specifically drought stress signals, across topographic moisture gradients within the boreal forest. We sampled 72 recently (2004) burned black spruce stands within interior Alaska and found the proportion of black spruce relative to deciduous trees decreased post-fire, ranging from almost no change to a 90% decrease. The largest shifts in post-fire species composition occurred in sites where trees showed negative growth responses to warm spring temperatures, and shallow post-fire organic layer depths due to dry site conditions or high fire severity. These sites were generally located at warmer and drier landscape positions, suggesting they are less resilient to disturbance than sites at the wetter end of the gradient. Tree growth-climate responses can provide an estimate of stand environmental stress to ongoing climate change and as such are a valuable tool for predicting landscape variations in forest ecosystem resilience and forecasting future forest composition.

Numerical simulation of turbulence flow in a Kaplan turbine -Evaluation on turbine performance prediction accuracy-

NASA Astrophysics Data System (ADS)

Ko, P.; Kurosawa, S.

2014-03-01

The understanding and accurate prediction of the flow behaviour related to cavitation and pressure fluctuation in a Kaplan turbine are important to the design work enhancing the turbine performance including the elongation of the operation life span and the improvement of turbine efficiency. In this paper, high accuracy turbine and cavitation performance prediction method based on entire flow passage for a Kaplan turbine is presented and evaluated. Two-phase flow field is predicted by solving Reynolds-Averaged Navier-Stokes equations expressed by volume of fluid method tracking the free surface and combined with Reynolds Stress model. The growth and collapse of cavitation bubbles are modelled by the modified Rayleigh-Plesset equation. The prediction accuracy is evaluated by comparing with the model test results of Ns 400 Kaplan model turbine. As a result that the experimentally measured data including turbine efficiency, cavitation performance, and pressure fluctuation are accurately predicted. Furthermore, the cavitation occurrence on the runner blade surface and the influence to the hydraulic loss of the flow passage are discussed. Evaluated prediction method for the turbine flow and performance is introduced to facilitate the future design and research works on Kaplan type turbine.

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

Warming reinforces nonconsumptive predator effects on prey growth, physiology, and body stoichiometry.

PubMed

Janssens, Lizanne; Van Dievel, Marie; Stoks, Robby

2015-12-01

While nonconsumptive effects of predators may strongly affect prey populations, little is known how future warming will modulate these effects. Such information would be especially relevant with regard to prey physiology and resulting changes in prey stoichiometry. We investigated in Enallagma cyathigerum damselfly larvae the effects of a 4°C warming (20°C vs. 24°C) and predation risk on growth rate, physiology and body stoichiometry, for the first time including all key mechanisms suggested by the general stress paradigm (GSP) on how stressors shape changes in body stoichiometry. Growth rate and energy storage were higher at 24°C. Based on thermodynamic principles and the growth rate hypothesis, we could demonstrate predictable reductions in body C:P under warming and link these to the increase in P-rich RNA; the associated warming-induced decrease in C:N may be explained by the increased synthesis of N-rich proteins. Yet, under predation risk, growth rate instead decreased with warming and the warming-induced decreases in C:N and C:P disappeared. As predicted by the GSP, larvae increased body C:N and C:P at 24°C under predation risk. Notably, we did not detect the assumed GSP-mechanisms driving these changes: despite an increased metabolic rate there was neither an increase of C-rich biomolecules (instead fat and sugar contents decreased under predation risk), nor a decrease of N-rich proteins. We hypothesize that the higher C:N and N:P under predation risk are caused by a higher investment in morphological defense. This may also explain the stronger predator-induced increase in C:N under warming. The expected higher C:P under predation risk was only present under warming and matched the observed growth reduction and associated reduction in P-rich RNA. Our integrated mechanistic approach unraveled novel pathways of how warming and predation risk shape body stoichiometry. Key findings that (1) warming effects on elemental stoichiometry were predictable and only present in the absence of predation risk and that (2) warming reinforced the predator-induced effects on C:N:P, are pivotal in understanding how nonconsumptive predator effects under global warming will shape prey populations.

Future hotspots of terrestrial mammal loss

PubMed Central

Visconti, Piero; Pressey, Robert L.; Giorgini, Daniele; Maiorano, Luigi; Bakkenes, Michel; Boitani, Luigi; Alkemade, Rob; Falcucci, Alessandra; Chiozza, Federica; Rondinini, Carlo

2011-01-01

Current levels of endangerment and historical trends of species and habitats are the main criteria used to direct conservation efforts globally. Estimates of future declines, which might indicate different priorities than past declines, have been limited by the lack of appropriate data and models. Given that much of conservation is about anticipating and responding to future threats, our inability to look forward at a global scale has been a major constraint on effective action. Here, we assess the geography and extent of projected future changes in suitable habitat for terrestrial mammals within their present ranges. We used a global earth-system model, IMAGE, coupled with fine-scale habitat suitability models and parametrized according to four global scenarios of human development. We identified the most affected countries by 2050 for each scenario, assuming that no additional conservation actions other than those described in the scenarios take place. We found that, with some exceptions, most of the countries with the largest predicted losses of suitable habitat for mammals are in Africa and the Americas. African and North American countries were also predicted to host the most species with large proportional global declines. Most of the countries we identified as future hotspots of terrestrial mammal loss have little or no overlap with the present global conservation priorities, thus confirming the need for forward-looking analyses in conservation priority setting. The expected growth in human populations and consumption in hotspots of future mammal loss mean that local conservation actions such as protected areas might not be sufficient to mitigate losses. Other policies, directed towards the root causes of biodiversity loss, are required, both in Africa and other parts of the world. PMID:21844048

A real-time method to predict social media popularity

NASA Astrophysics Data System (ADS)

Chen, Xiao; Lu, Zhe-Ming

How to predict the future popularity of a message or video on online social media (OSM) has long been an attractive problem for researchers. Although many difficulties are still ahead, recent studies suggest that temporal and topological features of early adopters generally play a very important role. However, with the increase of the adopters, the feature space will grow explosively. How to select the most effective features is still an open issue. In this work, we investigate several feature extraction methods over the Twitter platform and find that most predictive power concentrates on the second half of the propagation period, and that not only a model trained on one platform generalizes well to others as previous works observed, but also a model trained on one dataset performs well on predicting the popularity for other datasets with different number of observed early adopters. According to these findings, at least for the best features by far, the data used to extract features can be halved without loss of evident accuracy and we provide a way to roughly predict the growth trend of a social-media item in real-time.

Computer predictions on Rh-based double perovskites with unusual electronic and magnetic properties

NASA Astrophysics Data System (ADS)

Halder, Anita; Nafday, Dhani; Sanyal, Prabuddha; Saha-Dasgupta, Tanusri

2018-03-01

In search for new magnetic materials, we make computer prediction of structural, electronic and magnetic properties of yet-to-be synthesized Rh-based double perovskite compounds, Sr(Ca)2BRhO6 (B=Cr, Mn, Fe). We use combination of evolutionary algorithm, density functional theory, and statistical-mechanical tool for this purpose. We find that the unusual valence of Rh5+ may be stabilized in these compounds through formation of oxygen ligand hole. Interestingly, while the Cr-Rh and Mn-Rh compounds are predicted to be ferromagnetic half-metals, the Fe-Rh compounds are found to be rare examples of antiferromagnetic and metallic transition-metal oxide with three-dimensional electronic structure. The computed magnetic transition temperatures of the predicted compounds, obtained from finite temperature Monte Carlo study of the first principles-derived model Hamiltonian, are found to be reasonably high. The prediction of favorable growth condition of the compounds, reported in our study, obtained through extensive thermodynamic analysis should be useful for future synthesize of this interesting class of materials with intriguing properties.

The influence of El Niño-Southern Oscillation regimes on eastern African vegetation and its future implications under the RCP8.5 warming scenario

NASA Astrophysics Data System (ADS)

Fer, Istem; Tietjen, Britta; Jeltsch, Florian; Wolff, Christian

2017-09-01

The El Niño-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.

The income body weight gradients in the developing economy of China.

PubMed

Tafreschi, Darjusch

2015-01-01

Existing theories predict the income gradient of individual body weight to change sign from positive to negative in process of economic development. However, there are only few empirical studies which test this hypothesis. This paper adds to the literature on that topic by investigating the case of China. Using individual and community data from 1991 to 2009 waves of the China Health and Nutrition Survey regression analyses suggest that after controlling for important confounding factors (1) higher income is positively related to future growth of individuals' BMI in less developed areas (i.e. BMI growth is 0.7-1.5 percentage points higher when comparing the richest with the poorest individuals), but negatively related to BMI growth in more developed areas (i.e. BMI growth is 0.8-1.6 percentage points lower for the richest individuals), and (2) that concentrations of overweight are "trickling down" to lower income ranks as regions become more developed. Moreover, the reversal of the income gradient appears to happen at earlier stages of development for females. Copyright © 2014 Elsevier B.V. All rights reserved.

GaAsBi Synthesis: From Band Structure Modification to Nanostructure Formation

NASA Astrophysics Data System (ADS)

Collar, Kristen N.

Research and development bismides have proven bismides to be a promising field for material science with important applications in optoelectronics. However, the development of a complete description of the electrical and material properties of bismide ternaries is not comprehensive or straightforward. One of the main benefits of this ternary system is the opportunity for bandgap tuning, which opens doors to new applications. Tuning the bandgap is achieved by means of varying the composition; this allows access to a wider energy spectrum with particular applications in long wavelength emitters and detectors. In addition to bandgap tuning, Bi provides an opportunity to decrease lasing threshold currents, the temperature sensitivity and a major loss mechanism of today's telecom lasers. We propose to characterize the electronic and chemical structure of GaAsBi grown by molecular beam epitaxy. We probe the binding structure using x-ray photoelectron spectroscopy. This provides insights into the antisite incorporation of Bi and the reactivity of the surface. Furthermore, we use XPS to track the energy variation in the valence band with dilute Bi incorporation into GaAs. These insights provide valuable perspective into improving the predictability of bandgaps and of heterostructure band offsets for the realization of bismides in future electronics. The stringent growth conditions required by GaAsBi and the surfactant properties of Bi provide a unique opportunity to study nanostructure formation and epitaxial growth control mechanisms. The GaAsBi epitaxial films under Ga-rich growth conditions self-catalyze Ga droplet seeds for Vapor-Liquid-Solid growth of embedded nanowires. We demonstrate a means to direct the nanowires unidirectionally along preferential crystallographic directions utilizing the step-flow growth mode. We mediated the step-flow growth by employing vicinal surfaces and Bi's surfactant-like properties to enhance the properties of the step-flow growth mode. Semiconductor nanostructures are becoming a cornerstone of future optoelectronics and the work presented herein exploits the power of a bottom-up architecture to self-assemble aligned unidirectional planar nanowires.

Sultanate of Oman: building a dental workforce.

PubMed

Gallagher, Jennifer E; Manickam, Sivakumar; Wilson, Nairn H F

2015-06-22

A medium- and long-term perspective is required in human resource development to ensure that future needs and demands for oral healthcare are met by the most appropriate health professionals. This paper presents a case study of the Sultanate of Oman, one of the Gulf States with a current population of 3.8 million, which has initiated dental training through the creation of a dental college. The objectives of this paper are first to describe trends in the dental workforce in Oman from 1990 to date and compare the dental workforce with its medical counterparts in Oman and with other countries, and second, to consider future dental workforce in the Sultanate. Data were collected from published sources, including the Ministry of Health (MoH), Ministry of Manpower (MoM), and Ministry of National Economy (MoNE)-Sultanate of Oman; the World Health Organization (WHO); World Bank; and the Central Intelligence Agency (CIA). Dentist-to-population ratios were compared nationally, regionally and globally for medicine and dentistry. Dental graduate outputs were mapped onto the local supply. Future trends were examined using population growth predictions, exploring the expected impact in relation to global, regional and European workforce densities. Population growth in Oman is increasing at a rate of over 2% per year. Oman has historically been dependent upon an expatriate dental workforce with only 24% of the dentist workforce Omani in 2010 (n = 160). Subsequent to Oman Dental College (ODC) starting to qualify dental (BDS) graduates in 2012, there is an increase in the annual growth of the dentist workforce. On the assumption that all future dental graduates from ODC have an opportunity to practise in Oman, ODC graduates will boost the annual Omani dentist growth rate starting at 28% per annum from 2012 onwards, building capacity towards global (n = 1711) and regional levels (Gulf State: n = 2167) in the medium term. The output of dental graduates from Oman Dental College is improving the dentist-to-population ratio and helping the Sultanate to realize its aim of developing an Omani-majority dental workforce. The implications for retention of dentists and team training are discussed.

[Development of a predictive program for microbial growth under various temperature conditions].

PubMed

Fujikawa, Hiroshi; Yano, Kazuyoshi; Morozumi, Satoshi; Kimura, Bon; Fujii, Tateo

2006-12-01

A predictive program for microbial growth under various temperature conditions was developed with a mathematical model. The model was a new logistic model recently developed by us. The program predicts Escherichia coli growth in broth, Staphylococcus aureus growth and its enterotoxin production in milk, and Vibrio parahaemolyticus growth in broth at various temperature patterns. The program, which was built with Microsoft Excel (Visual Basic Application), is user-friendly; users can easily input the temperature history of a test food and obtain the prediction instantly on the computer screen. The predicted growth and toxin production can be important indices to determine whether a food is microbiologically safe or not. This program should be a useful tool to confirm the microbial safety of commercial foods.

Hurricane Activity and the Large-Scale Pattern of Spread of an Invasive Plant Species

PubMed Central

Bhattarai, Ganesh P.; Cronin, James T.

2014-01-01

Disturbances are a primary facilitator of the growth and spread of invasive species. However, the effects of large-scale disturbances, such as hurricanes and tropical storms, on the broad geographic patterns of invasive species growth and spread have not been investigated. We used historical aerial imagery to determine the growth rate of invasive Phragmites australis patches in wetlands along the Atlantic and Gulf Coasts of the United States. These were relatively undisturbed wetlands where P. australis had room for unrestricted growth. Over the past several decades, invasive P. australis stands expanded in size by 6–35% per year. Based on tropical storm and hurricane activity over that same time period, we found that the frequency of hurricane-force winds explained 81% of the variation in P. australis growth over this broad geographic range. The expansion of P. australis stands was strongly and positively correlated with hurricane frequency. In light of the many climatic models that predict an increase in the frequency and intensity of hurricanes over the next century, these results suggest a strong link between climate change and species invasion and a challenging future ahead for the management of invasive species. PMID:24878928

Holocene key coral species in the Northwest Pacific: indicators of reef formation and reef ecosystem responses to global climate change and anthropogenic stresses in the near future

NASA Astrophysics Data System (ADS)

Hongo, Chuki

2012-03-01

The geological record of key coral species that contribute to reef formation and maintenance of reef ecosystems is important for understanding the ecosystem response to global-scale climate change and anthropogenic stresses in the near future. Future responses can be predicted from accumulated data on Holocene reef species identified in drillcore and from data on raised reef terraces. The present study analyzes a dataset based on 27 drillcores, raised reef terraces, and 134 radiocarbon and U-Th ages from reefs of the Northwest Pacific, with the aim of examining the role of key coral species in reef growth and maintenance for reef ecosystem during Holocene sea-level change. The results indicate a latitudinal change in key coral species: arborescent Acropora (Acropora intermedia and Acropora muricata) was the dominant reef builder at reef crests in the tropics, whereas Porites (Porites australiensis, Porites lutea, and Porites lobata) was the dominant contributor to reef growth in the subtropics between 10,000 and 7000 cal. years BP (when the rate of sea-level rise was 10 m/ka). Acropora digitifera, Acropora hyacinthus, Acropora robusta/A. abrotanoides, Isopora palifera, Favia stelligera, and Goniastrea retiformis from the corymbose and tabular Acropora facies were the main key coral species at reef crests between 7000 and 5000 cal. years BP (when the rate of sea-level rise was 5 m/ka) and during the following period of stable sea-level. Massive Porites (P. australiensis, P. lutea, and P. lobata) contributed to reef growth in shallow lagoons during the period of stable sea level. Key coral species from the corymbose and tabular Acropora facies have the potential to build reefs and maintain ecosystems in the near future under a global sea-level rise of 2-6 m/ka, as do key coral species from the arborescent Acropora facies and massive Porites facies, which show vigorous growth and are tolerant to relatively deep-water, low-energy environments. However, these species are likely to experience severe mortality in upcoming decades due to natural and anthropogenic stresses. Consequently, this damage will lead to a collapse in reef formation and the maintenance of reef ecosystems in the near future. This study emphasizes the need for research into the conservation of key coral species.

Chronic Generalized Harassment during College: Influences on Alcohol and Drug Use

PubMed Central

McGinley, Meredith; Rospenda, Kathleen M.; Liu, Li; Richman, Judith A.

2015-01-01

The experience of chronic generalized harassment from others can have a deleterious impact on individuals over time. Specifically, coping resources may be taxed, resulting in the use of avoidant coping strategies such substance use. However, little is known about the experience of chronic generalized harassment (e.g., verbal hostility, manipulation by others, exclusion from important events) and its impact on substance use in collegiate populations. In the current study, we examined the latent growth of generalized harassment across the transition from high school to college, whether this growth was heterogeneous, and the relationships between latent generalized harassment classifications and substance use. Incoming freshmen students (N = 2890; 58% female; 53% White) at eight colleges in Illinois completed a web survey at four points: fall 2011 (baseline), spring 2012 (T1), fall 2012 (T2), and fall 2013 (T3). Students were required to be at least 18 years old at baseline, and were compensated with online gift certificates. Two-part Latent Class Growth Analysis (LCGA) was implemented in order to examine heterogeneous growth over time. The results supported a two-class solution (infrequent and chronic classes) for generalized harassment. Growth in harassment was characterized by a decrease from baseline through college entry, with a recovery in rates by T3. Members of the chronically harassed class had greater mean generalized harassment over time, and were less likely to report zero instances of harassment experiences. As hypothesized, membership in the chronic class predicted future binge drinking, drinking to intoxication, problems due to alcohol use, and cigarette use, but not marijuana use. Future interventions should focus on providing college students with resources to help cope with distress stemming from persistent generalized harassment from peers, faculty, and other individuals in higher-education settings. PMID:26081935

Chronic Generalized Harassment During College: Influences on Alcohol and Drug Use.

PubMed

McGinley, Meredith; Rospenda, Kathleen M; Liu, Li; Richman, Judith A

2015-10-01

The experience of chronic generalized harassment from others can have a deleterious impact on individuals over time. Specifically, coping resources may be taxed, resulting in the use of avoidant coping strategies such as substance use. However, little is known about the experience of chronic generalized harassment (e.g., verbal hostility, manipulation by others, exclusion from important events) and its impact on substance use in collegiate populations. In the current study, we examined the latent growth of generalized harassment across the transition from high school to college, whether this growth was heterogeneous, and the relationships between latent generalized harassment classifications and substance use. Incoming freshmen students (N = 2890; 58% female; 53% white) at eight colleges in Illinois completed a web survey at five points: fall 2011 (baseline), spring 2012 (T1), fall 2012 (T2), fall 2013 (T3) and fall 2014 (T4). Students were required to be at least 18 years old at baseline, and were compensated with online gift certificates. Two-part latent class growth analysis was implemented in order to examine heterogeneous growth over time. The results supported a two-class solution (infrequent and chronic classes) for generalized harassment. Growth in harassment was characterized by a decrease from baseline through college entry, with a recovery in rates by T3. Members of the chronically harassed class had greater mean generalized harassment over time, and were less likely to report zero instances of harassment experiences. As hypothesized, membership in the chronic class predicted future binge drinking, drinking to intoxication, problems due to alcohol use, and cigarette use, but not marijuana use. Future interventions should focus on providing college students with resources to help cope with distress stemming from persistent generalized harassment from peers, faculty, and other individuals in higher-education settings.

Evolution of the potential distribution area of french mediterranean forests under global warming

NASA Astrophysics Data System (ADS)

Gaucherel, C.; Guiot, J.; Misson, L.

