Born Knowing: Tentacled Snakes Innately Predict Future Prey Behavior

PubMed Central

Catania, Kenneth C.

2010-01-01

Background Aquatic tentacled snakes (Erpeton tentaculatus) can take advantage of their prey's escape response by startling fish with their body before striking. The feint usually startles fish toward the snake's approaching jaws. But when fish are oriented at a right angle to the jaws, the C-start escape response translates fish parallel to the snake's head. To exploit this latter response, snakes must predict the future location of the fish. Adult snakes can make this prediction. Is it learned, or are tentacled snakes born able to predict future fish behavior? Methods and Findings Laboratory-born, naïve snakes were investigated as they struck at fish. Trials were recorded at 250 or 500 frames per second. To prevent learning, snakes were placed in a water container with a clear transparency sheet or glass bottom. The chamber was placed over a channel in a separate aquarium with fish below. Thus snakes could see and strike at fish, without contact. The snake's body feint elicited C-starts in the fish below the transparency sheet, allowing strike accuracy to be quantified in relationship to the C-starts. When fish were oriented at a right angle to the jaws, naïve snakes biased their strikes to the future location of the escaping fish's head, such that the snake's jaws and the fish's translating head usually converged. Several different types of predictive strikes were observed. Conclusions The results show that some predators have adapted their nervous systems to directly compensate for the future behavior of prey in a sensory realm that usually requires learning. Instead of behavior selected during their lifetime, newborn tentacled snakes exhibit behavior that has been selected on a different scale—over many generations. Counter adaptations in fish are not expected, as tentacled snakes are rare predators exploiting fish responses that are usually adaptive. PMID:20585384

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.

Symbiont diversity may help coral reefs survive moderate climate change.

PubMed

Baskett, Marissa L; Gaines, Steven D; Nisbet, Roger M

2009-01-01

Given climate change, thermal stress-related mass coral-bleaching events present one of the greatest anthropogenic threats to coral reefs. While corals and their symbiotic algae may respond to future temperatures through genetic adaptation and shifts in community compositions, the climate may change too rapidly for coral response. To test this potential for response, here we develop a model of coral and symbiont ecological dynamics and symbiont evolutionary dynamics. Model results without variation in symbiont thermal tolerance predict coral reef collapse within decades under multiple future climate scenarios, consistent with previous threshold-based predictions. However, model results with genetic or community-level variation in symbiont thermal tolerance can predict coral reef persistence into the next century, provided low enough greenhouse gas emissions occur. Therefore, the level of greenhouse gas emissions will have a significant effect on the future of coral reefs, and accounting for biodiversity and biological dynamics is vital to estimating the size of this effect.

Silent Expectations: Dynamic Causal Modeling of Cortical Prediction and Attention to Sounds That Weren't.

PubMed

Chennu, Srivas; Noreika, Valdas; Gueorguiev, David; Shtyrov, Yury; Bekinschtein, Tristan A; Henson, Richard

2016-08-10

There is increasing evidence that human perception is realized by a hierarchy of neural processes in which predictions sent backward from higher levels result in prediction errors that are fed forward from lower levels, to update the current model of the environment. Moreover, the precision of prediction errors is thought to be modulated by attention. Much of this evidence comes from paradigms in which a stimulus differs from that predicted by the recent history of other stimuli (generating a so-called "mismatch response"). There is less evidence from situations where a prediction is not fulfilled by any sensory input (an "omission" response). This situation arguably provides a more direct measure of "top-down" predictions in the absence of confounding "bottom-up" input. We applied Dynamic Causal Modeling of evoked electromagnetic responses recorded by EEG and MEG to an auditory paradigm in which we factorially crossed the presence versus absence of "bottom-up" stimuli with the presence versus absence of "top-down" attention. Model comparison revealed that both mismatch and omission responses were mediated by increased forward and backward connections, differing primarily in the driving input. In both responses, modeling results suggested that the presence of attention selectively modulated backward "prediction" connections. Our results provide new model-driven evidence of the pure top-down prediction signal posited in theories of hierarchical perception, and highlight the role of attentional precision in strengthening this prediction. Human auditory perception is thought to be realized by a network of neurons that maintain a model of and predict future stimuli. Much of the evidence for this comes from experiments where a stimulus unexpectedly differs from previous ones, which generates a well-known "mismatch response." But what happens when a stimulus is unexpectedly omitted altogether? By measuring the brain's electromagnetic activity, we show that it also generates an "omission response" that is contingent on the presence of attention. We model these responses computationally, revealing that mismatch and omission responses only differ in the location of inputs into the same underlying neuronal network. In both cases, we show that attention selectively strengthens the brain's prediction of the future. Copyright © 2016 Chennu et al.