2008-02-01

This work aims at understanding future spatial and temporal distributions of tree species in the Mediterranean region of France under various climates. We focused on two different species (Pinus Halepensis and Quercus Ilex) and compared their growth under the IPCC-B2 climate scenario in order to quantify significant changes between present and future. The influence of environmental factors such as atmospheric CO2 increase and topography on the tree growth has also been quantified. We modeled species growths with the help of a process-based model (MAIDEN), previously calibrated over measured ecophysiological and dendrochronological series with a Bayesian scheme. The model was fed with the ARPEGE - MeteoFrance climate model, combined with an explicit increase in CO2 atmospheric concentration. The main output of the model gives the carbon allocation in boles and thus tree production. Our results show that the MAIDEN model is correctly able to simulate pine and oak production in space and time, after detailed calibration and validation stages. Yet, these simulations, mainly based on climate, are indicative and not predictive. The comparison of simulated growth at end of 20 and 21 centuries, show a shift of the pine production optimum from about 650 to 950 m due to 2.5°K temperature increase, while no optimum has been found for oak. With the direct effect of CO2 increase taken into account, both species show a significant increase in productivity (+26 and +43% for pine and oak, respectively) at the end of the 21 century. While both species have complementary growth mechanisms, they have a good chance to extend their spatial distribution and their elevation in the Alps during the 21 century under the IPCC-B2 climate scenario. This extension is mainly due to the CO2 fertilization effect.

Host Plant Physiology and Mycorrhizal Functioning Shift across a Glacial through Future [CO2] Gradient1[OPEN

PubMed Central

Mullinix, George W.R.; Ward, Joy K.

2016-01-01

Rising atmospheric carbon dioxide concentration ([CO2]) may modulate the functioning of mycorrhizal associations by altering the relative degree of nutrient and carbohydrate limitations in plants. To test this, we grew Taraxacum ceratophorum and Taraxacum officinale (native and exotic dandelions) with and without mycorrhizal fungi across a broad [CO2] gradient (180–1,000 µL L−1). Differential plant growth rates and vegetative plasticity were hypothesized to drive species-specific responses to [CO2] and arbuscular mycorrhizal fungi. To evaluate [CO2] effects on mycorrhizal functioning, we calculated response ratios based on the relative biomass of mycorrhizal (MBio) and nonmycorrhizal (NMBio) plants (RBio = [MBio − NMBio]/NMBio). We then assessed linkages between RBio and host physiology, fungal growth, and biomass allocation using structural equation modeling. For T. officinale, RBio increased with rising [CO2], shifting from negative to positive values at 700 µL L−1. [CO2] and mycorrhizal effects on photosynthesis and leaf growth rates drove shifts in RBio in this species. For T. ceratophorum, RBio increased from 180 to 390 µL L−1 and further increases in [CO2] caused RBio to shift from positive to negative values. [CO2] and fungal effects on plant growth and carbon sink strength were correlated with shifts in RBio in this species. Overall, we show that rising [CO2] significantly altered the functioning of mycorrhizal associations. These symbioses became more beneficial with rising [CO2], but nonlinear effects may limit plant responses to mycorrhizal fungi under future [CO2]. The magnitude and mechanisms driving mycorrhizal-CO2 responses reflected species-specific differences in growth rate and vegetative plasticity, indicating that these traits may provide a framework for predicting mycorrhizal responses to global change. PMID:27573369

The Heterogeneous Dynamics of Economic Complexity

PubMed Central

Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

2015-01-01

What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch—Economic Complexity—have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method—the selective predictability scheme—in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries. PMID:25671312

The heterogeneous dynamics of economic complexity.

PubMed

Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

2015-01-01

What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch--Economic Complexity--have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method--the selective predictability scheme--in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries.

Comparison of Primary Models to Predict Microbial Growth by the Plate Count and Absorbance Methods.

PubMed

Pla, María-Leonor; Oltra, Sandra; Esteban, María-Dolores; Andreu, Santiago; Palop, Alfredo

2015-01-01

The selection of a primary model to describe microbial growth in predictive food microbiology often appears to be subjective. The objective of this research was to check the performance of different mathematical models in predicting growth parameters, both by absorbance and plate count methods. For this purpose, growth curves of three different microorganisms (Bacillus cereus, Listeria monocytogenes, and Escherichia coli) grown under the same conditions, but with different initial concentrations each, were analysed. When measuring the microbial growth of each microorganism by optical density, almost all models provided quite high goodness of fit (r(2) > 0.93) for all growth curves. The growth rate remained approximately constant for all growth curves of each microorganism, when considering one growth model, but differences were found among models. Three-phase linear model provided the lowest variation for growth rate values for all three microorganisms. Baranyi model gave a variation marginally higher, despite a much better overall fitting. When measuring the microbial growth by plate count, similar results were obtained. These results provide insight into predictive microbiology and will help food microbiologists and researchers to choose the proper primary growth predictive model.

Structure, diversity, and biophysical properties of old-growth forestsin the Klamath region, USA

USGS Publications Warehouse

van Mantgem, Phillip J.; Starr, Daniel A

2015-01-01

The diverse old-growth forests in Klamath region of northern California and southern Oregon provide valuable ecosystem services (e.g., maintaining watersheds, wildlife habitat, recreation), but may be vulnerable to a wide range of stressors, including invasive species, disrupted disturbance regimes, and climatic change. Yet our understanding of how forest structure in the Klamath region relates to the current physical environment is limited. Here we provide present-day benchmarks for old-growth forest structure across a climatic gradient ranging from coastal to dry interior sites. We established 16 large (1 ha) forest plots where all stems > 5 cm in diameter were identified to species and mapped. Climate across these sites was highly variable, with estimated actual evapotranspiration correlated to several basic measures of forest structure, including plot basal area, stem size-class inequality, tree species diversity and, to a lesser extent, tree species richness. Analyses of the spatial arrangement of stems indicated a high degree of non-uniformity, with 75% of plots showing significant stem clumping at small spatial scales (0 to 10 m). Downscaled predictions of future site water balance suggest changes will be dominated by rapidly increasing climatic water deficit (D, a biologically meaningful index of drought). While these plots give a picture of current conditions, continued monitoring of these stands is needed to describe forest dynamics and to detect forest responses to ongoing and future stressors.

Simulating ectomycorrhiza in boreal forests: implementing ectomycorrhizal fungi model MYCOFON in CoupModel (v5)

NASA Astrophysics Data System (ADS)

He, Hongxing; Meyer, Astrid; Jansson, Per-Erik; Svensson, Magnus; Rütting, Tobias; Klemedtsson, Leif

2018-02-01

The symbiosis between plants and Ectomycorrhizal fungi (ECM) is shown to considerably influence the carbon (C) and nitrogen (N) fluxes between the soil, rhizosphere, and plants in boreal forest ecosystems. However, ECM are either neglected or presented as an implicit, undynamic term in most ecosystem models, which can potentially reduce the predictive power of models.

In order to investigate the necessity of an explicit consideration of ECM in ecosystem models, we implement the previously developed MYCOFON model into a detailed process-based, soil-plant-atmosphere model, Coup-MYCOFON, which explicitly describes the C and N fluxes between ECM and roots. This new Coup-MYCOFON model approach (ECM explicit) is compared with two simpler model approaches: one containing ECM implicitly as a dynamic uptake of organic N considering the plant roots to represent the ECM (ECM implicit), and the other a static N approach in which plant growth is limited to a fixed N level (nonlim). Parameter uncertainties are quantified using Bayesian calibration in which the model outputs are constrained to current forest growth and soil C / N ratio for four forest sites along a climate and N deposition gradient in Sweden and simulated over a 100-year period.

The nonlim approach could not describe the soil C / N ratio due to large overestimation of soil N sequestration but simulate the forest growth reasonably well. The ECM implicit and explicit approaches both describe the soil C / N ratio well but slightly underestimate the forest growth. The implicit approach simulated lower litter production and soil respiration than the explicit approach. The ECM explicit Coup-MYCOFON model provides a more detailed description of internal ecosystem fluxes and feedbacks of C and N between plants, soil, and ECM. Our modeling highlights the need to incorporate ECM and organic N uptake into ecosystem models, and the nonlim approach is not recommended for future long-term soil C and N predictions. We also provide a key set of posterior fungal parameters that can be further investigated and evaluated in future ECM studies.

Creep-fatigue modelling in structural steels using empirical and constitutive creep methods implemented in a strip-yield model

NASA Astrophysics Data System (ADS)

Andrews, Benjamin J.

The phenomena of creep and fatigue have each been thoroughly studied. More recently, attempts have been made to predict the damage evolution in engineering materials due to combined creep and fatigue loading, but these formulations have been strictly empirical and have not been used successfully outside of a narrow set of conditions. This work proposes a new creep-fatigue crack growth model based on constitutive creep equations (adjusted to experimental data) and Paris law fatigue crack growth. Predictions from this model are compared to experimental data in two steels: modified 9Cr-1Mo steel and AISI 316L stainless steel. Modified 9Cr-1Mo steel is a high-strength steel used in the construction of pressure vessels and piping for nuclear and conventional power plants, especially for high temperature applications. Creep-fatigue and pure creep experimental data from the literature are compared to model predictions, and they show good agreement. Material constants for the constitutive creep model are obtained for AISI 316L stainless steel, an alloy steel widely used for temperature and corrosion resistance for such components as exhaust manifolds, furnace parts, heat exchangers and jet engine parts. Model predictions are compared to pure creep experimental data, with satisfactory results. Assumptions and constraints inherent in the implementation of the present model are examined. They include: spatial discretization, similitude, plane stress constraint and linear elasticity. It is shown that the implementation of the present model had a non-trivial impact on the model solutions in 316L stainless steel, especially the spatial discretization. Based on these studies, the following conclusions are drawn: 1. The constitutive creep model consistently performs better than the Nikbin, Smith and Webster (NSW) model for predicting creep and creep-fatigue crack extension. 2. Given a database of uniaxial creep test data, a constitutive material model such as the one developed for modified 9Cr-1Mo can be developed for other materials. 3. Due to the assumptions used to develop the strip-yield model, model predictions are expected to show some scatter, especially in some situations. Several areas of future research are proposed from these conclusions: 1. Alternative methods for predicting fatigue crack growth, especially a constitutive fatigue crack growth model, 2. Continued development of new material models and refinement the existing ones, and 3. Implementation of the present creep-fatigue model as a user-defined subroutine in a finite element solver.

The competitive status of trees determines their responsiveness to increasing atmospheric humidity - a climate trend predicted for northern latitudes.

PubMed

Tullus, Arvo; Kupper, Priit; Kaasik, Ants; Tullus, Hardi; Lõhmus, Krista; Sõber, Anu; Sellin, Arne

2017-05-01

The interactive effects of climate variables and tree-tree competition are still insufficiently understood drivers of forest response to global climate change. Precipitation and air humidity are predicted to rise concurrently at high latitudes of the Northern Hemisphere. We investigated whether the growth response of deciduous trees to elevated air humidity varies with their competitive status. The study was conducted in seed-originated silver birch and monoclonal hybrid aspen stands grown at the free air humidity manipulation (FAHM) experimental site in Estonia, in which manipulated stands (n = 3 for both species) are exposed to artificially elevated relative air humidity (6-7% over the ambient level). The study period included three growing seasons during which the stands had reached the competitive stage (trees were 7 years old in the final year). A significant 'treatment×competitive status' interactive effect on growth was detected in all years in birch (P < 0.01) and in one year in aspen stands (P = 0.015). Competitively advantaged trees were always more strongly affected by elevated humidity. Initially the growth of advantaged and neutral trees of both species remained significantly suppressed in humidified stands. In the following years, dominance and elevated humidity had a synergistic positive effect on the growth of birches. Aspens with different competitive status recovered more uniformly, attaining similar relative growth rates in manipulated and control stands, but preserved a significantly lower total growth yield due to severe initial growth stress. Disadvantaged trees of both species were never significantly affected by elevated humidity. Our results suggest that air humidity affects trees indirectly depending on their social status. Therefore, the response of northern temperate and boreal forests to a more humid climate in future will likely be modified by competitive relationships among trees, which may potentially affect species composition and cause a need to change forestry practices. © 2016 John Wiley & Sons Ltd.

Unraveling irradiation induced grain growth with in situ transmission electron microscopy and coordinated modeling

DOE PAGES

Bufford, D. C.; Abdeljawad, F. F.; Foiles, S. M.; ...

2015-11-09

Here, nanostructuring has been proposed as a method to enhance radiation tolerance, but many metallic systems are rejected due to significant concerns regarding long term grain boundary and interface stability. This work utilized recent advancements in transmission electron microscopy (TEM) to quantitatively characterize the grain size, texture, and individual grain boundary character in a nanocrystalline gold model system before and after in situ TEM ion irradiation with 10 MeV Si. The initial experimental measurements were fed into a mesoscale phase field model, which incorporates the role of irradiation-induced thermal events on boundary properties, to directly compare the observed and simulatedmore » grain growth with varied parameters. The observed microstructure evolution deviated subtly from previously reported normal grain growth in which some boundaries remained essentially static. In broader terms, the combined experimental and modeling techniques presented herein provide future avenues to enhance quantification and prediction of the thermal, mechanical, or radiation stability of grain boundaries in nanostructured crystalline systems.« less

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.

Dynamic energy budget modeling reveals the potential of future growth and calcification for the coccolithophore Emiliania huxleyi in an acidified ocean.

PubMed

Muller, Erik B; Nisbet, Roger M

2014-06-01

Ocean acidification is likely to impact the calcification potential of marine organisms. In part due to the covarying nature of the ocean carbonate system components, including pH and CO2 and CO3(2-) levels, it remains largely unclear how each of these components may affect calcification rates quantitatively. We develop a process-based bioenergetic model that explains how several components of the ocean carbonate system collectively affect growth and calcification rates in Emiliania huxleyi, which plays a major role in marine primary production and biogeochemical carbon cycling. The model predicts that under the IPCC A2 emission scenario, its growth and calcification potential will have decreased by the end of the century, although those reductions are relatively modest. We anticipate that our model will be relevant for many other marine calcifying organisms, and that it can be used to improve our understanding of the impact of climate change on marine systems. © 2014 John Wiley & Sons Ltd.

Can rising CO2 concentrations in the atmosphere mitigate the impact of drought years on tree growth?

NASA Astrophysics Data System (ADS)

Achim, Alexis; Plumpton, Heather; Auty, David; Ogee, Jerome; MacCarthy, Heather; Bert, Didier; Domec, Jean-Christophe; Oren, Ram; Wingate, Lisa

2015-04-01

Atmospheric CO2 concentrations and nitrogen deposition rates have increased substantially over the last century and are expected to continue unabated. As a result, terrestrial ecosystems will experience warmer temperatures and some may even experience droughts of a more intense and frequent nature that could lead to widespread forest mortality. Thus there is mounting pressure to understand and predict how forest growth will be affected by such environmental interactions in the future. In this study we used annual tree growth data from the Duke Free Air CO2 Enrichment (FACE) experiment to determine the effects of elevated atmospheric CO2 concentration (+200 ppm) and Nitrogen fertilisation (11.2 g of N m-2 yr-1) on the stem biomass increments of mature loblolly pine (Pinus taeda L.) trees from 1996 to 2010. A non-linear mixed-effects model was developed to provide estimates of annual ring specific gravity in all trees using cambial age and annual ring width as explanatory variables. Elevated CO2 did not have a significant effect on annual ring specific gravity, but N fertilisation caused a slight decrease of approximately 2% compared to the non-fertilised in both the ambient and CO2-elevated plots. When basal area increments were multiplied by wood specific gravity predictions to provide estimates of stem biomass, there was a 40% increase in the CO2-elevated plots compared to those in ambient conditions. This difference remained relatively stable until the application of the fertilisation treatment, which caused a further increase in biomass increments that peaked after three years. Unexpectedly the magnitude of this second response was similar in the CO2-elevated and ambient plots (about 25% in each after 3 years), suggesting that there was no interaction between the concentration of CO2 and the availability of soil N on biomass increments. Importantly, during drier years when annual precipitation was less than 1000 mm we observed a significant decrease in annual increments across all treatments. However, the relative difference in growth between CO2-elevated and ambient plots was greater during drought years, providing evidence that tree growth in the future might become less sensitive to water shortages under elevated CO2 conditions.

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.

The development and validation of different decision-making tools to predict urine culture growth out of urine flow cytometry parameter.

PubMed

Müller, Martin; Seidenberg, Ruth; Schuh, Sabine K; Exadaktylos, Aristomenis K; Schechter, Clyde B; Leichtle, Alexander B; Hautz, Wolf E

2018-01-01

Patients presenting with suspected urinary tract infection are common in every day emergency practice. Urine flow cytometry has replaced microscopic urine evaluation in many emergency departments, but interpretation of the results remains challenging. The aim of this study was to develop and validate tools that predict urine culture growth out of urine flow cytometry parameter. This retrospective study included all adult patients that presented in a large emergency department between January and July 2017 with a suspected urinary tract infection and had a urine flow cytometry as well as a urine culture obtained. The objective was to identify urine flow cytometry parameters that reliably predict urine culture growth and mixed flora growth. The data set was split into a training (70%) and a validation set (30%) and different decision-making approaches were developed and validated. Relevant urine culture growth (respectively mixed flora growth) was found in 40.2% (7.2% respectively) of the 613 patients included. The number of leukocytes and bacteria in flow cytometry were highly associated with urine culture growth, but mixed flora growth could not be sufficiently predicted from the urine flow cytometry parameters. A decision tree, predictive value figures, a nomogram, and a cut-off table to predict urine culture growth from bacteria and leukocyte count were developed, validated and compared. Urine flow cytometry parameters are insufficient to predict mixed flora growth. However, the prediction of urine culture growth based on bacteria and leukocyte count is highly accurate and the developed tools should be used as part of the decision-making process of ordering a urine culture or starting an antibiotic therapy if a urogenital infection is suspected.

The development and validation of different decision-making tools to predict urine culture growth out of urine flow cytometry parameter

PubMed Central

Seidenberg, Ruth; Schuh, Sabine K.; Exadaktylos, Aristomenis K.; Schechter, Clyde B.; Leichtle, Alexander B.; Hautz, Wolf E.

2018-01-01

Objective Patients presenting with suspected urinary tract infection are common in every day emergency practice. Urine flow cytometry has replaced microscopic urine evaluation in many emergency departments, but interpretation of the results remains challenging. The aim of this study was to develop and validate tools that predict urine culture growth out of urine flow cytometry parameter. Methods This retrospective study included all adult patients that presented in a large emergency department between January and July 2017 with a suspected urinary tract infection and had a urine flow cytometry as well as a urine culture obtained. The objective was to identify urine flow cytometry parameters that reliably predict urine culture growth and mixed flora growth. The data set was split into a training (70%) and a validation set (30%) and different decision-making approaches were developed and validated. Results Relevant urine culture growth (respectively mixed flora growth) was found in 40.2% (7.2% respectively) of the 613 patients included. The number of leukocytes and bacteria in flow cytometry were highly associated with urine culture growth, but mixed flora growth could not be sufficiently predicted from the urine flow cytometry parameters. A decision tree, predictive value figures, a nomogram, and a cut-off table to predict urine culture growth from bacteria and leukocyte count were developed, validated and compared. Conclusions Urine flow cytometry parameters are insufficient to predict mixed flora growth. However, the prediction of urine culture growth based on bacteria and leukocyte count is highly accurate and the developed tools should be used as part of the decision-making process of ordering a urine culture or starting an antibiotic therapy if a urogenital infection is suspected. PMID:29474463

Dynamic prediction in functional concurrent regression with an application to child growth.

PubMed

Leroux, Andrew; Xiao, Luo; Crainiceanu, Ciprian; Checkley, William

2018-04-15

In many studies, it is of interest to predict the future trajectory of subjects based on their historical data, referred to as dynamic prediction. Mixed effects models have traditionally been used for dynamic prediction. However, the commonly used random intercept and slope model is often not sufficiently flexible for modeling subject-specific trajectories. In addition, there may be useful exposures/predictors of interest that are measured concurrently with the outcome, complicating dynamic prediction. To address these problems, we propose a dynamic functional concurrent regression model to handle the case where both the functional response and the functional predictors are irregularly measured. Currently, such a model cannot be fit by existing software. We apply the model to dynamically predict children's length conditional on prior length, weight, and baseline covariates. Inference on model parameters and subject-specific trajectories is conducted using the mixed effects representation of the proposed model. An extensive simulation study shows that the dynamic functional regression model provides more accurate estimation and inference than existing methods. Methods are supported by fast, flexible, open source software that uses heavily tested smoothing techniques. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

The interacting effects of nutrient enrichment and ocean acidification on the growth and physiology of the macroalgae Ulva sp.