Sacred Cows and Stubborn Mules: The Imperative to Reform the US Code

DTIC Science & Technology

2013-02-14

National Guard have also added specialized domestic military missions like the Chemical, Biological , Radiological and Nuclear (CBRN) Response Enterprise...lists cyber and EMP as exigent future threats, adding that the most predictable future megatrend is empowerment. “Individuals and small groups will...and include a Defense CBRN Response Force (DCRF) and two CBRN Response Elements (CRE). The US Marines also maintain two Chemical, Biological Incident

Advances and trends in computational structural mechanics

NASA Technical Reports Server (NTRS)

Noor, A. K.

1986-01-01

Recent developments in computational structural mechanics are reviewed with reference to computational needs for future structures technology, advances in computational models for material behavior, discrete element technology, assessment and control of numerical simulations of structural response, hybrid analysis, and techniques for large-scale optimization. Research areas in computational structural mechanics which have high potential for meeting future technological needs are identified. These include prediction and analysis of the failure of structural components made of new materials, development of computational strategies and solution methodologies for large-scale structural calculations, and assessment of reliability and adaptive improvement of response predictions.

The MJO-SSW Teleconnection: Interaction Between MJO-Forced Waves and the Midlatitude Jet

NASA Astrophysics Data System (ADS)

Kang, Wanying; Tziperman, Eli

2018-05-01

The Madden-Julian Oscillation (MJO) was shown to affect both present-day sudden stratospheric warming (SSW) events in the Arctic and their future frequency under global warming scenarios, with implications to the Arctic Oscillation and midlatitude extreme weather. This work uses a dry dynamic core model to understand the dependence of SSW frequency on the amplitude and longitudinal range of the MJO, motivated by the prediction that the MJO will strengthen and broaden its longitudinal range in a warmer climate. We focus on the response of the midlatitude jets and the corresponding generated stationary waves, which are shown to dominate the response of SSW events to MJO forcing. Momentum budget analysis of a large ensemble of spinup simulations suggests that the climatological jet response is driven by the MJO-forced meridional eddy momentum transport. The results suggest that the trends in both MJO amplitude and longitudinal range are important for the prediction of the midlatitude jet response and for the prediction of SSWs in a future climate.

A crucial step toward realism: responses to climate change from an evolving metacommunity perspective.

PubMed

Urban, Mark C; De Meester, Luc; Vellend, Mark; Stoks, Robby; Vanoverbeke, Joost

2012-02-01

We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The 'evolving metacommunity' framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats.

A crucial step toward realism: responses to climate change from an evolving metacommunity perspective

PubMed Central

Urban, Mark C; De Meester, Luc; Vellend, Mark; Stoks, Robby; Vanoverbeke, Joost

2012-01-01

We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The ‘evolving metacommunity’ framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats. PMID:25568038

Modelling benthic macrofauna and seagrass distribution patterns in a North Sea tidal basin in response to 2050 climatic and environmental scenarios

NASA Astrophysics Data System (ADS)

Singer, Anja; Millat, Gerald; Staneva, Joanna; Kröncke, Ingrid

2017-03-01

Small-scale spatial distribution patterns of seven macrofauna species, seagrass beds and mixed mussel/oyster reefs were modelled for the Jade Bay (North Sea, Germany) in response to climatic and environmental scenarios (representing 2050). For the species distribution models four presence-absence modelling methods were merged within the ensemble forecasting platform 'biomod2'. The present spatial distribution (representing 2009) was modelled by statistically related species presences, true species absences and six high-resolution environmental grids. The future spatial distribution was then predicted in response to expected climate change-induced ongoing (1) sea-level rise and (2) water temperature increase. Between 2009 and 2050, the present and future prediction maps revealed a significant range gain for two macrofauna species (Macoma balthica, Tubificoides benedii), whereas the species' range sizes of five macrofauna species remained relatively stable across space and time. The predicted probability of occurrence (PO) of two macrofauna species (Cerastoderma edule, Scoloplos armiger) decreased significantly under the potential future habitat conditions. In addition, a clear seagrass bed extension (Zostera noltii) on the lower intertidal flats (mixed sediments) and a decrease in the PO of mixed Mytilus edulis/Crassostrea gigas reefs was predicted for 2050. Until the mid-21st century, our future climatic and environmental scenario revealed significant changes in the range sizes (gains-losses) and/or the PO (increases-decreases) for seven of the 10 modelled species at the study site.

Motivational indicators of protective behaviour in response to urban water shortage threat

NASA Astrophysics Data System (ADS)

Mankad, Aditi; Greenhill, Murni; Tucker, David; Tapsuwan, Sorada

2013-05-01

The present study examined the role of protection motivation variables in predicting rainwater tank adoption among urban householders. A regression analysis found that subjective knowledge, threat appraisal, response efficacy, response costs, subjective norms and social norms significantly predicted adaptive behavioural intentions (F(6, 399) = 50.769, p < .001, Cohen's f2 = .763). The model accounted for 43% of the variance in intentions to install a rainwater tank as a protective measure against future water shortages. Results further indicated that several variables uniquely contributed to the prediction of rainwater tank adoption (listed in order of relative contribution: response efficacy, threat appraisal, response costs, subjective knowledge and subjective norms). This suggests that people who perceive there is a real water shortage threat, and believe that rainwater tanks are effective in relieving the threat and require minimal or manageable effort to obtain, are more likely to install a tank on their property as a protective measure. Implications of these results are discussed from a research and policy perspective. Recommendations for future motivational research in the area of urban decentralised system acceptance and adoption are presented.

Distributional dynamics of a vulnerable species in response to past and future climate change: a window for conservation prospects

PubMed Central

Bai, Yunjun; Wei, Xueping

2018-01-01

Background The ongoing change in climate is predicted to exert unprecedented effects on Earth’s biodiversity at all levels of organization. Biological conservation is important to prevent biodiversity loss, especially for species facing a high risk of extinction. Understanding the past responses of species to climate change is helpful for revealing response mechanisms, which will contribute to the development of effective conservation strategies in the future. Methods In this study, we modelled the distributional dynamics of a ‘Vulnerable’ species, Pseudolarix amabilis, in response to late Quaternary glacial-interglacial cycles and future 2080 climate change using an ecological niche model (MaxEnt). We also performed migration vector analysis to reveal the potential migration of the population over time. Results Historical modelling indicates that the range dynamics of P. amabilis is highly sensitive to climate change and that its long-distance dispersal ability and potential for evolutionary adaption are limited. Compared to the current climatically suitable areas for this species, future modelling showed significant migration northward towards future potential climatically suitable areas. Discussion In combination with the predicted future distribution, the mechanism revealed by the historical response suggests that this species will not be able to fully occupy the future expanded areas of suitable climate or adapt to the unsuitable climate across the future contraction regions. As a result, we suggest assisted migration as an effective supplementary means of conserving this vulnerable species in the face of the unprecedentedly rapid climate change of the 21st century. As a study case, this work highlights the significance of introducing historical perspectives while researching species conservation, especially for currently vulnerable or endangered taxa that once had a wider distribution in geological time. PMID:29362700

Distributional dynamics of a vulnerable species in response to past and future climate change: a window for conservation prospects.