NASA Astrophysics Data System (ADS)

Reidenbach, L. B.; Hurd, C. L.; Kubler, J.; Fernandez, P. A.; Leal, P. P.; Noisette, F.; Revill, A. T.; McGraw, C. M.

2016-02-01

Ocean acidification, caused by the increased absorption of carbon dioxide in the ocean, changes the carbon chemistry in the seawater, decreases pH, and alters the chemical speciation of some nitrogenous compounds, such as ammonium. The green macroalgae Ulva spp. are intertidal species that occur worldwide. Ocean acidification may alter the growth response of Ulva sp. to increased nutrients by altering the photosynthetic and nutrient physiology of the algae as well as the bioavailability of nutrients. To determine if there is an interactive effect between ocean acidification and nutrient enrichment Ulva sp. were grown in the lab in a cross of three pCO2 levels under ambient and enriched ammonium concentrations. We predicted that the growth rates of Ulva sp. in ammonium enriched treatments would be enhanced by increased pCO2 relative to those in ambient ammonium concentrations. While growth rate, relative electron transport rates, and chlorophyll content were enhanced by enriched ammonium, there was no interactive effect of high pCO2 and ammonium enrichment. Ammonium uptake rates and ammonium pools were not affected by the pH and ammonium interaction, but nitrate reductase activity increased in the high pCO2, high ammonium treatments. Increased pCO2 has been found to increase Ulva sp. growth rates under some conditions, but this was not the case in this set of experiments. To make realistic predictions of Ulva sp. abundances into the future, based on better understanding of their physiology, ocean acidification experiments should include additional environmental variables such as light intensity and macronutrient supplies that may simultaneously be affected by climate change.

First Satellite Measurement of the ULF Wave Growth Rate in the Ion Foreshock

NASA Astrophysics Data System (ADS)

Dorfman, Seth

2017-10-01

Waves generated by accelerated particles are important throughout our heliosphere. These particles often gain their energy at shocks via Fermi acceleration. At the Earth's bow shock, this mechanism accelerates ion beams back into the solar wind; the beams can then generate ultra low frequency (ULF) waves via an ion-ion right hand resonant instability. These waves influence the shock structure and particle acceleration, lead to coherent structures in the magnetosheath, and are ideal for non-linear interaction studies relevant to turbulence. We report the first satellite measurement of the ultralow frequency (ULF) wave growth rate in the upstream region of the Earth's bow shock. This is made possible by employing the two ARTEMIS spacecraft orbiting the moon at 60 Earth radii from Earth to characterize crescent-shaped reflected ion beams and relatively monochromatic ULF waves. The event to be presented features spacecraft separation of 2.5 Earth radii (0.9 +/- 0.1 wavelengths) in the solar wind flow direction along a nearly radial interplanetary magnetic field. By contrast, most prior ULF wave observations use spacecraft with insufficient separation to see wave growth and are so close to Earth (within 30 Earth radii) that waves convected from different events interfere. Using ARTEMIS data, the ULF wave growth rate is estimated and found to fall within dispersion solver predictions during the initial growth time. Observed frequencies and wave numbers are within the predicted range. Other ULF wave properties such as the phase speed, obliquity, and polarization are consistent with expectations from resonant beam instability theory and prior satellite measurements. These results not only advance our understanding of the foreshock, but will also inform future nonlinear studies related to turbulence and dissipation in the heliosphere. Supported by NASA, NASA Eddy Postdoctoral Fellowship.

Geologic Controls on the Growth of Petroleum Reserves

USGS Publications Warehouse

Fishman, Neil S.; Turner, Christine E.; Peterson, Fred; Dyman, Thaddeus S.; Cook, Troy

2008-01-01

The geologic characteristics of selected siliciclastic (largely sandstone) and carbonate (limestone and dolomite) reservoirs in North America (largely the continental United States) were investigated to improve our understanding of the role of geology in the growth of petroleum reserves. Reservoirs studied were deposited in (1) eolian environments (Jurassic Norphlet Formation of the Gulf Coast and Pennsylvanian-Permian Minnelusa Formation of the Powder River Basin), (2) interconnected fluvial, deltaic, and shallow marine environments (Oligocene Frio Formation of the Gulf Coast and the Pennsylvanian Morrow Formation of the Anadarko and Denver Basins), (3) deeper marine environments (Mississippian Barnett Shale of the Fort Worth Basin and Devonian-Mississippian Bakken Formation of the Williston Basin), (4) marine carbonate environments (Ordovician Ellenburger Group of the Permian Basin and Jurassic Smackover Formation of the Gulf of Mexico Basin), (5) a submarine fan environment (Permian Spraberry Formation of the Midland Basin), and (6) a fluvial environment (Paleocene-Eocene Wasatch Formation of the Uinta-Piceance Basin). The connection between an oil reservoir's production history and geology was also evaluated by studying production histories of wells in disparate reservoir categories and wells in a single formation containing two reservoir categories. This effort was undertaken to determine, in general, if different reservoir production heterogeneities could be quantified on the basis of gross geologic differences. It appears that reserve growth in existing fields is most predictable for those in which reservoir heterogeneity is low and thus production differs little between wells, probably owing to relatively homogeneous fluid flow. In fields in which reservoirs are highly heterogeneous, prediction of future growth from infill drilling is notably more difficult. In any case, success at linking heterogeneity to reserve growth depends on factors in addition to geology, such as engineering and technological advances and political or cultural or economic influences.

An Individual-Tree Growth and Yield Prediction System for Even-Aged Natural Shortleaf Pine Forests

Treesearch

Thomas B. Lynch; Kenneth L. Hitch; Michael M. Huebschmann; Paul A. Murphy

1999-01-01

The development of a system of equations that model the growth and development of even-aged natural shortleaf (Pinus echinata Mill.) pine forests is described. The growth prediction system is a distance-independent individual-tree simulator containing equations that predict basal-area growth, survival, total and merchantable heights, and total and...

Effects of global changes on the climatic niche of the tick Ixodes ricinus inferred by species distribution modelling.

PubMed

Porretta, Daniele; Mastrantonio, Valentina; Amendolia, Sara; Gaiarsa, Stefano; Epis, Sara; Genchi, Claudio; Bandi, Claudio; Otranto, Domenico; Urbanelli, Sandra

2013-09-19

Global climate change can seriously impact on the epidemiological dynamics of vector-borne diseases. In this study we investigated how future climatic changes could affect the climatic niche of Ixodes ricinus (Acari, Ixodida), among the most important vectors of pathogens of medical and veterinary concern in Europe. Species Distribution Modelling (SDM) was used to reconstruct the climatic niche of I. ricinus, and to project it into the future conditions for 2050 and 2080, under two scenarios: a continuous human demographic growth and a severe increase of gas emissions (scenario A2), and a scenario that proposes lower human demographic growth than A2, and a more sustainable gas emissions (scenario B2). Models were reconstructed using the algorithm of "maximum entropy", as implemented in the software Maxent 3.3.3e; 4,544 occurrence points and 15 bioclimatic variables were used. In both scenarios an increase of climatic niche of about two times greater than the current area was predicted as well as a higher climatic suitability under the scenario B2 than A2. Such an increase occurred both in a latitudinal and longitudinal way, including northern Eurasian regions (e.g. Sweden and Russia), that were previously unsuitable for the species. Our models are congruent with the predictions of range expansion already observed in I. ricinus at a regional scale and provide a qualitative and quantitative assessment of the future climatically suitable areas for I. ricinus at a continental scale. Although the use of SDM at a higher resolution should be integrated by a more refined analysis of further abiotic and biotic data, the results presented here suggest that under future climatic scenarios most of the current distribution area of I. ricinus could remain suitable and significantly increase at a continental geographic scale. Therefore disease outbreaks of pathogens transmitted by this tick species could emerge in previous non-endemic geographic areas. Further studies will implement and refine present data toward a better understanding of the risk represented by I. ricinus to human health.

Early Life Growth Predictors of Childhood Adiposity Trajectories and Future Risk for Obesity: Birth to Twenty Cohort.

PubMed

Munthali, Richard J; Kagura, Juliana; Lombard, Zané; Norris, Shane A

2017-10-01

There is growing evidence of variations in adiposity trajectories among individuals, but the influence of early life growth patterns on these trajectories is underresearched in low- and middle-income countries. Therefore, our aim was to examine the association between early life conditional weight gain and childhood adiposity trajectories. We previously identified distinct adiposity trajectories (four for girls and three for boys) in black South African children (boys = 877; girls = 947). The association between the trajectories and early life growth patterns, and future obesity risk was assessed by multivariate linear and multinomial logistic and logistic regressions. Conditional weight gain independent of height was computed for infancy (0-2 years) and early childhood (2-4 years). Conditional weight gain before 5 years of age was significantly associated with early onset of obesity or overweight (excess weight) BMI trajectories in both boys and girls. In girls, greater conditional weight gain in infancy was associated with increased relative risk of being in the early-onset obese to morbid obese trajectory, with relative risk ratios of 2.03 (95% confidence interval: 1.17-3.52) compared to belonging to a BMI trajectory in the normal range. Boys and girls in the early-onset obesity or overweight BMI trajectories were more likely to be overweight or obese in early adulthood. Excessive weight gain in infancy and early childhood, independent of linear growth, predicts childhood and adolescent BMI trajectories toward obesity. These results underscore the importance of early life factors in the development of obesity and other NCDs in later life.

Scenario analysis for sustainable development of Chongming Island: water resources sustainability.

PubMed

Ni, Xiong; Wu, Yanqing; Wu, Jun; Lu, Jian; Wilson, P Chris

2012-11-15

With the socioeconomic and urban development of Chongming Island (the largest alluvial island in the world), water demand is rapidly growing. To make adjustments to the water utilization structure of each industry, allocate limited water resources, and increase local water use efficiency, this study performed a scenario analysis for the water sustainability of Chongming Island. Four different scenarios were performed to assess the water resource availability by 2020. The growth rate for water demand will be much higher than that of water supply under a serious situation prediction. The water supply growth volume will be 2.22 × 10(8)m(3) from 2010 to 2020 under Scenario I and Scenario II while the corresponding water demand growth volume will be 2.74 × 10(8)m(3) and 2.64 × 10(8)m(3), respectively. There will be a rapid growth in water use benefit under both high and low development modes. The water use benefit will be about 50 CNY/m(3) under Scenarios I and II in 2020. The production structure will need to be adjusted for sustainable utilization of water resources. Sewage drainage but not the forest and grass coverage rate will be a major obstacle to future development and environmental quality. According to a multi-level fuzzy comprehensive evaluation, Scenario II is finally deemed to be the most desirable plan, suggesting that the policy of rapid socioeconomic development and better environmental protection may achieve the most sustainable development of Chongming Island in the future. Copyright © 2012 Elsevier B.V. All rights reserved.

HEALTH CARE SPENDING GROWTH AND THE FUTURE OF U.S. TAX RATES

PubMed Central

Baicker, Katherine; Skinner, Jonathan S.

2011-01-01

The fraction of GDP devoted to health care in the United States is the highest in the world and rising rapidly. Recent economic studies have highlighted the growing value of health improvements, but less attention has been paid to the efficiency costs of tax-financed spending to pay for such improvements. This paper uses a life cycle model of labor supply, saving, and longevity improvement to measure the balanced-budget impact of continued growth in the Medicare and Medicaid programs. The model predicts that top marginal tax rates could rise to 70 percent by 2060, depending on the progressivity of future tax changes. The deadweight loss of the tax system is greater when the financing is more progressive. If the share of taxes paid by high-income taxpayers remains the same, the efficiency cost of raising the revenue needed to finance the additional health spending is $1.48 per dollar of revenue collected, and GDP declines (relative to trend) by 11 percent. A proportional payroll tax has a lower efficiency cost (41 cents per dollar of revenue averaged over all tax hikes, a 5 percent drop in GDP) but more than doubles the share of the tax burden borne by lower income taxpayers. Empirical support for the model comes from analysis of OECD country data showing that countries facing higher tax burdens in 1979 experienced slower health care spending growth in subsequent decades. The rising burden imposed by the public financing of health care expenditures may therefore serve as a brake on health care spending growth. PMID:21608156

Importance of plasticity and local adaptation for coping with changing salinity in coastal areas: a test case with barnacles in the Baltic Sea

PubMed Central

2014-01-01

Background Salinity plays an important role in shaping coastal marine communities. Near-future climate predictions indicate that salinity will decrease in many shallow coastal areas due to increased precipitation; however, few studies have addressed this issue. The ability of ecosystems to cope with future changes will depend on species’ capacities to acclimatise or adapt to new environmental conditions. Here, we investigated the effects of a strong salinity gradient (the Baltic Sea system – Baltic, Kattegat, Skagerrak) on plasticity and adaptations in the euryhaline barnacle Balanus improvisus. We used a common-garden approach, where multiple batches of newly settled barnacles from each of three different geographical areas along the Skagerrak-Baltic salinity gradient were exposed to corresponding native salinities (6, 15 and 30 PSU), and phenotypic traits including mortality, growth, shell strength, condition index and reproductive maturity were recorded. Results We found that B. improvisus was highly euryhaline, but had highest growth and reproductive maturity at intermediate salinities. We also found that low salinity had negative effects on other fitness-related traits including initial growth and shell strength, although mortality was also lowest in low salinity. Overall, differences between populations in most measured traits were weak, indicating little local adaptation to salinity. Nonetheless, we observed some population-specific responses – notably that populations from high salinity grew stronger shells in their native salinity compared to the other populations, possibly indicating adaptation to differences in local predation pressure. Conclusions Our study shows that B. improvisus is an example of a true brackish-water species, and that plastic responses are more likely than evolutionary tracking in coping with future changes in coastal salinity. PMID:25038588

Analysis of turbulence and surface growth models on the estimation of soot level in ethylene non-premixed flames

NASA Astrophysics Data System (ADS)

Yunardi, Y.; Munawar, Edi; Rinaldi, Wahyu; Razali, Asbar; Iskandar, Elwina; Fairweather, M.

2018-02-01

Soot prediction in a combustion system has become a subject of attention, as many factors influence its accuracy. An accurate temperature prediction will likely yield better soot predictions, since the inception, growth and destruction of the soot are affected by the temperature. This paper reported the study on the influences of turbulence closure and surface growth models on the prediction of soot levels in turbulent flames. The results demonstrated that a substantial distinction was observed in terms of temperature predictions derived using the k-ɛ and the Reynolds stress models, for the two ethylene flames studied here amongst the four types of surface growth rate model investigated, the assumption of the soot surface growth rate proportional to the particle number density, but independent on the surface area of soot particles, f ( A s ) = ρ N s , yields in closest agreement with the radial data. Without any adjustment to the constants in the surface growth term, other approaches where the surface growth directly proportional to the surface area and square root of surface area, f ( A s ) = A s and f ( A s ) = √ A s , result in an under- prediction of soot volume fraction. These results suggest that predictions of soot volume fraction are sensitive to the modelling of surface growth.

Effects of consumption-oriented versus trophy-oriented fisheries on Muskellunge population size structure in northern Wisconsin

USGS Publications Warehouse

Faust, Matthew D.; Hansen, Michael J.

2016-01-01

To determine whether a consumption-oriented fishery was compatible with a trophy-oriented fishery for Muskellunge Esox masquinongy, we modeled effects of a spearing fishery and recreational angling fishery on population size structure (i.e., numbers of fish ≥ 102, 114, and 127 cm) in northern Wisconsin. An individual-based simulation model was used to quantify the effect of harvest mortality at currently observed levels of recreational angling and tribal spearing fishery exploitation, along with simulated increases in exploitation, for three typical growth potentials (i.e., low, moderate, and high) of Muskellunge in northern Wisconsin across a variety of minimum length limits (i.e., 71, 102, 114, and 127 cm). Populations with moderate to high growth potential and minimum length limits ≥ 114 cm were predicted to have lower declines in numbers of trophy Muskellunge when subjected to angling-only and mixed fisheries at observed and increased levels of exploitation, which suggested that fisheries with disparate motivations may be able to coexist under certain conditions such as restrictive length limits and low levels of exploitation. However, for most Muskellunge populations in northern Wisconsin regulated by a 102-cm minimum length limit, both angling and spearing fisheries may reduce numbers of trophy Muskellunge as larger declines were predicted across all growth potentials. Our results may be useful if Muskellunge management options in northern Wisconsin are re-examined in the future.

Development of Cardiovascular and Neurodevelopmental Metrics as Sublethal Endpoints for the Fish Embryo Toxicity Test.

PubMed

Krzykwa, Julie C; Olivas, Alexis; Jeffries, Marlo K Sellin

2018-06-19

The fathead minnow fish embryo toxicity (FET) test has been proposed as a more humane alternative to current toxicity testing methods, as younger organisms are thought to experience less distress during toxicant exposure. However, the FET test protocol does not include endpoints that allow for the prediction of sublethal adverse outcomes, limiting its utility relative to other test types. Researchers have proposed the development of sublethal endpoints for the FET test to increase its utility. The present study 1) developed methods for previously unmeasured sublethal metrics in fathead minnows (i.e., spontaneous contraction frequency and heart rate) and 2) investigated the responsiveness of several sublethal endpoints related to growth (wet weight, length, and growth-related gene expression), neurodevelopment (spontaneous contraction frequency, and neurodevelopmental gene expression), and cardiovascular function and development (pericardial area, eye size and cardiovascular related gene expression) as additional FET test metrics using the model toxicant 3,4-dichloroaniline. Of the growth, neurological and cardiovascular endpoints measured, length, eye size and pericardial area were found to more responsive than the other endpoints, respectively. Future studies linking alterations in these endpoints to longer-term adverse impacts are needed to fully evaluate the predictive power of these metrics in chemical and whole effluent toxicity testing. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Prediction of Lunar Reconnaissance Orbiter Reaction Wheel Assembly Angular Momentum Using Regression Analysis

NASA Technical Reports Server (NTRS)

DeHart, Russell

2017-01-01

This study determines the feasibility of creating a tool that can accurately predict Lunar Reconnaissance Orbiter (LRO) reaction wheel assembly (RWA) angular momentum, weeks or even months into the future. LRO is a three-axis stabilized spacecraft that was launched on June 18, 2009. While typically nadir-pointing, LRO conducts many types of slews to enable novel science collection. Momentum unloads have historically been performed approximately once every two weeks with the goal of maintaining system total angular momentum below 70 Nms; however flight experience shows the models developed before launch are overly conservative, with many momentum unloads being performed before system angular momentum surpasses 50 Nms. A more accurate model of RWA angular momentum growth would improve momentum unload scheduling and decrease the frequency of these unloads. Since some LRO instruments must be deactivated during momentum unloads and in the case of one instrument, decontaminated for 24 hours there after a decrease in the frequency of unloads increases science collection. This study develops a new model to predict LRO RWA angular momentum. Regression analysis of data from October 2014 to October 2015 was used to develop relationships between solar beta angle, slew specifications, and RWA angular momentum growth. The resulting model predicts RWA angular momentum using input solar beta angle and mission schedule data. This model was used to predict RWA angular momentum from October 2013 to October 2014. Predictions agree well with telemetry; of the 23 momentum unloads performed from October 2013 to October 2014, the mean and median magnitude of the RWA total angular momentum prediction error at the time of the momentum unloads were 3.7 and 2.7 Nms, respectively. The magnitude of the largest RWA total angular momentum prediction error was 10.6 Nms. Development of a tool that uses the models presented herein is currently underway.

Development of a predictive program for Vibrio parahaemolyticus growth under various environmental conditions.

PubMed

Fujikawa, Hiroshi; Kimura, Bon; Fujii, Tateo

2009-09-01

In this study, we developed a predictive program for Vibrio parahaemolyticus growth under various environmental conditions. Raw growth data was obtained with a V. parahaemolyticus O3:K6 strain cultured at a variety of broth temperatures, pH, and salt concentrations. Data were analyzed with our logistic model and the parameter values of the model were analyzed with polynomial equations. A prediction program consisting of the growth model and the polynomial equations was then developed. After the range of the growth environments was modified, the program successfully predicted the growth for all environments tested. The program could be a useful tool to ensure the bacteriological safety of seafood.

Phenological cues drive an apparent trade-off between freezing tolerance and growth in the family Salicaceae.

PubMed

Savage, Jessica A; Cavender-Bares, Jeannine

2013-08-01

With increasing concern about the ecological consequences of global climate change, there has been renewed interest in understanding the processes that determine species range limits. We tested a long-hypothesized trade-off between freezing tolerance and growth rate that is often used to explain species range limits. We grew 24 willow and poplar species (family Salicaceae) collected from across North America in a greenhouse common garden under two climate treatments. Maximum entropy models were used to describe species distributions and to estimate species-specific climate parameters. A range of traits related to freezing tolerance, including senescence, budburst, and susceptibility to different temperature minima during and after acclimation were measured. As predicted, species from colder climates exhibited higher freezing tolerance and slower growth rates than species from warmer climates under certain environmental conditions. However, the average relative growth rate (millimeters per meter per day) of northern species markedly increased when a subset of species was grown under a long summer day length (20.5 h), indicating that genetically based day-length cues are required for growth regulation in these species. We conclude that the observed relationship between freezing tolerance and growth rate is not driven by differences in species' intrinsic growth capacity but by differences in the environmental cues that trigger growth. We propose that the coordinated evolution of freezing tolerance and growth phenology could be important in circumscribing willow and poplar range limits and may have important implications for species' current and future distributions.

The Conditions under which Growth-Fostering Relationships Promote Resilience and Alleviate Psychological Distress among Sexual Minorities: Applications of Relational Cultural Theory

PubMed Central

Mereish, Ethan H.; Poteat, V. Paul

2015-01-01

Relational cultural theory posits that resilience and psychological growth are rooted in relational connections and are facilitated through growth-fostering relationships. Framed within this theory, the current study examined the associations between growth-fostering relationships (i.e., relationships characterized by authenticity and mutuality) with a close friend and psychological distress among sexual minorities. More specifically, we tested the moderating effects of individuals’ internalized homophobia and their friend’s sexual orientation on the associations between growth-fostering relationship with their close friend and level of psychological distress. A sample of sexual minorities (N = 661) were recruited online and completed a questionnaire. The 3-way interaction between (a) growth-fostering relationship with a close friend, (b) the close friend’s sexual orientation, and (c) internalized homophobia was significant in predicting psychological distress. Among participants with low levels of internalized homophobia, a stronger growth-fostering relationship with a close heterosexual or LGBT friend was associated with less psychological distress. Among participants with high levels of internalized homophobia, a stronger growth-fostering relationship with a close LGBT friend was associated with less psychological distress but not with a heterosexual friend. Our results demonstrate that growth-fostering relationships may be associated with less psychological distress but under specific conditions. These findings illuminate a potential mechanism for sexual minorities’ resilience and provide support for relational cultural theory. Understanding resilience factors among sexual minorities is critical for culturally sensitive and affirmative clinical practice and future research. PMID:26380836

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.

Challenges associated with projecting urbanization-induced heat-related mortality.

PubMed

Hondula, David M; Georgescu, Matei; Balling, Robert C

2014-08-15

Maricopa County, Arizona, anchor to the fastest growing megapolitan area in the United States, is located in a hot desert climate where extreme temperatures are associated with elevated risk of mortality. Continued urbanization in the region will impact atmospheric temperatures and, as a result, potentially affect human health. We aimed to quantify the number of excess deaths attributable to heat in Maricopa County based on three future urbanization and adaptation scenarios and multiple exposure variables. Two scenarios (low and high growth projections) represent the maximum possible uncertainty range associated with urbanization in central Arizona, and a third represents the adaptation of high-albedo cool roof technology. Using a Poisson regression model, we related temperature to mortality using data spanning 1983-2007. Regional climate model simulations based on 2050-projected urbanization scenarios for Maricopa County generated distributions of temperature change, and from these predicted changes future excess heat-related mortality was estimated. Subject to urbanization scenario and exposure variable utilized, projections of heat-related mortality ranged from a decrease of 46 deaths per year (-95%) to an increase of 339 deaths per year (+359%). Projections based on minimum temperature showed the greatest increase for all expansion and adaptation scenarios and were substantially higher than those for daily mean temperature. Projections based on maximum temperature were largely associated with declining mortality. Low-growth and adaptation scenarios led to the smallest increase in predicted heat-related mortality based on mean temperature projections. Use of only one exposure variable to project future heat-related deaths may therefore be misrepresentative in terms of direction of change and magnitude of effects. Because urbanization-induced impacts can vary across the diurnal cycle, projections of heat-related health outcomes that do not consider place-based, time-varying urban heat island effects are neglecting essential elements for policy relevant decision-making. Copyright © 2014 Elsevier B.V. All rights reserved.

An energy-economy-environment model for simulating the impacts of socioeconomic development on energy and environment.

PubMed

Wang, Wenyi; Zeng, Weihua; Yao, Bo

2014-01-01

Many rapidly developing regions have begun to draw the attention of the world. Meanwhile, the energy and environmental issues associated with rapid economic growth have aroused widespread critical concern. Therefore, studying energy, economic, and environmental systems is of great importance. This study establishes a system dynamic model that covers multiple aspects of those systems, such as energy, economy, population, water pollution, air pollution, solid waste, and technology. The model designed here attempts to determine the impacts of socioeconomic development on the energy and environment of Tongzhou District in three scenarios: under current, planning, and sustainable conditions. The results reveal that energy shortages and water pollutions are very serious and are the key issues constraining future social and economic development. Solid waste emissions increase with population growth. The prediction results provide valuable insights into social advancement.

Gas in the land of Gauchos

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

Kelley, T.

The author discusses the natural gas industry in Argentina. Despite a troubled past, Argentina looks toward a future brightened by the growing prominence of natural gas use. A state-run company, Gas del Estado, controls the exploration, production, transmission and distribution of natural gas. Natural gas reserves, measured in tons of oil equivalent, grew from 51 percent of oil reserves in 1970 to 187 percent in 1983. This growth is expected to continue with gas reserves predicted to nearly triple in absolute terms to 70 Tcf, by the turn of the century. This article discusses some of the problems that Argentinamore » has in using its natural gas. The immediate obstacle is one of funds. Gas del Estado has no technical limitations but may be handicapped in its growth by economic and financial problems.« less

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.

Tracing children's vocabulary development from preschool through the school-age years: An 8-year longitudinal study

PubMed Central

Kang, Cuiping; Liu, Hongyun; Zhang, Yuping; McBride-Chang, Catherine; Tardif, Twila; Li, Hong; Liang, Weilan; Zhang, Zhixiang; Shu, Hua

2014-01-01

In this 8-year longitudinal study, we traced the vocabulary growth of Chinese children, explored potential precursors of vocabulary knowledge, and investigated how vocabulary growth predicted future reading skills. Two hundred sixty-four (264) native Chinese children from Beijing were measured on a variety of reading and language tasks over 8 years. Between the ages of 4 to 10 years, they were administered tasks of vocabulary and related cognitive skills. At age 11, comprehensive reading skills, including character recognition, reading fluency, and reading comprehension were examined. Individual differences in vocabulary developmental profiles were estimated using the intercept-slope cluster method. Vocabulary development was then examined in relation to later reading outcomes. Three subgroups of lexical growth were classified, namely high-high (with a large initial vocabulary size and a fast growth rate), low-high (with a small initial vocabulary size and a fast growth rate) and low-low (with a small initial vocabulary size and a slow growth rate) groups. Low-high and low-low groups were distinguishable mostly through phonological skills, morphological skills and other reading-related cognitive skills. Childhood vocabulary development (using intercept and slope) explained subsequent reading skills. Findings suggest that language-related and reading-related cognitive skills differ among groups with different developmental trajectories of vocabulary, and the initial size and growth rate of vocabulary may be two predictors for later reading development. PMID:24962559

Simulation of growth of Adirondack conifers in relation to global climate change

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

Pan, Y.; Raynal, D.J.

1993-06-01

Several conifer species grown in plantations in the southeastern Adirondack mountains of New York were chosen to model tree growth. In the models, annual xylem growth was decomposed into several components that reflect various intrinsic or extrinsic factors. Growth signals indicative of climatic effects were used to construct response functions using both multivariate analysis and Kalman filter methods. Two models were used to simulate tree growth response to future CO[sub 2]-induced climate change projected by GCMs. The comparable results of both models indicate that different conifer species have individualistic growth responses to future climatic change. The response behaviors of treesmore » are affected greatly by local stand conditions. The results suggest possible changes in future growth and distributions of naturally occurring conifers in this region.« less

Gravitational entropy and the cosmological no-hair conjecture

NASA Astrophysics Data System (ADS)

Bolejko, Krzysztof

2018-04-01

The gravitational entropy and no-hair conjectures seem to predict contradictory future states of our Universe. The growth of the gravitational entropy is associated with the growth of inhomogeneity, while the no-hair conjecture argues that a universe dominated by dark energy should asymptotically approach a homogeneous and isotropic de Sitter state. The aim of this paper is to study these two conjectures. The investigation is based on the Simsilun simulation, which simulates the universe using the approximation of the Silent Universe. The Silent Universe is a solution to the Einstein equations that assumes irrotational, nonviscous, and insulated dust, with vanishing magnetic part of the Weyl curvature. The initial conditions for the Simsilun simulation are sourced from the Millennium simulation, which results with a realistically appearing but relativistic at origin simulation of a universe. The Simsilun simulation is evolved from the early universe (t =25 Myr ) until far future (t =1000 Gyr ). The results of this investigation show that both conjectures are correct. On global scales, a universe with a positive cosmological constant and nonpositive spatial curvature does indeed approach the de Sitter state. At the same time it keeps generating the gravitational entropy.

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.

Comparison of Swirl Sign and Black Hole Sign in Predicting Early Hematoma Growth in Patients with Spontaneous Intracerebral Hemorrhage.

PubMed

Xiong, Xin; Li, Qi; Yang, Wen-Song; Wei, Xiao; Hu, Xi; Wang, Xing-Chen; Zhu, Dan; Li, Rui; Cao, Du; Xie, Peng

2018-01-29

BACKGROUND Early hematoma growth is associated with poor outcome in patients with spontaneous intracerebral hemorrhage (ICH). The swirl sign (SS) and the black hole sign (BHS) are imaging markers in ICH patients. The aim of this study was to compare the predictive value of these 2 signs for early hematoma growth. MATERIAL AND METHODS ICH patients were screened for the appearance of the 2 signs within 6 h after onset of symptoms. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the 2 signs in predicting early hematoma growth were assessed. The accuracy of the 2 signs in predicting early hematoma growth was analyzed by receiver-operator analysis. RESULTS A total of 200 patients were enrolled in this study. BHS was found in 30 (15%) patients, and SS was found in 70 (35%) patients. Of the 71 patients with early hematoma growth, BHS was found on initial computed tomography scans in 24 (33.8%) and SS in 33 (46.5%). The sensitivity, specificity, PPV, and NPV of BHS for predicting early hematoma growth were 33.8%, 95.3%, 80.0%, and 72.0%, respectively. The sensitivity, specificity, PPV, and NPV of SS were 46.5%, 71.3%, 47.0%, and 71.0%, respectively. The area under the curve was 0.646 for BHS and 0.589 for SS (P=0.08). Multivariate logistic regression showed that presence of BHS is an independent predictor of early hematoma growth. CONCLUSIONS The Black hole sign seems to be good predictor for hematoma growth. The presence of swirl sign on admission CT does not independently predict hematoma growth in patients with ICH.

Predicting Development of Mathematical Word Problem Solving Across the Intermediate Grades

PubMed Central

Tolar, Tammy D.; Fuchs, Lynn; Cirino, Paul T.; Fuchs, Douglas; Hamlett, Carol L.; Fletcher, Jack M.

2012-01-01

This study addressed predictors of the development of word problem solving (WPS) across the intermediate grades. At beginning of 3rd grade, 4 cohorts of students (N = 261) were measured on computation, language, nonverbal reasoning skills, and attentive behavior and were assessed 4 times from beginning of 3rd through end of 5th grade on 2 measures of WPS at low and high levels of complexity. Language skills were related to initial performance at both levels of complexity and did not predict growth at either level. Computational skills had an effect on initial performance in low- but not high-complexity problems and did not predict growth at either level of complexity. Attentive behavior did not predict initial performance but did predict growth in low-complexity, whereas it predicted initial performance but not growth for high-complexity problems. Nonverbal reasoning predicted initial performance and growth for low-complexity WPS, but only growth for high-complexity WPS. This evidence suggests that although mathematical structure is fixed, different cognitive resources may act as limiting factors in WPS development when the WPS context is varied. PMID:23325985

Black Hole Sign: Novel Imaging Marker That Predicts Hematoma Growth in Patients With Intracerebral Hemorrhage.

PubMed

Li, Qi; Zhang, Gang; Xiong, Xin; Wang, Xing-Chen; Yang, Wen-Song; Li, Ke-Wei; Wei, Xiao; Xie, Peng

2016-07-01

Early hematoma growth is a devastating neurological complication after intracerebral hemorrhage. We aim to report and evaluate the usefulness of computed tomography (CT) black hole sign in predicting hematoma growth in patients with intracerebral hemorrhage. Patients with intracerebral hemorrhage were screened for the presence of CT black hole sign on admission head CT performed within 6 hours after onset of symptoms. The black hole sign was defined as hypoattenuatting area encapsulated within the hyperattenuating hematoma with a clearly defined border. The sensitivity, specificity, and positive and negative predictive values of CT black hole sign in predicting hematoma expansion were calculated. Logistic regression analyses were used to assess the presence of the black hole sign and early hematoma growth. A total of 206 patients were enrolled. Black hole sign was found in 30 (14.6%) of 206 patients on the baseline CT scan. The black hole sign was more common in patients with hematoma growth (31.9%) than those without hematoma growth (5.8%; P<0.001). The sensitivity, specificity, positive predictive value, and negative predictive value of back hole sign in predicting early hematoma growth were 31.9%, 94.1%, 73.3%, and 73.2%, respectively. The time-to-admission CT scan, baseline hematoma volume, and the presence of black hole sign on admission CT independently predict hematoma growth in multivariate model. The CT black hole sign could be used as a simple and easy-to-use predictor for early hematoma growth in patients with intracerebral hemorrhage. © 2016 American Heart Association, Inc.

Are trait-growth models transferable? Predicting multi-species growth trajectories between ecosystems using plant functional traits

PubMed Central

Vesk, Peter A.

2017-01-01

Plant functional traits are increasingly used to generalize across species, however few examples exist of predictions from trait-based models being evaluated in new species or new places. Can we use functional traits to predict growth of unknown species in different areas? We used three independently collected datasets, each containing data on heights of individuals from non-resprouting species over a chronosquence of time-since-fire sites from three ecosystems in south-eastern Australia. We examined the influence of specific leaf area, woody density, seed size and leaf nitrogen content on three aspects of plant growth; maximum relative growth rate, age at maximum growth and asymptotic height. We tested our capacity to perform out-of-sample prediction of growth trajectories between ecosystems using species functional traits. We found strong trait-growth relationships in one of the datasets; whereby species with low SLA achieved the greatest asymptotic heights, species with high leaf-nitrogen content achieved relatively fast growth rates, and species with low seed mass reached their time of maximum growth early. However these same growth-trait relationships did not hold across the two other datasets, making accurate prediction from one dataset to another unachievable. We believe there is evidence to suggest that growth trajectories themselves may be fundamentally different between ecosystems and that trait-height-growth relationships may change over environmental gradients. PMID:28486535

Why Be a Shrub? A Basic Model and Hypotheses for the Adaptive Values of a Common Growth Form

PubMed Central

Götmark, Frank; Götmark, Elin; Jensen, Anna M.

2016-01-01

Shrubs are multi-stemmed short woody plants, more widespread than trees, important in many ecosystems, neglected in ecology compared to herbs and trees, but currently in focus due to their global expansion. We present a novel model based on scaling relationships and four hypotheses to explain the adaptive significance of shrubs, including a review of the literature with a test of one hypothesis. Our model describes advantages for a small shrub compared to a small tree with the same above-ground woody volume, based on larger cross-sectional stem area, larger area of photosynthetic tissue in bark and stem, larger vascular cambium area, larger epidermis (bark) area, and larger area for sprouting, and faster production of twigs and canopy. These components form our Hypothesis 1 that predicts higher growth rate for a small shrub than a small tree. This prediction was supported by available relevant empirical studies (14 publications). Further, a shrub will produce seeds faster than a tree (Hypothesis 2), multiple stems in shrubs insure future survival and growth if one or more stems die (Hypothesis 3), and three structural traits of short shrub stems improve survival compared to tall tree stems (Hypothesis 4)—all hypotheses have some empirical support. Multi-stemmed trees may be distinguished from shrubs by more upright stems, reducing bending moment. Improved understanding of shrubs can clarify their recent expansion on savannas, grasslands, and alpine heaths. More experiments and other empirical studies, followed by more elaborate models, are needed to understand why the shrub growth form is successful in many habitats. PMID:27507981

High-Temperature Cast Aluminum for Efficient Engines

NASA Astrophysics Data System (ADS)

Bobel, Andrew C.

Accurate thermodynamic databases are the foundation of predictive microstructure and property models. An initial assessment of the commercially available Thermo-Calc TCAL2 database and the proprietary aluminum database of QuesTek demonstrated a large degree of deviation with respect to equilibrium precipitate phase prediction in the compositional region of interest when compared to 3-D atom probe tomography (3DAPT) and transmission electron microscopy (TEM) experimental results. New compositional measurements of the Q-phase (Al-Cu-Mg-Si phase) led to a remodeling of the Q-phase thermodynamic description in the CALPHAD databases which has produced significant improvements in the phase prediction capabilities of the thermodynamic model. Due to the unique morphologies of strengthening precipitate phases commonly utilized in high-strength cast aluminum alloys, the development of new microstructural evolution models to describe both rod and plate particle growth was critical for accurate mechanistic strength models which rely heavily on precipitate size and shape. Particle size measurements through both 3DAPT and TEM experiments were used in conjunction with literature results of many alloy compositions to develop a physical growth model for the independent prediction of rod radii and rod length evolution. In addition a machine learning (ML) model was developed for the independent prediction of plate thickness and plate diameter evolution as a function of alloy composition, aging temperature, and aging time. The developed models are then compared with physical growth laws developed for spheres and modified for ellipsoidal morphology effects. Analysis of the effect of particle morphology on strength enhancement has been undertaken by modification of the Orowan-Ashby equation for 〈110〉 alpha-Al oriented finite rods in addition to an appropriate version for similarly oriented plates. A mechanistic strengthening model was developed for cast aluminum alloys containing both rod and plate-like precipitates. The model accurately accounts for the temperature dependence of particle nucleation and growth, solid solution strengthening, Si eutectic strength, and base aluminum yield strength. Strengthening model predictions of tensile yield strength are in excellent agreement with experimental observations over a wide range of aluminum alloy systems, aging temperatures, and test conditions. The developed models enable the prediction of the required particle morphology and volume fraction necessary to achieve target property goals in the design of future aluminum alloys. The effect of partitioning elements to the Q-phase was also considered for the potential to control the nucleation rate, reduce coarsening, and control the evolution of particle morphology. Elements were selected based on density functional theory (DFT) calculations showing the prevalence of certain elements to partition to the Q-phase. 3DAPT experiments were performed on Q-phase containing wrought alloys with these additions and show segregation of certain elements to the Q-phase with relative agreement to DFT predictions.

Temperature requirements of Atlantic salmon Salmo salar, brown trout Salmo trutta and Arctic charr Salvelinus alpinus: predicting the effects of climate change.