PubMed

Bai, Yunjun; Wei, Xueping; Li, Xiaoqiang

2018-01-01

The ongoing change in climate is predicted to exert unprecedented effects on Earth's biodiversity at all levels of organization. Biological conservation is important to prevent biodiversity loss, especially for species facing a high risk of extinction. Understanding the past responses of species to climate change is helpful for revealing response mechanisms, which will contribute to the development of effective conservation strategies in the future. In this study, we modelled the distributional dynamics of a 'Vulnerable' species, Pseudolarix amabilis , in response to late Quaternary glacial-interglacial cycles and future 2080 climate change using an ecological niche model (MaxEnt). We also performed migration vector analysis to reveal the potential migration of the population over time. Historical modelling indicates that the range dynamics of P. amabilis is highly sensitive to climate change and that its long-distance dispersal ability and potential for evolutionary adaption are limited. Compared to the current climatically suitable areas for this species, future modelling showed significant migration northward towards future potential climatically suitable areas. In combination with the predicted future distribution, the mechanism revealed by the historical response suggests that this species will not be able to fully occupy the future expanded areas of suitable climate or adapt to the unsuitable climate across the future contraction regions. As a result, we suggest assisted migration as an effective supplementary means of conserving this vulnerable species in the face of the unprecedentedly rapid climate change of the 21st century. As a study case, this work highlights the significance of introducing historical perspectives while researching species conservation, especially for currently vulnerable or endangered taxa that once had a wider distribution in geological time.

Predicting ecological responses in a changing ocean: the effects of future climate uncertainty.

PubMed

Freer, Jennifer J; Partridge, Julian C; Tarling, Geraint A; Collins, Martin A; Genner, Martin J

2018-01-01

Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica . Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies.

Illusions and Ignorance about the Family-Responsive Workplace.

ERIC Educational Resources Information Center

Kingston, Paul W.

1990-01-01

Contends American businesses have made modest headway in instituting family-responsive practices and that it is illusory to expect that market solutions will deliver good or equitable family policy in foreseeable future. Predicts uneven realization of the responsive workplace. (Author/ABL)

Therapygenetics: Using genetic markers to predict response to psychological treatment for mood and anxiety disorders

PubMed Central

2013-01-01

Considerable variation is evident in response to psychological therapies for mood and anxiety disorders. Genetic factors alongside environmental variables and gene-environment interactions are implicated in the etiology of these disorders and it is plausible that these same factors may also be important in predicting individual differences in response to psychological treatment. In this article, we review the evidence that genetic variation influences psychological treatment outcomes with a primary focus on mood and anxiety disorders. Unlike most past work, which has considered prediction of response to pharmacotherapy, this article reviews recent work in the field of therapygenetics, namely the role of genes in predicting psychological treatment response. As this is a field in its infancy, methodological recommendations are made and opportunities for future research are identified. PMID:23388219

The dynamics of learning about a climate threshold

NASA Astrophysics Data System (ADS)

Keller, Klaus; McInerney, David

2008-02-01

Anthropogenic greenhouse gas emissions may trigger threshold responses of the climate system. One relevant example of such a potential threshold response is a shutdown of the North Atlantic meridional overturning circulation (MOC). Numerous studies have analyzed the problem of early MOC change detection (i.e., detection before the forcing has committed the system to a threshold response). Here we analyze the early MOC prediction problem. To this end, we virtually deploy an MOC observation system into a simple model that mimics potential future MOC responses and analyze the timing of confident detection and prediction. Our analysis suggests that a confident prediction of a potential threshold response can require century time scales, considerably longer that the time required for confident detection. The signal enabling early prediction of an approaching MOC threshold in our model study is associated with the rate at which the MOC intensity decreases for a given forcing. A faster MOC weakening implies a higher MOC sensitivity to forcing. An MOC sensitivity exceeding a critical level results in a threshold response. Determining whether an observed MOC trend in our model differs in a statistically significant way from an unforced scenario (the detection problem) imposes lower requirements on an observation system than the determination whether the MOC will shut down in the future (the prediction problem). As a result, the virtual observation systems designed in our model for early detection of MOC changes might well fail at the task of early and confident prediction. Transferring this conclusion to the real world requires a considerably refined MOC model, as well as a more complete consideration of relevant observational constraints.