PubMed

Elliott, J M; Elliott, J A

2010-11-01

Atlantic salmon Salmo salar, brown trout Salmo trutta (including the anadromous form, sea trout) and Arctic charr Salvelinus alpinus (including anadromous fish) provide important commercial and sports fisheries in Western Europe. As water temperature increases as a result of climate change, quantitative information on the thermal requirements of these three species is essential so that potential problems can be anticipated by those responsible for the conservation and sustainable management of the fisheries and the maintenance of biodiversity in freshwater ecosystems. Part I compares the temperature limits for survival, feeding and growth. Salmo salar has the highest temperature tolerance, followed by S. trutta and finally S. alpinus. For all three species, the temperature tolerance for alevins is slightly lower than that for parr and smolts, and the eggs have the lowest tolerance; this being the most vulnerable life stage to any temperature increase, especially for eggs of S. alpinus in shallow water. There was little evidence to support local thermal adaptation, except in very cold rivers (mean annual temperature <6·5° C). Part II illustrates the importance of developing predictive models, using data from a long-term study (1967-2000) of a juvenile anadromous S. trutta population. Individual-based models predicted the emergence period for the fry. Mean values over 34 years revealed a large variation in the timing of emergence with c. 2 months between extreme values. The emergence time correlated significantly with the North Atlantic Oscillation Index, indicating that interannual variations in emergence were linked to more general changes in climate. Mean stream temperatures increased significantly in winter and spring at a rate of 0·37° C per decade, but not in summer and autumn, and led to an increase in the mean mass of pre-smolts. A growth model for S. trutta was validated by growth data from the long-term study and predicted growth under possible future conditions. Small increases (<2·5° C) in winter and spring would be beneficial for growth with 1 year-old smolts being more common. Water temperatures would have to increase by c. 4° C in winter and spring, and 3° C in summer and autumn before they had a marked negative effect on trout growth. © 2010 The Authors. Journal of Fish Biology © 2010 The Fisheries Society of the British Isles.

Differences in extreme low salinity timing and duration differentially affect eastern oyster (Crassostrea virginica) size class growth and mortality in Breton Sound, LA

NASA Astrophysics Data System (ADS)

La Peyre, Megan K.; Eberline, Benjamin S.; Soniat, Thomas M.; La Peyre, Jerome F.

2013-12-01

Understanding how different life history stages are impacted by extreme or stochastic environmental variation is critical for predicting and modeling organism population dynamics. This project examined recruitment, growth, and mortality of seed (25-75 mm) and market (>75 mm) sized oysters along a salinity gradient over two years in Breton Sound, LA. In April 2010, management responses to the Deepwater Horizon oil spill resulted in extreme low salinity (<5) at all sites through August 2010; in 2011, a 100-year Mississippi River flood event resulted in low salinity in late spring. Extended low salinity (<5) during hot summer months (>25 °C) significantly and negatively impacted oyster recruitment, survival and growth in 2010, while low salinity (<5) for a shorter period that did not extend into July (<25 °C) in 2011 had minimal impacts on oyster growth and mortality. In 2011, recruitment was limited, which may be due to a combination of low spring time salinities, high 2010 oyster mortality, minimal 2010 recruitment, cumulative effects from 10 years of declining oyster stock in the area, and poor cultch quality. In both 2010 and 2011, Perkinsus marinus infection prevalence remained low throughout the year at all sites and almost all infection intensities were light. Oyster plasma osmolality failed to match surrounding low salinity waters in 2010, while oysters appeared to osmoconform throughout 2011 indicating that the high mortality in 2010 may be due to extended valve closing and resulting starvation or asphyxiation in response to the combination of low salinity during high temperatures (>25 °C). With increasing management of our freshwater inputs to estuaries combined with predicted climate changes, how extreme events affect different life history stages is key to understanding variation in population demographics of commercially important species and predicting future populations.

Differences in extreme low salinity timing and duration differentially affect eastern oyster (Crassostrea virginica) size class growth and mortality in Breton Sound, LA

USGS Publications Warehouse

LaPeyre, Megan K.; Eberline, Benjamin S.; Soniat, Thomas M.; La Peyre, Jerome F.

2013-01-01

Understanding how different life history stages are impacted by extreme or stochastic environmental variation is critical for predicting and modeling organism population dynamics. This project examined recruitment, growth, and mortality of seed (25–75 mm) and market (>75 mm) sized oysters along a salinity gradient over two years in Breton Sound, LA. In April 2010, management responses to the Deepwater Horizon oil spill resulted in extreme low salinity (<5) at all sites through August 2010; in 2011, a 100-year Mississippi River flood event resulted in low salinity in late spring. Extended low salinity (<5) during hot summer months (>25 °C) significantly and negatively impacted oyster recruitment, survival and growth in 2010, while low salinity (<5) for a shorter period that did not extend into July (<25 °C) in 2011 had minimal impacts on oyster growth and mortality. In 2011, recruitment was limited, which may be due to a combination of low spring time salinities, high 2010 oyster mortality, minimal 2010 recruitment, cumulative effects from 10 years of declining oyster stock in the area, and poor cultch quality. In both 2010 and 2011, Perkinsus marinusinfection prevalence remained low throughout the year at all sites and almost all infection intensities were light. Oyster plasma osmolality failed to match surrounding low salinity waters in 2010, while oysters appeared to osmoconform throughout 2011 indicating that the high mortality in 2010 may be due to extended valve closing and resulting starvation or asphyxiation in response to the combination of low salinity during high temperatures (>25 °C). With increasing management of our freshwater inputs to estuaries combined with predicted climate changes, how extreme events affect different life history stages is key to understanding variation in population demographics of commercially important species and predicting future populations.

Assessing the effects of management on forest growth across France: insights from a new functional-structural model.

PubMed

Guillemot, Joannès; Delpierre, Nicolas; Vallet, Patrick; François, Christophe; Martin-StPaul, Nicolas K; Soudani, Kamel; Nicolas, Manuel; Badeau, Vincent; Dufrêne, Eric

2014-09-01

The structure of a forest stand, i.e. the distribution of tree size features, has strong effects on its functioning. The management of the structure is therefore an important tool in mitigating the impact of predicted changes in climate on forests, especially with respect to drought. Here, a new functional-structural model is presented and is used to assess the effects of management on forest functioning at a national scale. The stand process-based model (PBM) CASTANEA was coupled to a stand structure module (SSM) based on empirical tree-to-tree competition rules. The calibration of the SSM was based on a thorough analysis of intersite and interannual variability of competition asymmetry. The coupled CASTANEA-SSM model was evaluated across France using forest inventory data, and used to compare the effect of contrasted silvicultural practices on simulated stand carbon fluxes and growth. The asymmetry of competition varied consistently with stand productivity at both spatial and temporal scales. The modelling of the competition rules enabled efficient prediction of changes in stand structure within the CASTANEA PBM. The coupled model predicted an increase in net primary productivity (NPP) with management intensity, resulting in higher growth. This positive effect of management was found to vary at a national scale across France: the highest increases in NPP were attained in forests facing moderate to high water stress; however, the absolute effect of management on simulated stand growth remained moderate to low because stand thinning involved changes in carbon allocation at the tree scale. This modelling approach helps to identify the areas where management efforts should be concentrated in order to mitigate near-future drought impact on national forest productivity. Around a quarter of the French temperate oak and beech forests are currently in zones of high vulnerability, where management could thus mitigate the influence of climate change on forest yield.

Modeling a failure criterion for U-Mo/Al dispersion fuel

NASA Astrophysics Data System (ADS)

Oh, Jae-Yong; Kim, Yeon Soo; Tahk, Young-Wook; Kim, Hyun-Jung; Kong, Eui-Hyun; Yim, Jeong-Sik

2016-05-01

The breakaway swelling in U-Mo/Al dispersion fuel is known to be caused by large pore formation enhanced by interaction layer (IL) growth between fuel particles and Al matrix. In this study, a critical IL thickness was defined as a criterion for the formation of a large pore in U-Mo/Al dispersion fuel. Specifically, the critical IL thickness is given when two neighboring fuel particles come into contact with each other in the developed IL. The model was verified using the irradiation data from the RERTR tests and KOMO-4 test. The model application to full-sized sample irradiations such as IRISs, FUTURE, E-FUTURE, and AFIP-1 tests resulted in conservative predictions. The parametric study revealed that the fuel particle size and the homogeneity of the fuel particle distribution are influential for fuel performance.

Recent trends and future of pharmaceutical packaging technology

PubMed Central

Zadbuke, Nityanand; Shahi, Sadhana; Gulecha, Bhushan; Padalkar, Abhay; Thube, Mahesh

2013-01-01

The pharmaceutical packaging market is constantly advancing and has experienced annual growth of at least five percent per annum in the past few years. The market is now reckoned to be worth over $20 billion a year. As with most other packaged goods, pharmaceuticals need reliable and speedy packaging solutions that deliver a combination of product protection, quality, tamper evidence, patient comfort and security needs. Constant innovations in the pharmaceuticals themselves such as, blow fill seal (BFS) vials, anti-counterfeit measures, plasma impulse chemical vapor deposition (PICVD) coating technology, snap off ampoules, unit dose vials, two-in-one prefilled vial design, prefilled syringes and child-resistant packs have a direct impact on the packaging. The review details several of the recent pharmaceutical packaging trends that are impacting packaging industry, and offers some predictions for the future. PMID:23833515

Predicting the Spatial Distribution of Aspen Growth Potential in the Upper Great Lakes Region

Treesearch

Eric J. Gustafson; Sue M. Lietz; John L. Wright

2003-01-01

One way to increase aspen yields is to produce aspen on sites where aspen growth potential is highest. Aspen growth rates are typically predicted using site index, but this is impractical for landscape-level assessments. We tested the hypothesis that aspen growth can be predicted from site and climate variables and generated a model to map the spatial variability of...

Quantifying the influence of CO2 seasonality on future aragonite undersaturation onset

NASA Astrophysics Data System (ADS)

Sasse, T. P.; McNeil, B. I.; Matear, R. J.; Lenton, A.

2015-10-01

Ocean acidification is a predictable consequence of rising atmospheric carbon dioxide (CO2), and is highly likely to impact the entire marine ecosystem - from plankton at the base of the food chain to fish at the top. Factors which are expected to be impacted include reproductive health, organism growth and species composition and distribution. Predicting when critical threshold values will be reached is crucial for projecting the future health of marine ecosystems and for marine resources planning and management. The impacts of ocean acidification will be first felt at the seasonal scale, however our understanding how seasonal variability will influence rates of future ocean acidification remains poorly constrained due to current model and data limitations. To address this issue, we first quantified the seasonal cycle of aragonite saturation state utilizing new data-based estimates of global ocean-surface dissolved inorganic carbon and alkalinity. This seasonality was then combined with earth system model projections under different emissions scenarios (representative concentration pathways; RCPs 2.6, 4.5 and 8.5) to provide new insights into future aragonite undersaturation onset. Under a high emissions scenario (RCP 8.5), our results suggest accounting for seasonality will bring forward the initial onset of month-long undersaturation by 17 ± 10 years compared to annual-mean estimates, with differences extending up to 35 ± 16 years in the North Pacific due to strong regional seasonality. This earlier onset will result in large-scale undersaturation once atmospheric CO2 reaches 496 ppm in the North Pacific and 511 ppm in the Southern Ocean, independent of emission scenario. This work suggests accounting for seasonality is critical to projecting the future impacts of ocean acidification on the marine environment.

Comparative assessment for future prediction of urban water environment using WEAP model: A case study of Kathmandu, Manila and Jakarta

NASA Astrophysics Data System (ADS)

Kumar, Pankaj; Yoshifumi, Masago; Ammar, Rafieiemam; Mishra, Binaya; Fukushi, Ken

2017-04-01

Uncontrolled release of pollutants, increasing extreme weather condition, rapid urbanization and poor governance posing a serious threat to sustainable water resource management in developing urban spaces. Considering half of the world's mega-cities are in the Asia and the Pacific with 1.7 billion people do not access to improved water and sanitation, water security through its proper management is both an increasing concern and an imperative critical need. This research work strives to give a brief glimpse about predicted future water environment in Bagmati, Pasig and Ciliwung rivers from three different cities viz. Manila, Kathmandu and Jakarta respectively. Hydrological model used here to foresee the collective impacts of rapid population growth because of urbanization as well as climate change on unmet demand and water quality in near future time by 2030. All three rivers are major source of water for different usage viz. domestic, industrial, agriculture and recreation but uncontrolled withdrawal and sewerage disposal causing deterioration of water environment in recent past. Water Evaluation and Planning (WEAP) model was used to model river water quality pollution future scenarios using four indicator species i.e. Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD) and Nitrate (NO3). Result for simulated water quality as well as unmet demand for year 2030 when compared with that of reference year clearly indicates that not only water quality deteriorates but also unmet demands is increasing in future course of time. This also suggests that current initiatives and policies for water resource management are not sufficient enough and hence immediate and inclusive action through transdisciplinary research.

Importance of vegetation distribution for future carbon balance

NASA Astrophysics Data System (ADS)

Ahlström, A.; Xia, J.; Arneth, A.; Luo, Y.; Smith, B.

2015-12-01

Projections of future terrestrial carbon uptake vary greatly between simulations. Net primary production (NPP), wild fires, vegetation dynamics (including biome shifts) and soil decomposition constitute the main processes governing the response of the terrestrial carbon cycle in a changing climate. While primary production and soil respiration are relatively well studied and implemented in all global ecosystem models used to project the future land sink of CO2, vegetation dynamics are less studied and not always represented in global models. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality and the associated turnover and proven skill in predicting vegetation distribution and succession. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the CMIP5 ensemble under RCP8.5 radiative forcing at year 2085. We exchanged carbon cycle processes between these 13 simulations and investigate the changes predicted by the emulator. This method allowed us to partition the entire ensemble carbon uptake uncertainty into individual processes. We found that NPP, vegetation dynamics (including biome shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33% respectively of uncertainties in modeled global C-uptake. Uncertainty due to vegetation dynamics was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by shifts in vegetation distribution, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.

Predicted Water and Carbon Fluxes as well as Vegetation Distribution on the Korean Peninsula in the Future with the Ecosystem Demography Model version 2

NASA Astrophysics Data System (ADS)

Kim, J. B.; Kim, Y.

2017-12-01

This study investigates how the water and carbon fluxes as well as vegetation distribution on the Korean peninsula would vary with climate change. Ecosystem Demography (ED) Model version 2 (ED2) is used in this study, which is an integrated terrestrial biosphere model that can utilize a set of size- and age- structured partial differential equations that track the changing structure and composition of the plant canopy. With using the vegetation distribution data of Jeju Island, located at the southern part of the Korean Peninsula, ED2 is setup and driven for the past 10 years. Then the results of ED2 are evaluated and adjusted with observed forestry data, i.e., growth and mortality, and the flux tower and MODIS satellite data, i.e., evapotranspiration (ET) and gross primary production (GPP). This adjusted ED2 are used to simulate the water and carbon fluxes as well as vegetation dynamics in the Korean Peninsula for the historical period with evaluating the model against the MODIS satellite data. Finally, the climate scenarios of RCP 2.6 and 6.0 are used to predict the fluxes and vegetation distribution of the Korean Peninsula in the future. With using the state-of-art terrestrial ecosystem model, this study would provide us better understanding of the future ecosystem vulnerability of the Korean Peninsula. AcknowledgementsThis work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2015R1C1A2A01054800) and by the Korea Meteorological Administration R&D Program under Grant KMIPA 2015-6180. This work was also supported by the Yonsei University Future-leading Research Initiative of 2015(2016-22-0061).

Evaluating land-use change scenarios for the Puget Sound Basin, Washington, within the ecosystem recovery target model-based framework

USGS Publications Warehouse

Villarreal, Miguel; Labiosa, Bill; Aiello, Danielle

2017-05-23

The Puget Sound Basin, Washington, has experienced rapid urban growth in recent decades, with varying impacts to local ecosystems and natural resources. To plan for future growth, land managers often use scenarios to assess how the pattern and volume of growth may affect natural resources. Using three different land-management scenarios for the years 2000–2060, we assessed various spatial patterns of urban growth relative to maps depicting a model-based characterization of the ecological integrity and recent development pressure of individual land parcels. The three scenarios depict future trajectories of land-use change under alternative management strategies—status quo, managed growth, and unconstrained growth. The resulting analysis offers a preliminary assessment of how future growth patterns in the Puget Sound Basin may impact land targeted for conservation and how short-term metrics of land-development pressure compare to longer term growth projections.

Predicting Transition from Laminar to Turbulent Flow over a Surface

NASA Technical Reports Server (NTRS)

Sturdza, Peter (Inventor); Rajnarayan, Dev (Inventor)

2013-01-01

A prediction of whether a point on a computer-generated surface is adjacent to laminar or turbulent flow is made using a transition prediction technique. A plurality of boundary-layer properties at the point are obtained from a steady-state solution of a fluid flow in a region adjacent to the point. A plurality of instability modes are obtained, each defined by one or more mode parameters. A vector of regressor weights is obtained for the known instability growth rates in a training dataset. For each instability mode in the plurality of instability modes, a covariance vector is determined, which is the covariance of a predicted local growth rate with the known instability growth rates. Each covariance vector is used with the vector of regressor weights to determine a predicted local growth rate at the point. Based on the predicted local growth rates, an n-factor envelope at the point is determined.

Prediction of pathogen growth on iceberg lettuce under real temperature history during distribution from farm to table.

PubMed

Koseki, Shigenobu; Isobe, Seiichiro

2005-10-25

The growth of pathogenic bacteria Escherichia coli O157:H7, Salmonella spp., and Listeria monocytogenes on iceberg lettuce under constant and fluctuating temperatures was modelled in order to estimate the microbial safety of this vegetable during distribution from the farm to the table. Firstly, we examined pathogen growth on lettuce at constant temperatures, ranging from 5 to 25 degrees C, and then we obtained the growth kinetic parameters (lag time, maximum growth rate (micro(max)), and maximum population density (MPD)) using the Baranyi primary growth model. The parameters were similar to those predicted by the pathogen modelling program (PMP), with the exception of MPD. The MPD of each pathogen on lettuce was 2-4 log(10) CFU/g lower than that predicted by PMP. Furthermore, the MPD of pathogens decreased with decreasing temperature. The relationship between mu(max) and temperature was linear in accordance with Ratkowsky secondary model as was the relationship between the MPD and temperature. Predictions of pathogen growth under fluctuating temperature used the Baranyi primary microbial growth model along with the Ratkowsky secondary model and MPD equation. The fluctuating temperature profile used in this study was the real temperature history measured during distribution from the field at harvesting to the retail store. Overall predictions for each pathogen agreed well with observed viable counts in most cases. The bias and root mean square error (RMSE) of the prediction were small. The prediction in which mu(max) was based on PMP showed a trend of overestimation relative to prediction based on lettuce. However, the prediction concerning E. coli O157:H7 and Salmonella spp. on lettuce greatly overestimated growth in the case of a temperature history starting relatively high, such as 25 degrees C for 5 h. In contrast, the overall prediction of L. monocytogenes under the same circumstances agreed with the observed data.

Behavioral Attention: A Longitudinal Study of Whether and How It Influences the Development of Word Reading and Reading Comprehension among At-Risk Readers

PubMed Central

Miller, Amanda C.; Fuchs, Douglas; Fuchs, Lynn S.; Compton, Donald L.; Kearns, Devin; Zhang, Wenjuan; Yen, Loulee; Patton, Samuel; Kirchner, Danielle

2014-01-01

The purpose of this study was to examine the extent to which teacher ratings of behavioral attention predicted responsiveness to word reading instruction in first grade and third-grade reading comprehension performance. Participants were 110 first grade students identified as at-risk for reading difficulties who received 20 weeks of intensive reading intervention in combination with classroom reading instruction. Path analysis indicated that teacher ratings of student attention significantly predicted students’ word reading growth in first grade even when they were competed against other relevant predictors (phonological awareness, nonword reading, sight word efficiency, vocabulary, listening comprehension, hyperactivity, nonverbal reasoning, and short term memory). Also, student attention demonstrated a significant indirect effect on third grade reading comprehension via word reading, but not via listening comprehension. Results suggest that student attention (indexed by teacher ratings) is an important predictor of at-risk readers’ responsiveness to reading instruction in first grade and that first-grade reading growth mediates the relationship between students’ attention and their future level of reading comprehension. The importance of considering ways to manage and improve behavioral attention when implementing reading instruction is discussed. PMID:25110548

Global health indicators and maternal health futures: The case of Intrauterine Growth Restriction.

PubMed

Erikson, Susan L

2015-01-01

Public health indicators generally operate in the world as credible, apolitical and authoritative. But indicators are less stable than they appear. Clinical critiques of Intrauterine Growth Restriction (IUGR) criteria have been forthcoming for decades. This article, though, takes up the measuring and calculation gradients of IUGR in the ultrasound machine itself, including the software algorithms that identify IUGR. One hospital where research was conducted incorrectly predicted pathological birth outcomes 14 of 14 times. We are at a historical moment when the global use of prenatal diagnostic ultrasound for the express purpose of assessing IUGR is set to escalate. Medical imaging device corporations like Siemens, Toshiba, General Electric and Phillips are quite literally banking on it, and new forms of ultrasound technology and diagnostic software are increasingly available on smartphones, tablets and laptops. Clinical guidelines for IUGR--assumed to be authoritative and evidence-based--are evolving right along with the installation throughout the world of the technology capable of diagnosing it. Maternal malnutrition remains the single strongest predictive factor for IUGR, regardless of the technological investments currently amassing to identify the indicator, which is cause for a reassessment of priority spending and investment.

Simulation of RCC Crack Growth Due to Carbon Oxidation in High-Temperature Gas Environments

NASA Technical Reports Server (NTRS)

Titov, E. V.; Levin, D. A.; Picetti, Donald J.; Anderson, Brian P.

2009-01-01

The carbon wall oxidation technique coupled with a CFD technique was employed to study the flow in the expanding crack channel caused by the oxidation of the channel carbon walls. The recessing 3D surface morphing procedure was developed and tested in comparison with the arcjet experimental results. The multi-block structured adaptive meshing was used to model the computational domain changes due to the wall recession. Wall regression rates for a reinforced carbon-carbon (RCC) samples, that were tested in a high enthalpy arcjet environment, were computationally obtained and used to assess the channel expansion. The test geometry and flow conditions render the flow regime as the transitional to continuum, therefore Navier-Stokes gas dynamic approach with the temperature jump and velocity slip correction to the boundary conditions was used. The modeled mechanism for wall material loss was atomic oxygen reaction with bare carbon. The predicted channel growth was found to agree with arcjet observations. Local gas flow field results were found to affect the oxidation rate in a manner that cannot be predicted by previous mass loss correlations. The method holds promise for future modeling of materials gas-dynamic interactions for hypersonic flight.

Whole genome prediction and heritability of childhood asthma phenotypes.

PubMed

McGeachie, Michael J; Clemmer, George L; Croteau-Chonka, Damien C; Castaldi, Peter J; Cho, Michael H; Sordillo, Joanne E; Lasky-Su, Jessica A; Raby, Benjamin A; Tantisira, Kelan G; Weiss, Scott T

2016-12-01

While whole genome prediction (WGP) methods have recently demonstrated successes in the prediction of complex genetic diseases, they have not yet been applied to asthma and related phenotypes. Longitudinal patterns of lung function differ between asthmatics, but these phenotypes have not been assessed for heritability or predictive ability. Herein, we assess the heritability and genetic predictability of asthma-related phenotypes. We applied several WGP methods to a well-phenotyped cohort of 832 children with mild-to-moderate asthma from CAMP. We assessed narrow-sense heritability and predictability for airway hyperresponsiveness, serum immunoglobulin E, blood eosinophil count, pre- and post-bronchodilator forced expiratory volume in 1 sec (FEV 1 ), bronchodilator response, steroid responsiveness, and longitudinal patterns of lung function (normal growth, reduced growth, early decline, and their combinations). Prediction accuracy was evaluated using a training/testing set split of the cohort. We found that longitudinal lung function phenotypes demonstrated significant narrow-sense heritability (reduced growth, 95%; normal growth with early decline, 55%). These same phenotypes also showed significant polygenic prediction (areas under the curve [AUCs] 56% to 62%). Including additional demographic covariates in the models increased prediction 4-8%, with reduced growth increasing from 62% to 66% AUC. We found that prediction with a genomic relatedness matrix was improved by filtering available SNPs based on chromatin evidence, and this result extended across cohorts. Longitudinal reduced lung function growth displayed extremely high heritability. All phenotypes with significant heritability showed significant polygenic prediction. Using SNP-prioritization increased prediction across cohorts. WGP methods show promise in predicting asthma-related heritable traits.

Impacts of rural development on Yellowstone wildlife: linking grizzly bear Ursus arctos demographics with projected residential growth

USGS Publications Warehouse

Schwartz, Charles C.; Gude, Patricia H.; Landenburger, Lisa; Haroldson, Mark A.; Podruzny, Shannon

2012-01-01

Exurban development is consuming wildlife habitat within the Greater Yellowstone Ecosystem with potential consequences to the long-term conservation of grizzly bears Ursus arctos. We assessed the impacts of alternative future land-use scenarios by linking an existing regression-based simulation model predicting rural development with a spatially explicit model that predicted bear survival. Using demographic criteria that predict population trajectory, we portioned habitats into either source or sink, and projected the loss of source habitat associated with four different build out (new home construction) scenarios through 2020. Under boom growth, we predicted that 12 km2 of source habitat were converted to sink habitat within the Grizzly Bear Recovery Zone (RZ), 189 km2 were converted within the current distribution of grizzly bears outside of the RZ, and 289 km2 were converted in the area outside the RZ identified as suitable grizzly bear habitat. Our findings showed that extremely low densities of residential development created sink habitats. We suggest that tools, such as those outlined in this article, in addition to zoning and subdivision regulation may prove more practical, and the most effective means of retaining large areas of undeveloped land and conserving grizzly bear source habitat will likely require a landscape-scale approach. We recommend a focus on land conservation efforts that retain open space (easements, purchases and trades) coupled with the implementation of ‘bear community programmes’ on an ecosystem wide basis in an effort to minimize human-bear conflicts, minimize management-related bear mortalities associated with preventable conflicts and to safeguard human communities. Our approach has application to other species and areas, and it has illustrated how spatially explicit demographic models can be combined with models predicting land-use change to help focus conservation priorities.

U.S. Population Growth: Prospects and Policy.

ERIC Educational Resources Information Center

McFalls, Joseph A., Jr.; And Others

1984-01-01

The Commission on Population Growth and the American Future concluded that zero population growth (ZPG) is in the best interest of the United States. To achieve ZPG in the future, the United States must keep fertility and net immigration relatively low. Practical problems are discussed. (RM)

Assessment of climate change impact on yield of major crops in the Banas River Basin, India.

PubMed

Dubey, Swatantra Kumar; Sharma, Devesh

2018-09-01

Crop growth models like AquaCrop are useful in understanding the impact of climate change on crop production considering the various projections from global circulation models and regional climate models. The present study aims to assess the climate change impact on yield of major crops in the Banas River Basin i.e., wheat, barley and maize. Banas basin is part of the semi-arid region of Rajasthan state in India. AquaCrop model is used to calculate the yield of all the three crops for a historical period of 30years (1981-2010) and then compared with observed yield data. Root Mean Square Error (RMSE) values are calculated to assess the model accuracy in prediction of yield. Further, the calibrated model is used to predict the possible impacts of climate change and CO 2 concentration on crop yield using CORDEX-SA climate projections of three driving climate models (CNRM-CM5, CCSM4 and MPI-ESM-LR) for two different scenarios (RCP4.5 and RCP8.5) for the future period 2021-2050. RMSE values of simulated yield with respect to observed yield of wheat, barley and maize are 11.99, 16.15 and 19.13, respectively. It is predicted that crop yield of all three crops will increase under the climate change conditions for future period (2021-2050). Copyright © 2018 Elsevier B.V. All rights reserved.

Projecting technology change to improve space technology planning and systems management

NASA Astrophysics Data System (ADS)

Walk, Steven Robert

2011-04-01

Projecting technology performance evolution has been improving over the years. Reliable quantitative forecasting methods have been developed that project the growth, diffusion, and performance of technology in time, including projecting technology substitutions, saturation levels, and performance improvements. These forecasts can be applied at the early stages of space technology planning to better predict available future technology performance, assure the successful selection of technology, and improve technology systems management strategy. Often what is published as a technology forecast is simply scenario planning, usually made by extrapolating current trends into the future, with perhaps some subjective insight added. Typically, the accuracy of such predictions falls rapidly with distance in time. Quantitative technology forecasting (QTF), on the other hand, includes the study of historic data to identify one of or a combination of several recognized universal technology diffusion or substitution patterns. In the same manner that quantitative models of physical phenomena provide excellent predictions of system behavior, so do QTF models provide reliable technological performance trajectories. In practice, a quantitative technology forecast is completed to ascertain with confidence when the projected performance of a technology or system of technologies will occur. Such projections provide reliable time-referenced information when considering cost and performance trade-offs in maintaining, replacing, or migrating a technology, component, or system. This paper introduces various quantitative technology forecasting techniques and illustrates their practical application in space technology and technology systems management.

Working Group 5: Measurements technology and active experiments

NASA Technical Reports Server (NTRS)

Whipple, E.; Barfield, J. N.; Faelthammar, C.-G.; Feynman, J.; Quinn, J. N.; Roberts, W.; Stone, N.; Taylor, W. L.

1986-01-01

Technology issues identified by working groups 5 are listed. (1) New instruments are needed to upgrade the ability to measure plasma properties in space. (2) Facilities should be developed for conducting a broad range of plasma experiments in space. (3) The ability to predict plasma weather within magnetospheres should be improved and a capability to modify plasma weather developed. (4) Methods of control of plasma spacecraft and spacecraft plasma interference should be upgraded. (5) The space station laboratory facilities should be designed with attention to problems of flexibility to allow for future growth. These issues are discussed.

Temperature adaptation of bacterial communities in experimentally warmed forest soils.

PubMed

Rousk, Johannes; Frey, Serita D; Bååth, Erland

2012-10-01

A detailed understanding of the influence of temperature on soil microbial activity is critical to predict future atmospheric CO 2 concentrations and feedbacks to anthropogenic warming. We investigated soils exposed to 3-4 years of continuous 5 °C-warming in a field experiment in a temperate forest. We found that an index for the temperature adaptation of the microbial community, T min for bacterial growth, increased by 0.19 °C per 1 °C rise in temperature, showing a community shift towards one adapted to higher temperature with a higher temperature sensitivity (Q 10(5-15 °C) increased by 0.08 units per 1 °C). Using continuously measured temperature data from the field experiment we modelled in situ bacterial growth. Assuming that warming did not affect resource availability, bacterial growth was modelled to become 60% higher in warmed compared to the control plots, with the effect of temperature adaptation of the community only having a small effect on overall bacterial growth (<5%). However, 3 years of warming decreased bacterial growth, most likely due to substrate depletion because of the initially higher growth in warmed plots. When this was factored in, the result was similar rates of modelled in situ bacterial growth in warmed and control plots after 3 years, despite the temperature difference. We conclude that although temperature adaptation for bacterial growth to higher temperatures was detectable, its influence on annual bacterial growth was minor, and overshadowed by the direct temperature effect on growth rates. © 2012 Blackwell Publishing Ltd.

Multiscale Modeling of Angiogenesis and Predictive Capacity

NASA Astrophysics Data System (ADS)

Pillay, Samara; Byrne, Helen; Maini, Philip

Tumors induce the growth of new blood vessels from existing vasculature through angiogenesis. Using an agent-based approach, we model the behavior of individual endothelial cells during angiogenesis. We incorporate crowding effects through volume exclusion, motility of cells through biased random walks, and include birth and death-like processes. We use the transition probabilities associated with the discrete model and a discrete conservation equation for cell occupancy to determine collective cell behavior, in terms of partial differential equations (PDEs). We derive three PDE models incorporating single, multi-species and no volume exclusion. By fitting the parameters in our PDE models and other well-established continuum models to agent-based simulations during a specific time period, and then comparing the outputs from the PDE models and agent-based model at later times, we aim to determine how well the PDE models predict the future behavior of the agent-based model. We also determine whether predictions differ across PDE models and the significance of those differences. This may impact drug development strategies based on PDE models.

Predicting Urban Medical Services Demand in China: An Improved Grey Markov Chain Model by Taylor Approximation.

PubMed

Duan, Jinli; Jiao, Feng; Zhang, Qishan; Lin, Zhibin

2017-08-06

The sharp increase of the aging population has raised the pressure on the current limited medical resources in China. To better allocate resources, a more accurate prediction on medical service demand is very urgently needed. This study aims to improve the prediction on medical services demand in China. To achieve this aim, the study combines Taylor Approximation into the Grey Markov Chain model, and develops a new model named Taylor-Markov Chain GM (1,1) (T-MCGM (1,1)). The new model has been tested by adopting the historical data, which includes the medical service on treatment of diabetes, heart disease, and cerebrovascular disease from 1997 to 2015 in China. The model provides a predication on medical service demand of these three types of disease up to 2022. The results reveal an enormous growth of urban medical service demand in the future. The findings provide practical implications for the Health Administrative Department to allocate medical resources, and help hospitals to manage investments on medical facilities.

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.

Weight centile crossing in infancy: correlations between successive months show evidence of growth feedback and an infant-child growth transition.

PubMed

Cole, Tim J; Singhal, Atul; Fewtrell, Mary S; Wells, Jonathan Ck

2016-10-01

Early rapid weight gain is associated with later overweight, which implies that weight centile crossing tracks over time. Centile crossing is defined in terms of the change or deviation in weight z score during 1 mo, and the correlations between successive deviations are explored at different ages. Two Cambridge (United Kingdom) growth cohorts were used: Widdowson (1094 infants born during 1959-1965) and the Cambridge Infant Growth Study (CIGS; 255 infants born during 1984-1987), each with weights measured monthly in the first year. Weights were converted to WHO age- and sex-adjusted z scores, deviations were calculated as the change in z score between adjacent measurement occasions, and the correlations between deviations were studied. In both cohorts, the correlations between successive monthly deviations were positive in the first 6 mo and highest at ages 3-4 mo (r = 0.3, P < 0.0001), whereas after 6 mo they were negative and were lowest at ages 10-11 mo (r = -0.3, P < 0.0001), with the correlation decreasing linearly with age between these extremes. Thus, during the first 6 mo of age, infants crossing centiles in 1 mo tended to continue crossing centiles in the same direction the following month, whereas after 6 mo they tended to cross back again. This represents positive and negative feedback, respectively. At age 12 mo, the correlation was close to zero, which suggests an infant-child transition in growth. The results confirm that weight centile crossing tracks over time, with the correlations between successive periods that change with age suggesting a complex feedback mechanism underlying infant growth. This may throw light on the link between early rapid weight gain and later overweight. Clinically, the correlations indicate that when predicting future weight from current weight, recent centile crossing affects the prediction in an age-dependent manner.

NASA-Langley Research Center's participation in a round-robin comparison between some current crack-propagation prediction methods

NASA Technical Reports Server (NTRS)

Hudson, C. M.; Lewis, P. E.

1979-01-01

A round-robin study was conducted which evaluated and compared different methods currently in practice for predicting crack growth in surface-cracked specimens. This report describes the prediction methods used by the Fracture Mechanics Engineering Section, at NASA-Langley Research Center, and presents a comparison between predicted crack growth and crack growth observed in laboratory experiments. For tests at higher stress levels, the correlation between predicted and experimentally determined crack growth was generally quite good. For tests at lower stress levels, the predicted number of cycles to reach a given crack length was consistently higher than the experimentally determined number of cycles. This consistent overestimation of the number of cycles could have resulted from a lack of definition of crack-growth data at low values of the stress intensity range. Generally, the predicted critical flaw sizes were smaller than the experimentally determined critical flaw sizes. This underestimation probably resulted from using plane-strain fracture toughness values to predict failure rather than the more appropriate values based on maximum load.

Prediction of attendance at fitness center: a comparison between the theory of planned behavior, the social cognitive theory, and the physical activity maintenance theory

PubMed Central

Jekauc, Darko; Völkle, Manuel; Wagner, Matthias O.; Mess, Filip; Reiner, Miriam; Renner, Britta

2015-01-01

In the processes of physical activity (PA) maintenance specific predictors are effective, which differ from other stages of PA development. Recently, Physical Activity Maintenance Theory (PAMT) was specifically developed for prediction of PA maintenance. The aim of the present study was to evaluate the predictability of the future behavior by the PAMT and compare it with the Theory of Planned Behavior (TPB) and Social Cognitive Theory (SCT). Participation rate in a fitness center was observed for 101 college students (53 female) aged between 19 and 32 years (M = 23.6; SD = 2.9) over 20 weeks using a magnetic card. In order to predict the pattern of participation TPB, SCT and PAMT were used. A latent class zero-inflated Poisson growth curve analysis identified two participation patterns: regular attenders and intermittent exercisers. SCT showed the highest predictive power followed by PAMT and TPB. Impeding aspects as life stress and barriers were the strongest predictors suggesting that overcoming barriers might be an important aspect for working out on a regular basis. Self-efficacy, perceived behavioral control, and social support could also significantly differentiate between the participation patterns. PMID:25717313

Long-term prediction of fish growth under varying ambient temperature using a multiscale dynamic model

PubMed Central

2009-01-01

Background Feed composition has a large impact on the growth of animals, particularly marine fish. We have developed a quantitative dynamic model that can predict the growth and body composition of marine fish for a given feed composition over a timespan of several months. The model takes into consideration the effects of environmental factors, particularly temperature, on growth, and it incorporates detailed kinetics describing the main metabolic processes (protein, lipid, and central metabolism) known to play major roles in growth and body composition. Results For validation, we compared our model's predictions with the results of several experimental studies. We showed that the model gives reliable predictions of growth, nutrient utilization (including amino acid retention), and body composition over a timespan of several months, longer than most of the previously developed predictive models. Conclusion We demonstrate that, despite the difficulties involved, multiscale models in biology can yield reasonable and useful results. The model predictions are reliable over several timescales and in the presence of strong temperature fluctuations, which are crucial factors for modeling marine organism growth. The model provides important improvements over existing models. PMID:19903354

Present and future of metastatic colorectal cancer treatment: A review of new candidate targets

PubMed Central

Martini, Giulia; Troiani, Teresa; Cardone, Claudia; Vitiello, Pietropaolo; Sforza, Vincenzo; Ciardiello, Davide; Napolitano, Stefania; Della Corte, Carminia Maria; Morgillo, Floriana; Raucci, Antonio; Cuomo, Antonio; Selvaggi, Francesco; Ciardiello, Fortunato; Martinelli, Erika

2017-01-01

In the last two decades, great efforts have been made in the treatment of metastatic colorectal cancer (mCRC) due to the approval of new target agents for cytotoxic drugs. Unfortunately, a large percentage of patients present with metastasis at the time of diagnosis or relapse after a few months. The complex molecular heterogeneity of this disease is not completely understood; to date, there is a lack of predictive biomarkers that can be used to select subsets of patients who may respond to target drugs. Only the RAS-mutation status is used to predict resistance to anti-epidermal growth factor receptor agents in patients with mCRC. In this review, we describe approved targeted therapies for the management of metastatic mCRC and discuss new candidate targets on the horizon. PMID:28765689

Identifying structural elements needed for development of a predictive life-history model for pallid and shovelnose sturgeons

USGS Publications Warehouse

Wildhaber, Mark L.; DeLonay, A.J.; Papoulias, D.M.; Galat, D.L.; Jacobson, R.B.; Simpkins, D.G.; Braaten, P.J.; Korschgen, C.E.; Mac, M.J.

2011-01-01

Intensive management of the Missouri and Mississippi Rivers has resulted in dramatic changes to the river systems and their biota. These changes have been implicated in the decline of the pallid sturgeon (Scaphirhynchus albus), which has been listed as a United States federal endangered species. The sympatric shovelnose sturgeon (S. platorynchus) is more common and widespread but has also been in decline. The decline of pallid sturgeon is considered symptomatic of poor reproductive success and low or no recruitment. In order to organize information about these species and provide a basis for future development of a predictive model to help guide recovery efforts, we present an expert-vetted, conceptual life-history framework that incorporates the factors that affect reproduction, growth, and survival of shovelnose and pallid sturgeons.

Effect of temperature rise and ocean acidification on growth of calcifying tubeworm shells (Spirorbis spirorbis): an in situ benthocosm approach

NASA Astrophysics Data System (ADS)

Ni, Sha; Taubner, Isabelle; Böhm, Florian; Winde, Vera; Böttcher, Michael E.