Mentalizing about emotion and its relationship to empathy.

PubMed

Hooker, Christine I; Verosky, Sara C; Germine, Laura T; Knight, Robert T; D'Esposito, Mark

2008-09-01

Mentalizing involves the ability to predict someone else's behavior based on their belief state. More advanced mentalizing skills involve integrating knowledge about beliefs with knowledge about the emotional impact of those beliefs. Recent research indicates that advanced mentalizing skills may be related to the capacity to empathize with others. However, it is not clear what aspect of mentalizing is most related to empathy. In this study, we used a novel, advanced mentalizing task to identify neural mechanisms involved in predicting a future emotional response based on a belief state. Subjects viewed social scenes in which one character had a False Belief and one character had a True Belief. In the primary condition, subjects were asked to predict what emotion the False Belief Character would feel if they had a full understanding about the situation. We found that neural regions related to both mentalizing and emotion were involved when predicting a future emotional response, including the superior temporal sulcus, medial prefrontal cortex, temporal poles, somatosensory related cortices (SRC), inferior frontal gyrus and thalamus. In addition, greater neural activity in primarily emotion-related regions, including right SRC and bilateral thalamus, when predicting emotional response was significantly correlated with more self-reported empathy. The findings suggest that predicting emotional response involves generating and using internal affective representations and that greater use of these affective representations when trying to understand the emotional experience of others is related to more empathy.

Window-Based Channel Impulse Response Prediction for Time-Varying Ultra-Wideband Channels.

PubMed

Al-Samman, A M; Azmi, M H; Rahman, T A; Khan, I; Hindia, M N; Fattouh, A

2016-01-01

This work proposes channel impulse response (CIR) prediction for time-varying ultra-wideband (UWB) channels by exploiting the fast movement of channel taps within delay bins. Considering the sparsity of UWB channels, we introduce a window-based CIR (WB-CIR) to approximate the high temporal resolutions of UWB channels. A recursive least square (RLS) algorithm is adopted to predict the time evolution of the WB-CIR. For predicting the future WB-CIR tap of window wk, three RLS filter coefficients are computed from the observed WB-CIRs of the left wk-1, the current wk and the right wk+1 windows. The filter coefficient with the lowest RLS error is used to predict the future WB-CIR tap. To evaluate our proposed prediction method, UWB CIRs are collected through measurement campaigns in outdoor environments considering line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. Under similar computational complexity, our proposed method provides an improvement in prediction errors of approximately 80% for LOS and 63% for NLOS scenarios compared with a conventional method.

Window-Based Channel Impulse Response Prediction for Time-Varying Ultra-Wideband Channels

PubMed Central

Al-Samman, A. M.; Azmi, M. H.; Rahman, T. A.; Khan, I.; Hindia, M. N.; Fattouh, A.

2016-01-01

This work proposes channel impulse response (CIR) prediction for time-varying ultra-wideband (UWB) channels by exploiting the fast movement of channel taps within delay bins. Considering the sparsity of UWB channels, we introduce a window-based CIR (WB-CIR) to approximate the high temporal resolutions of UWB channels. A recursive least square (RLS) algorithm is adopted to predict the time evolution of the WB-CIR. For predicting the future WB-CIR tap of window wk, three RLS filter coefficients are computed from the observed WB-CIRs of the left wk−1, the current wk and the right wk+1 windows. The filter coefficient with the lowest RLS error is used to predict the future WB-CIR tap. To evaluate our proposed prediction method, UWB CIRs are collected through measurement campaigns in outdoor environments considering line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. Under similar computational complexity, our proposed method provides an improvement in prediction errors of approximately 80% for LOS and 63% for NLOS scenarios compared with a conventional method. PMID:27992445