2018-03-01

The calcareous tubeworm Spirorbis spirorbis is a widespread serpulid species in the Baltic Sea, where it commonly grows as an epibiont on brown macroalgae (genus Fucus). It lives within a Mg-calcite shell and could be affected by ocean acidification and temperature rise induced by the predicted future atmospheric CO2 increase. However, Spirorbis tubes grow in a chemically modified boundary layer around the algae, which may mitigate acidification. In order to investigate how increasing temperature and rising pCO2 may influence S. spirorbis shell growth we carried out four seasonal experiments in the Kiel Outdoor Benthocosms at elevated pCO2 and temperature conditions. Compared to laboratory batch culture experiments the benthocosm approach provides a better representation of natural conditions for physical and biological ecosystem parameters, including seasonal variations. We find that growth rates of S. spirorbis are significantly controlled by ontogenetic and seasonal effects. The length of the newly grown tube is inversely related to the initial diameter of the shell. Our study showed no significant difference of the growth rates between ambient atmospheric and elevated (1100 ppm) pCO2 conditions. No influence of daily average CaCO3 saturation state on the growth rates of S. spirorbis was observed. We found, however, net growth of the shells even in temporarily undersaturated bulk solutions, under conditions that concurrently favoured selective shell surface dissolution. The results suggest an overall resistance of S. spirorbis growth to acidification levels predicted for the year 2100 in the Baltic Sea. In contrast, S. spirorbis did not survive at mean seasonal temperatures exceeding 24 °C during the summer experiments. In the autumn experiments at ambient pCO2, the growth rates of juvenile S. spirorbis were higher under elevated temperature conditions. The results reveal that S. spirorbis may prefer moderately warmer conditions during their early life stages but will suffer from an excessive temperature increase and from increasing shell corrosion as a consequence of progressing ocean acidification.

Big Data’s Role in Precision Public Health

PubMed Central

Dolley, Shawn

2018-01-01

Precision public health is an emerging practice to more granularly predict and understand public health risks and customize treatments for more specific and homogeneous subpopulations, often using new data, technologies, and methods. Big data is one element that has consistently helped to achieve these goals, through its ability to deliver to practitioners a volume and variety of structured or unstructured data not previously possible. Big data has enabled more widespread and specific research and trials of stratifying and segmenting populations at risk for a variety of health problems. Examples of success using big data are surveyed in surveillance and signal detection, predicting future risk, targeted interventions, and understanding disease. Using novel big data or big data approaches has risks that remain to be resolved. The continued growth in volume and variety of available data, decreased costs of data capture, and emerging computational methods mean big data success will likely be a required pillar of precision public health into the future. This review article aims to identify the precision public health use cases where big data has added value, identify classes of value that big data may bring, and outline the risks inherent in using big data in precision public health efforts. PMID:29594091

Big Data's Role in Precision Public Health.

PubMed

Dolley, Shawn

2018-01-01

Precision public health is an emerging practice to more granularly predict and understand public health risks and customize treatments for more specific and homogeneous subpopulations, often using new data, technologies, and methods. Big data is one element that has consistently helped to achieve these goals, through its ability to deliver to practitioners a volume and variety of structured or unstructured data not previously possible. Big data has enabled more widespread and specific research and trials of stratifying and segmenting populations at risk for a variety of health problems. Examples of success using big data are surveyed in surveillance and signal detection, predicting future risk, targeted interventions, and understanding disease. Using novel big data or big data approaches has risks that remain to be resolved. The continued growth in volume and variety of available data, decreased costs of data capture, and emerging computational methods mean big data success will likely be a required pillar of precision public health into the future. This review article aims to identify the precision public health use cases where big data has added value, identify classes of value that big data may bring, and outline the risks inherent in using big data in precision public health efforts.

Latino Adolescents' Ethnic Identity: Is There a Developmental Progression and Does Growth in Ethnic Identity Predict Growth in Self-Esteem?

ERIC Educational Resources Information Center

Umana-Taylor, Adriana J.; Gonzales-Backen, Melinda A.; Guimond, Amy B.

2009-01-01

The current longitudinal study of 323 Latino adolescents (50.5% male; M age = 15.31 years) examined whether ethnic identity exploration, resolution, and affirmation demonstrated significant growth over a 4-year period and whether growth in ethnic identity predicted growth in self-esteem. Findings from multiple-group latent growth curve models…

Prediction of infarction volume and infarction growth rate in acute ischemic stroke.

PubMed

Kamran, Saadat; Akhtar, Naveed; Alboudi, Ayman; Kamran, Kainat; Ahmad, Arsalan; Inshasi, Jihad; Salam, Abdul; Shuaib, Ashfaq; Qidwai, Uvais

2017-08-08

The prediction of infarction volume after stroke onset depends on the shape of the growth dynamics of the infarction. To understand growth patterns that predict lesion volume changes, we studied currently available models described in literature and compared the models with Adaptive Neuro-Fuzzy Inference System [ANFIS], a method previously unused in the prediction of infarction growth and infarction volume (IV). We included 67 patients with malignant middle cerebral artery [MMCA] stroke who underwent decompressive hemicraniectomy. All patients had at least three cranial CT scans prior to the surgery. The rate of growth and volume of infarction measured on the third CT was predicted with ANFIS without statistically significant difference compared to the ground truth [P = 0.489]. This was not possible with linear, logarithmic or exponential methods. ANFIS was able to predict infarction volume [IV3] over a wide range of volume [163.7-600 cm 3 ] and time [22-110 hours]. The cross correlation [CRR] indicated similarity between the ANFIS-predicted IV3 and original data of 82% for ANFIS, followed by logarithmic 70%, exponential 63% and linear 48% respectively. Our study shows that ANFIS is superior to previously defined methods in the prediction of infarction growth rate (IGR) with reasonable accuracy, over wide time and volume range.

Crack Growth Simulation and Residual Strength Prediction in Airplane Fuselages

NASA Technical Reports Server (NTRS)

Chen, Chuin-Shan; Wawrzynek, Paul A.; Ingraffea, Anthony R.

1999-01-01

The objectives were to create a capability to simulate curvilinear crack growth and ductile tearing in aircraft fuselages subjected to widespread fatigue damage and to validate with tests. Analysis methodology and software program (FRANC3D/STAGS) developed herein allows engineers to maintain aging aircraft economically, while insuring continuous airworthiness, and to design more damage-tolerant aircraft for the next generation. Simulations of crack growth in fuselages were described. The crack tip opening angle (CTOA) fracture criterion, obtained from laboratory tests, was used to predict fracture behavior of fuselage panel tests. Geometrically nonlinear, elastic-plastic, thin shell finite element crack growth analyses were conducted. Comparisons of stress distributions, multiple stable crack growth history, and residual strength between measured and predicted results were made to assess the validity of the methodology. Incorporation of residual plastic deformations and tear strap failure was essential for accurate residual strength predictions. Issue related to predicting crack trajectory in fuselages were also discussed. A directional criterion, including T-stress and fracture toughness orthotropy, was developed. Curvilinear crack growth was simulated in coupon and fuselage panel tests. Both T-stress and fracture toughness orthotropy were essential to predict the observed crack paths. Flapping of fuselages were predicted. Measured and predicted results agreed reasonable well.

The hidden cost of moving up: type 2 diabetes and the escape from persistent poverty in the American South.

PubMed

Steckel, Richard H

2013-01-01

The paper tests the thrifty phenotype hypothesis, according to which nonharmonious growth trajectories are costly for adult health. The American surge in the prevalence of type 2 diabetes is concentrated in the South, a region characterized by a long history of poverty followed by rapid economic growth beginning in the 1960s. Civil rights legislation further accelerated income growth for African-Americans in the region. The paper investigates the hypothesis by using per capita income at the state level as a proxy for net nutritional conditions. Regressions at the state level explain 56% of the variation in the prevalence rate of type 2 diabetes in 2009 using two explanatory variables: the ratio of per capita income in 1980 to that in 1950 and the share of the population that was African-American. The paper discusses ways that rapid economic growth may have translated into weight gain and type 2 diabetes. If the thrifty phenotype hypothesis is correct, future rates in the prevalence of type 2 diabetes are predictable based on income history. The forecast for rapidly developing countries such as India and China are ominous. Copyright © 2013 Wiley Periodicals, Inc.

Growing multiplex networks with arbitrary number of layers

NASA Astrophysics Data System (ADS)

Momeni, Naghmeh; Fotouhi, Babak

2015-12-01

This paper focuses on the problem of growing multiplex networks. Currently, the results on the joint degree distribution of growing multiplex networks present in the literature pertain to the case of two layers and are confined to the special case of homogeneous growth and are limited to the state state (that is, the limit of infinite size). In the present paper, we first obtain closed-form solutions for the joint degree distribution of heterogeneously growing multiplex networks with arbitrary number of layers in the steady state. Heterogeneous growth means that each incoming node establishes different numbers of links in different layers. We consider both uniform and preferential growth. We then extend the analysis of the uniform growth mechanism to arbitrary times. We obtain a closed-form solution for the time-dependent joint degree distribution of a growing multiplex network with arbitrary initial conditions. Throughout, theoretical findings are corroborated with Monte Carlo simulations. The results shed light on the effects of the initial network on the transient dynamics of growing multiplex networks and takes a step towards characterizing the temporal variations of the connectivity of growing multiplex networks, as well as predicting their future structural properties.

Growth of single crystals of organic salts with large second-order optical nonlinearities by solution processes for devices

NASA Technical Reports Server (NTRS)

Leslie, Thomas M.

1995-01-01

Data obtained from the electric field induced second harmonic generation (EFISH) and Kurtz Powder Methods will be provided to MSFC for further refinement of their method. A theoretical model for predicting the second-order nonlinearities of organic salts is being worked on. Another task is the synthesis of a number of salts with various counterions. Several salts with promising SHG activities and new salts will be tested for the presence of two crystalline forms. The materials will be recrystallized from dry and wet solvents and compared for SHG efficiency. Salts that have a high SHG efficiency and no tendency to form hydrates will be documented. The synthesis of these materials are included in this report. A third task involves method to aid in the growth of large, high quality single crystals by solution processes. These crystals will be characterized for their applicability in the fabrication of devices that will be incorporated into optical computers in future programs. Single crystals of optimum quality may be obtained by crystal growth in low-gravity. The final task is the design of a temperature lowering single crystal growth apparatus for ground based work. At least one prototype will be built.

Dynamic model for predicting growth of salmonella spp. in ground sterile pork

USDA-ARS?s Scientific Manuscript database

Predictive model for Salmonella spp. growth in ground pork was developed and validated using kinetic growth data. Salmonella spp. kinetic growth data in ground pork was collected at several isothermal conditions (between 10 and 45C) and Baranyi model was fitted to describe the growth at each temper...

Simulating effects of changing climate and CO(2) emissions on soil carbon pools at the Hubbard Brook experimental forest.

PubMed

Dib, Alain E; Johnson, Chris E; Driscoll, Charles T; Fahey, Timothy J; Hayhoe, Katharine

2014-05-01

Carbon (C) sequestration in forest biomass and soils may help decrease regional C footprints and mitigate future climate change. The efficacy of these practices must be verified by monitoring and by approved calculation methods (i.e., models) to be credible in C markets. Two widely used soil organic matter models - CENTURY and RothC - were used to project changes in SOC pools after clear-cutting disturbance, as well as under a range of future climate and atmospheric carbon dioxide (CO(2) ) scenarios. Data from the temperate, predominantly deciduous Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA, were used to parameterize and validate the models. Clear-cutting simulations demonstrated that both models can effectively simulate soil C dynamics in the northern hardwood forest when adequately parameterized. The minimum postharvest SOC predicted by RothC occurred in postharvest year 14 and was within 1.5% of the observed minimum, which occurred in year 8. CENTURY predicted the postharvest minimum SOC to occur in year 45, at a value 6.9% greater than the observed minimum; the slow response of both models to disturbance suggests that they may overestimate the time required to reach new steady-state conditions. Four climate change scenarios were used to simulate future changes in SOC pools. Climate-change simulations predicted increases in SOC by as much as 7% at the end of this century, partially offsetting future CO(2) emissions. This sequestration was the product of enhanced forest productivity, and associated litter input to the soil, due to increased temperature, precipitation and CO(2) . The simulations also suggested that considerable losses of SOC (8-30%) could occur if forest vegetation at HBEF does not respond to changes in climate and CO(2) levels. Therefore, the source/sink behavior of temperate forest soils likely depends on the degree to which forest growth is stimulated by new climate and CO(2) conditions. © 2013 John Wiley & Sons Ltd.

Dynamic modeling of Listeria monocytogenes growth in pasteurized vanilla cream after postprocessing contamination.

PubMed

Panagou, Efstathios Z; Nychas, George-John E

2008-09-01

A product-specific model was developed and validated under dynamic temperature conditions for predicting the growth of Listeria monocytogenes in pasteurized vanilla cream, a traditional milk-based product. Model performance was also compared with Growth Predictor and Sym'Previus predictive microbiology software packages. Commercially prepared vanilla cream samples were artificially inoculated with a five-strain cocktail of L. monocytogenes, with an initial concentration of 102 CFU g(-1), and stored at 3, 5, 10, and 15 degrees C for 36 days. The growth kinetic parameters at each temperature were determined by the primary model of Baranyi and Roberts. The maximum specific growth rate (mu(max)) was further modeled as a function of temperature by means of a square root-type model. The performance of the model in predicting the growth of the pathogen under dynamic temperature conditions was based on two different temperature scenarios with periodic changes from 4 to 15 degrees C. Growth prediction for dynamic temperature profiles was based on the square root model and the differential equations of the Baranyi and Roberts model, which were numerically integrated with respect to time. Model performance was based on the bias factor (B(f)), the accuracy factor (A(f)), the goodness-of-fit index (GoF), and the percent relative errors between observed and predicted growth. The product-specific model developed in the present study accurately predicted the growth of L. monocytogenes under dynamic temperature conditions. The average values for the performance indices were 1.038, 1.068, and 0.397 for B(f), A(f), and GoF, respectively for both temperature scenarios assayed. Predictions from Growth Predictor and Sym'Previus overestimated pathogen growth. The average values of B(f), A(f), and GoF were 1.173, 1.174, 1.162, and 0.956, 1.115, 0.713 for [corrected] Growth Predictor and Sym'Previus, respectively.

Somatic growth of mussels Mytilus edulis in field studies compared to predictions using BEG, DEB, and SFG models

NASA Astrophysics Data System (ADS)

Larsen, Poul S.; Filgueira, Ramón; Riisgård, Hans Ulrik

2014-04-01

Prediction of somatic growth of blue mussels, Mytilus edulis, based on the data from 2 field-growth studies of mussels in suspended net-bags in Danish waters was made by 3 models: the bioenergetic growth (BEG), the dynamic energy budget (DEB), and the scope for growth (SFG). Here, the standard BEG model has been expanded to include the temperature dependence of filtration rate and respiration and an ad hoc modification to ensure a smooth transition to zero ingestion as chlorophyll a (chl a) concentration approaches zero, both guided by published data. The first 21-day field study was conducted at nearly constant environmental conditions with a mean chl a concentration of C = 2.7 μg L- 1, and the observed monotonous growth in the dry weight of soft parts was best predicted by DEB while BEG and SFG models produced lower growth. The second 165-day field study was affected by large variations in chl a and temperature, and the observed growth varied accordingly, but nevertheless, DEB and SFG predicted monotonous growth in good agreement with the mean pattern while BEG mimicked the field data in response to observed changes in chl a concentration and temperature. The general features of the models were that DEB produced the best average predictions, SFG mostly underestimated growth, whereas only BEG was sensitive to variations in chl a concentration and temperature. DEB and SFG models rely on the calibration of the half-saturation coefficient to optimize the food ingestion function term to that of observed growth, and BEG is independent of observed actual growth as its predictions solely rely on the time history of the local chl a concentration and temperature.

Effects of open-field experimental warming on the growth of two-year-old Pinus densiflora and Abies holophylla seedlings

NASA Astrophysics Data System (ADS)

Han, S.; Son, Y.; Lee, S.; Jo, W.; Yoon, T.; Park, C.; Ko, S.; Kim, J.; Han, S.; Jung, Y.

2012-12-01

Temperature increase due to climate change is expected to affect tree growth and distribution [Way and Oren, 2010]. The responses of trees to warming vary with tree species, ontogenic stages, tree life forms, and biomes. Especially, seedling stage is a vulnerable period for tree survival and competition [Saxe et al., 2007] and thus research on effects of temperature increase on seedling stage is needed. We aimed to examine the responses of coniferous seedlings to future temperature increase by conducting an open-field warming experiment. An experimental warming set-up using infra-red heater was built in 2011 and the temperature in warming plots has been regulated to 3°C higher than that of control plots constantly. The seeds of Pinus densiflora and Abies holophylla were planted in each 1 m × 1 m plot (n=3) in April, 2012. Seedling growth, root collar diameter (RCD) and height of 45 individuals of each plot were measured in June and July, 2012. The survival rate of seedlings was also measured. Survival rate of P. densiflora was lower in warming plots (93.3%) than in control plots (100.0%, p<0.05) and that of A. holophylla was also decreased in warming plots (79.3%) than in control plots (97.0%, p<0.01). RCD and height of P. densiflora seedlings were not significantly different between control and warming plots, however, height of A. holophylla was significantly higher in warming plots in June and July (p<0.01). Comparatively, RCD of A. holophylla was only higher in control plots in June. While there is still a lack of case studies on the growth of seedlings under experimental warming, a few studies reported increased seedling growth [Yin et al., 2008] or and no difference [Han et al., 2009] in warming plots. Different responses of seedling growth between two species of the current study might be derived from species-specific acclimation to temperature increase and/or other limiting factors [Way and Oren, 2010]. This result is, to our knowledge, unprecedented and will contribute to the knowledge of species-specific growth response of tree species and to development of model predicting species distribution in future climate regime. Future work on physiological traits of seedlings and analysis on environmental factors will provide mechanism of seedling response to increased temperature. [This work was supported by 'Korea Forest Service (S111112L080110)'.

The Mass Flux of Non-renewable Energy for Humanity

NASA Astrophysics Data System (ADS)

Solomon, Edwin

The global energy supply relies on non-renewable energy sources, coal, crude oil, and natural gas, along with nuclear power from uranium and these finite resources are located within the upper few kilometers of the Earth's crust. The total quantity of non-renewable energy resources consumed relative to the total quantity available is an essential question facing humanity. Analyses of energy consumption was conducted for the period 1800--2014 using data from the U. S. Energy Information Administration (EIA) and World Energy Production, 1800--1985 to determine the balance between non-renewable energy resources consumed and ultimately recoverable reserves. Annual energy consumption was plotted for each non-renewable resource followed by analyses to determine annual growth rates of consumption. Results indicated total energy consumption grew approximately exponentially 3.6% per year from 1800--1975 and was linear from 1975--2014. The ultimately recoverable reserves (URR) plus the total quantity consumed to date equals the total energy resource reserve prior to exploitation (7.15 x 1018 grams). Knowing the original resource quantity and the annual consumption and growth rates, we can forecast the duration of remaining resources using different scenarios. Alternatively, we can use population growth models and consumption trends to determine the per capita allocation trends and model that into the future. Alternative modeling of future resource allocation on a per capita bases suggests that resource lifetime may be significantly less than that predicted from consumption and production dynamics alone.

Temperature-dependent phenology of Plutella xylostella (Lepidoptera: Plutellidae): Simulation and visualization of current and future distributions along the Eastern Afromontane.

PubMed

Ngowi, Benignus V; Tonnang, Henri E Z; Mwangi, Evans M; Johansson, Tino; Ambale, Janet; Ndegwa, Paul N; Subramanian, Sevgan

2017-01-01

There is a scarcity of laboratory and field-based results showing the movement of the diamondback moth (DBM) Plutella xylostella (L.) across a spatial scale. We studied the population growth of the diamondback moth (DBM) Plutella xylostella (L.) under six constant temperatures, to understand and predict population changes along altitudinal gradients and under climate change scenarios. Non-linear functions were fitted to continuously model DBM development, mortality, longevity and oviposition. We compiled the best-fitted functions for each life stage to yield a phenology model, which we stochastically simulated to estimate the life table parameters. Three temperature-dependent indices (establishment, generation and activity) were derived from a logistic population growth model and then coupled to collected current (2013) and downscaled temperature data from AFRICLIM (2055) for geospatial mapping. To measure and predict the impacts of temperature change on the pest's biology, we mapped the indices along the altitudinal gradients of Mt. Kilimanjaro (Tanzania) and Taita Hills (Kenya) and assessed the differences between 2013 and 2055 climate scenarios. The optimal temperatures for development of DBM were 32.5, 33.5 and 33°C for eggs, larvae and pupae, respectively. Mortality rates increased due to extreme temperatures to 53.3, 70.0 and 52.4% for egg, larvae and pupae, respectively. The net reproduction rate reached a peak of 87.4 female offspring/female/generation at 20°C. Spatial simulations indicated that survival and establishment of DBM increased with a decrease in temperature, from low to high altitude. However, we observed a higher number of DBM generations at low altitude. The model predicted DBM population growth reduction in the low and medium altitudes by 2055. At higher altitude, it predicted an increase in the level of suitability for establishment with a decrease in the number of generations per year. If climate change occurs as per the selected scenario, DBM infestation may reduce in the selected region. The study highlights the need to validate these predictions with other interacting factors such as cropping practices, host plants and natural enemies.

How Do Trees Know When to Flower? Predicting Reproductive Phenology of Douglas-fir with Changing Winter and Spring Temperatures

NASA Astrophysics Data System (ADS)

Prevey, J.; St Clair, B.; Harrington, C.

2016-12-01

Flowering at the right time is one of the primary ways that plants are adapted to their environment. Trees that flower too early risk cold damage to vulnerable new tissues and those that flower too late miss peak resources or may mistime flowering to coincide with other trees, altering outcrossing rates and gene flow. Past observations indicate that temperature cues over winter and spring influence the timing of flowering in many tree species. Understanding these cues is important for predicting how flowering phenology of trees will change with a changing climate.We developed predictive models of flowering for Douglas-fir, an abundant and commercially important tree in the Pacific Northwest. We assembled over 10,000 flowering observations of trees from 11 sites across western Oregon and Washington. We modeled the dates of flowering using hourly temperature data; our models of flowering were adapted from previous models of vegetative budburst and height growth initiation developed for Douglas-fir. Preliminary results show that both chilling (cold) and forcing (warm) temperatures over winter and spring are important determinants of flowering time for Douglas-fir. This suggests that as spring temperatures warm in the future, Douglas-fir across the Pacific Northwest will flower earlier, unless plants experience insufficient chilling over winter, in which case it is possible that Douglas-fir may flower later than in the past, or not flower at all. At one site, Douglas-fir genotypes from different geographic regions flowered in the same order from year to year, indicating that both temperature and heredity influence flowering. Knowledge of the environmental and genetic cues that drive the timing of flowering can help predict how changes in temperature under various climate models could change flowering time across sites. These models may also indicate the geographic areas where future climate could enhance or reduce flowering of Douglas-fir in the future.

Predicting pathogen growth during short-term temperature abuse of raw pork, beef, and poultry products: use of an isothermal-based predictive tool.

PubMed

Ingham, Steven C; Fanslau, Melody A; Burnham, Greg M; Ingham, Barbara H; Norback, John P; Schaffner, Donald W

2007-06-01

A computer-based tool (available at: www.wisc.edu/foodsafety/meatresearch) was developed for predicting pathogen growth in raw pork, beef, and poultry meat. The tool, THERM (temperature history evaluation for raw meats), predicts the growth of pathogens in pork and beef (Escherichia coli O157:H7, Salmonella serovars, and Staphylococcus aureus) and on poultry (Salmonella serovars and S. aureus) during short-term temperature abuse. The model was developed as follows: 25-g samples of raw ground pork, beef, and turkey were inoculated with a five-strain cocktail of the target pathogen(s) and held at isothermal temperatures from 10 to 43.3 degrees C. Log CFU per sample data were obtained for each pathogen and used to determine lag-phase duration (LPD) and growth rate (GR) by DMFit software. The LPD and GR were used to develop the THERM predictive tool, into which chronological time and temperature data for raw meat processing and storage are entered. The THERM tool then predicts a delta log CFU value for the desired pathogen-product combination. The accuracy of THERM was tested in 20 different inoculation experiments that involved multiple products (coarse-ground beef, skinless chicken breast meat, turkey scapula meat, and ground turkey) and temperature-abuse scenarios. With the time-temperature data from each experiment, THERM accurately predicted the pathogen growth and no growth (with growth defined as delta log CFU > 0.3) in 67, 85, and 95% of the experiments with E. coli 0157:H7, Salmonella serovars, and S. aureus, respectively, and yielded fail-safe predictions in the remaining experiments. We conclude that THERM is a useful tool for qualitatively predicting pathogen behavior (growth and no growth) in raw meats. Potential applications include evaluating process deviations and critical limits under the HACCP (hazard analysis critical control point) system.

A dynamic model for predicting growth in zinc-deficient stunted infants given supplemental zinc.

PubMed

Wastney, Meryl E; McDonald, Christine M; King, Janet C

2018-05-01

Zinc deficiency limits infant growth and increases susceptibility to infections, which further compromises growth. Zinc supplementation improves the growth of zinc-deficient stunted infants, but the amount, frequency, and duration of zinc supplementation required to restore growth in an individual child is unknown. A dynamic model of zinc metabolism that predicts changes in weight and length of zinc-deficient, stunted infants with dietary zinc would be useful to define effective zinc supplementation regimens. The aims of this study were to develop a dynamic model for zinc metabolism in stunted, zinc-deficient infants and to use that model to predict the growth response when those infants are given zinc supplements. A model of zinc metabolism was developed using data on zinc kinetics, tissue zinc, and growth requirements for healthy 9-mo-old infants. The kinetic model was converted to a dynamic model by replacing the rate constants for zinc absorption and excretion with functions for these processes that change with zinc intake. Predictions of the dynamic model, parameterized for zinc-deficient, stunted infants, were compared with the results of 5 published zinc intervention trials. The model was then used to predict the results for zinc supplementation regimes that varied in the amount, frequency, and duration of zinc dosing. Model predictions agreed with published changes in plasma zinc after zinc supplementation. Predictions of weight and length agreed with 2 studies, but overpredicted values from a third study in which other nutrient deficiencies may have been growth limiting; the model predicted that zinc absorption was impaired in that study. The model suggests that frequent, smaller doses (5-10 mg Zn/d) are more effective for increasing growth in stunted, zinc-deficient 9-mo-old infants than are larger, less-frequent doses. The dose amount affects the duration of dosing necessary to restore and maintain plasma zinc concentration and growth.

Development and application of Geobacillus stearothermophilus growth model for predicting spoilage of evaporated milk.

PubMed

Kakagianni, Myrsini; Gougouli, Maria; Koutsoumanis, Konstantinos P

2016-08-01

The presence of Geobacillus stearothermophilus spores in evaporated milk constitutes an important quality problem for the milk industry. This study was undertaken to provide an approach in modelling the effect of temperature on G. stearothermophilus ATCC 7953 growth and in predicting spoilage of evaporated milk. The growth of G. stearothermophilus was monitored in tryptone soy broth at isothermal conditions (35-67 °C). The data derived were used to model the effect of temperature on G. stearothermophilus growth with a cardinal type model. The cardinal values of the model for the maximum specific growth rate were Tmin = 33.76 °C, Tmax = 68.14 °C, Topt = 61.82 °C and μopt = 2.068/h. The growth of G. stearothermophilus was assessed in evaporated milk at Topt in order to adjust the model to milk. The efficiency of the model in predicting G. stearothermophilus growth at non-isothermal conditions was evaluated by comparing predictions with observed growth under dynamic conditions and the results showed a good performance of the model. The model was further used to predict the time-to-spoilage (tts) of evaporated milk. The spoilage of this product caused by acid coagulation when the pH approached a level around 5.2, eight generations after G. stearothermophilus reached the maximum population density (Nmax). Based on the above, the tts was predicted from the growth model as the sum of the time required for the microorganism to multiply from the initial to the maximum level ( [Formula: see text] ), plus the time required after the [Formula: see text] to complete eight generations. The observed tts was very close to the predicted one indicating that the model is able to describe satisfactorily the growth of G. stearothermophilus and to provide realistic predictions for evaporated milk spoilage. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis and prediction of Multiple-Site Damage (MSD) fatigue crack growth

NASA Technical Reports Server (NTRS)

Dawicke, D. S.; Newman, J. C., Jr.

1992-01-01

A technique was developed to calculate the stress intensity factor for multiple interacting cracks. The analysis was verified through comparison with accepted methods of calculating stress intensity factors. The technique was incorporated into a fatigue crack growth prediction model and used to predict the fatigue crack growth life for multiple-site damage (MSD). The analysis was verified through comparison with experiments conducted on uniaxially loaded flat panels with multiple cracks. Configuration with nearly equal and unequal crack distribution were examined. The fatigue crack growth predictions agreed within 20 percent of the experimental lives for all crack configurations considered.

Examining the effect of down regulation under high [CO2] on the growth of soybean assimilating a semi process-based model and FACE data

NASA Astrophysics Data System (ADS)

Sakurai, G.; Iizumi, T.; Yokozawa, M.

2011-12-01

The actual impact of elevated [CO2] with the interaction of the other climatic factors on the crop growth is still debated. In many process-based crop models, the response of photosynthesis per single leaf to environmental factors is basically described using the biochemical model of Farquhar et al. (1980). However, the decline in photosynthetic enhancement known as down regulation has not been taken into account. On the other hand, the mechanisms causing photosynthetic down regulation is still unknown, which makes it difficult to include the effect of down regulation into process-based crop models. The current results of Free-air CO2 enrichment (FACE) experiments have reported the effect of down regulation under actual environments. One of the effective approaches to involve these results into future crop yield prediction is developing a semi process-based crop growth model, which includes the effect of photosynthetic down regulation as a statistical model, and assimilating the data obtained in FACE experiments. In this study, we statistically estimated the parameters of a semi process-based model for soybean growth ('SPM-soybean') using a hierarchical Baysian method with the FACE data on soybeans (Morgan et al. 2005). We also evaluated the effect of down regulation on the soybean yield in future climatic conditions. The model selection analysis showed that the effective correction to the overestimation of the Farquhar's biochemical C3 model was to reduce the maximum rate of carboxylation (Vcmax) under elevated [CO2]. However, interestingly, the difference in the estimated final crop yields between the corrected model and the non-corrected model was very slight (Fig.1a) for future projection under climate change scenario (Miroc-ESM). This was due to that the reduction in Vcmax also brought about the reduction of the base dark respiration rate of leaves. Because the dark respiration rate exponentially increases with temperature, the slight difference in base respiration rate becomes a large difference under high temperature under the future climate scenarios. In other words, if the temperature rise is very small or zero under elevated [CO2] condition, the effect of down regulation significantly appears (Fig.1b). This result suggest that further experimental data that considering high CO2 effect and high temperature effect in field conditions should be important and elaborate the model projection of the future crop yield through data assimilation method.

Software Reliability Analysis of NASA Space Flight Software: A Practical Experience

PubMed Central

Sukhwani, Harish; Alonso, Javier; Trivedi, Kishor S.; Mcginnis, Issac

2017-01-01

In this paper, we present the software reliability analysis of the flight software of a recently launched space mission. For our analysis, we use the defect reports collected during the flight software development. We find that this software was developed in multiple releases, each release spanning across all software life-cycle phases. We also find that the software releases were developed and tested for four different hardware platforms, spanning from off-the-shelf or emulation hardware to actual flight hardware. For releases that exhibit reliability growth or decay, we fit Software Reliability Growth Models (SRGM); otherwise we fit a distribution function. We find that most releases exhibit reliability growth, with Log-Logistic (NHPP) and S-Shaped (NHPP) as the best-fit SRGMs. For the releases that experience reliability decay, we investigate the causes for the same. We find that such releases were the first software releases to be tested on a new hardware platform, and hence they encountered major hardware integration issues. Also such releases seem to have been developed under time pressure in order to start testing on the new hardware platform sooner. Such releases exhibit poor reliability growth, and hence exhibit high predicted failure rate. Other problems include hardware specification changes and delivery delays from vendors. Thus, our analysis provides critical insights and inputs to the management to improve the software development process. As NASA has moved towards a product line engineering for its flight software development, software for future space missions will be developed in a similar manner and hence the analysis results for this mission can be considered as a baseline for future flight software missions. PMID:29278255

Software Reliability Analysis of NASA Space Flight Software: A Practical Experience.

PubMed

Sukhwani, Harish; Alonso, Javier; Trivedi, Kishor S; Mcginnis, Issac

2016-01-01

In this paper, we present the software reliability analysis of the flight software of a recently launched space mission. For our analysis, we use the defect reports collected during the flight software development. We find that this software was developed in multiple releases, each release spanning across all software life-cycle phases. We also find that the software releases were developed and tested for four different hardware platforms, spanning from off-the-shelf or emulation hardware to actual flight hardware. For releases that exhibit reliability growth or decay, we fit Software Reliability Growth Models (SRGM); otherwise we fit a distribution function. We find that most releases exhibit reliability growth, with Log-Logistic (NHPP) and S-Shaped (NHPP) as the best-fit SRGMs. For the releases that experience reliability decay, we investigate the causes for the same. We find that such releases were the first software releases to be tested on a new hardware platform, and hence they encountered major hardware integration issues. Also such releases seem to have been developed under time pressure in order to start testing on the new hardware platform sooner. Such releases exhibit poor reliability growth, and hence exhibit high predicted failure rate. Other problems include hardware specification changes and delivery delays from vendors. Thus, our analysis provides critical insights and inputs to the management to improve the software development process. As NASA has moved towards a product line engineering for its flight software development, software for future space missions will be developed in a similar manner and hence the analysis results for this mission can be considered as a baseline for future flight software missions.

Childhood growth predicts higher bone mass and greater bone area in early old age: findings among a subgroup of women from the Helsinki Birth Cohort Study.

PubMed

Mikkola, T M; von Bonsdorff, M B; Osmond, C; Salonen, M K; Kajantie, E; Cooper, C; Välimäki, M J; Eriksson, J G

2017-09-01

We examined the associations between childhood growth and bone properties among women at early old age. Early growth in height predicted greater bone area and higher bone mineral mass. However, information on growth did not improve prediction of bone properties beyond that predicted by body size at early old age. We examined the associations between body size at birth and childhood growth with bone area, bone mineral content (BMC), and areal bone mineral density (aBMD) in early old age. A subgroup of women (n = 178, mean 60.4 years) from the Helsinki Birth Cohort Study, born 1934-1944, participated in dual-energy X-ray absorptiometry (DXA) measurements of the lumbar spine and hip. Height and weight at 0, 2, 7, and 11 years, obtained from health care records, were reconstructed into conditional variables representing growth velocity independent of earlier growth. Weight was adjusted for corresponding height. Linear regression models were adjusted for multiple confounders. Birth length and growth in height before 7 years of age were positively associated with femoral neck area (p < 0.05) and growth in height at all age periods studied with spine bone area (p < 0.01). Growth in height before the age of 7 years was associated with BMC in the femoral neck (p < 0.01) and birth length and growth in height before the age of 7 years were associated with BMC in the spine (p < 0.05). After entering adult height into the models, nearly all associations disappeared. Weight gain during childhood was not associated with bone area or BMC, and aBMD was not associated with early growth. Optimal growth in height in girls is important for obtaining larger skeleton and consequently higher bone mass. However, when predicting bone mineral mass among elderly women, information on early growth does not improve prediction beyond that predicted by current height and weight.

An Energy-Economy-Environment Model for Simulating the Impacts of Socioeconomic Development on Energy and Environment

PubMed Central

Yao, Bo

2014-01-01

Many rapidly developing regions have begun to draw the attention of the world. Meanwhile, the energy and environmental issues associated with rapid economic growth have aroused widespread critical concern. Therefore, studying energy, economic, and environmental systems is of great importance. This study establishes a system dynamic model that covers multiple aspects of those systems, such as energy, economy, population, water pollution, air pollution, solid waste, and technology. The model designed here attempts to determine the impacts of socioeconomic development on the energy and environment of Tongzhou District in three scenarios: under current, planning, and sustainable conditions. The results reveal that energy shortages and water pollutions are very serious and are the key issues constraining future social and economic development. Solid waste emissions increase with population growth. The prediction results provide valuable insights into social advancement. PMID:24683332

Future heat waves due to climate change threaten the survival of Posidonia oceanica seedlings.

PubMed

Guerrero-Meseguer, Laura; Marín, Arnaldo; Sanz-Lázaro, Carlos

2017-11-01

Extreme weather events are major drivers of ecological change, and their occurrence is likely to increase due to climate change. The transient increases in atmospheric temperatures are leading to a greater occurrence of heat waves, extreme events that can produce a substantial warming of water, especially in enclosed basins such as the Mediterranean Sea. Here, we tested the effects of current and predicted heat waves on the early stages of development of the seagrass Posidonia oceanica. Temperatures above 27 °C limited the growth of the plant by inhibiting its photosynthetic system. It suffered a reduction in leaf growth and faster leaf senescence, and in some cases mortality. This study demonstrates that the greater frequency of heat waves, along with anticipated temperature rises in coming decades, are expected to negatively affect the germination of P. oceanica seedlings. Copyright © 2017 Elsevier Ltd. All rights reserved.

Chile confronts its environmental health future after 25 years of accelerated growth

PubMed Central

Pino, Paulina; Iglesias, Verónica; Garreaud, René; Cortés, Sandra; Canals, Mauricio; Folch, Walter; Burgos, Soledad; Levy, Karen; Naeher, Luke P.; Steenland, Kyle

2015-01-01

Background Chile has recently been reclassified by the World Bank from an upper middle income country to a higher income country. There has been great progress in the last 20–30 years in relation to air and water pollution in Chile. Yet after 25 years of unrestrained growth there remain clear challenges posed by air and water, as well as climate change. Methods: In late 2013 a three-day workshop on environmental health was held in Santiago, bringing together researchers and government policy makers. As a follow-up to that workshop, here we review the progress made in environmental health in the past 20–30 years, and discuss the challenges of the future. We focus on air and water pollution, and climate change, which we believe are among the most important areas of environmental health in Chile. Results Air pollution in some cities remains among the highest in the continent. Potable water is generally available, but weak state supervision has led to serious outbreaks of infectious disease and ongoing issues with arsenic exposure in some regions. Climate change modeling in Chile is quite sophisticated, and a number of the impacts of climate change can be reasonably predicted in terms of which areas of the country are most likely to be affected by increased temperature and decreased availability of water, as well as expansion of vector territory. Some health effects, including change vector-borne diseases and excess heat mortality, can be predicted. However, there has yet to be an integration of such research with government planning. Conclusion While great progress has been made, currently there are a number of problems. We suspect that the Chilean experience in environmental health may be of some use for other Latin American countries with rapid economic development. PMID:26615070

ASAS Centennial Paper: Impact of animal science research on United States goat production and predictions for the future.

PubMed

Sahlu, T; Dawson, L J; Gipson, T A; Hart, S P; Merkel, R C; Puchala, R; Wang, Z; Zeng, S; Goetsch, A L

2009-01-01

Goat research in the United States has increased but at a rate less than that in production. Research on goat meat includes nutritional quality, packaging, color, sensory characteristics, and preslaughter management. Goat skins have value for leather, but quality of goat leather has not been extensively studied. Research in the production, quality, antibiotic residues, and sensory characteristics of goat milk and its products has aided development of the US dairy goat industry. Limited progress has been made in genetic improvement of milk or meat production. There is need to explore applications of genomics and proteomics and improve consistency in texture and functionality of goat cheeses. New goat meat and milk products are needed to increase demand and meet the diverse tastes of the American public. Despite research progress in control of mohair and cashmere growth, erratic prices and sale of raw materials have contributed to further declines in US production. Innovative and cooperative ventures are needed for profit sharing up to the consumer level. Internal parasites pose the greatest challenge to goat production in humid areas largely because of anthelmintic resistance. Study of alternative controls is required, including immunity enhancement via nutrition, vaccination, pasture management such as co-grazing with cattle, and genetic resistance. Similarly, the importance of health management is increasing related in part to a lack of effective vaccines for many diseases. Nutrition research should address requirements for vitamins and minerals, efficiencies of protein utilization, adjusting energy requirements for nutritional plane, acclimatization, and grazing conditions, feed intake prediction, and management practices for rapid-growth production systems. Moreover, efficient technology transfer methods are needed to disseminate current knowledge and that gained in future research.