Can we use the past as a lens to the future? Using historic events to predict regional grassland and shrubland responses to multi-year drought or wet periods under climate change

USDA-ARS?s Scientific Manuscript database

Background/Question/Methods Ecologists are being challenged to predict ecosystem responses under changing climatic conditions. Water availability is the primary driver of ecosystem processes in temperate grasslands and shrublands, but uncertainty in the magnitude and direction of change in precipita...

Using Multiple Indicators of Cognitive State in Logistic Models that Predict Individual Performance in Machine-Mediated Learning Environments.

ERIC Educational Resources Information Center

Hancock, Thomas E.; And Others

1995-01-01

In machine-mediated learning environments, there is a need for more reliable methods of calculating the probability that a learner's response will be correct in future trials. A combination of domain-independent response-state measures of cognition along with two instructional variables for maximum predictive ability are demonstrated. (Author/LRW)

Emotional reactions to success and failure of collective action as predictors of future action intentions: a longitudinal investigation in the context of student protests in Germany.

PubMed

Tausch, Nicole; Becker, Julia C

2013-09-01

This research examined how emotional responses to success and failure of collective action relate to willingness to engage in collective action in the future. It was hypothesized that both pride (in relation to a success) and anger (in response to failure) would motivate future collective action. Findings are reported from a two-wave longitudinal study (N= 98) in the context of student protests against tuition fees in Germany, which was conducted before and after collective action had resulted in both a success and a failure. While anger positively predicted action intentions, over and above baseline action intentions, pride exerted a significant indirect effect on action intentions via increased efficacy perceptions, over and above baseline efficacy and action intentions. Politicized identification positively predicted the intensity of both pride and anger and baseline group efficacy positively predicted the intensity of anger. The theoretical and practical implications of these findings are discussed. © 2012 The British Psychological Society.

Climates Past, Present, and Yet-to-Come Shape Climate Change Vulnerabilities.

PubMed

Nadeau, Christopher P; Urban, Mark C; Bridle, Jon R

2017-10-01

Climate change is altering life at multiple scales, from genes to ecosystems. Predicting the vulnerability of populations to climate change is crucial to mitigate negative impacts. We suggest that regional patterns of spatial and temporal climatic variation scaled to the traits of an organism can predict where and why populations are most vulnerable to climate change. Specifically, historical climatic variation affects the sensitivity and response capacity of populations to climate change by shaping traits and the genetic variation in those traits. Present and future climatic variation can affect both climate change exposure and population responses. We provide seven predictions for how climatic variation might affect the vulnerability of populations to climate change and suggest key directions for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Physiological Response to Reward and Extinction Predicts Alcohol, Marijuana, and Cigarette Use Two Years Later

PubMed Central

Derefinko, Karen J.; Eisenlohr-Moul, Tory A.; Peters, Jessica R.; Roberts, Walter; Walsh, Erin C.; Milich, Richard; Lynam, Donald R.

2017-01-01

Background Physiological responses to reward and extinction are believed to represent the Behavioral Activation System (BAS) and Behavioral Inhibition System (BIS) constructs of Reinforcement Sensitivity Theory and underlie externalizing behaviors, including substance use. However, little research has examined these relations directly. Methods We assessed individuals’ cardiac pre-ejection periods (PEP) and electrodermal responses (EDR) during reward and extinction trials through the “Number Elimination Game” paradigm. Responses represented BAS and BIS, respectively. We then examined whether these responses provided incremental utility in the prediction of future alcohol, marijuana, and cigarette use. Results Zero-inflated Poisson (ZIP) regression models were used to examine the predictive utility of physiological BAS and BIS responses above and beyond previous substance use. Physiological responses accounted for incremental variance over previous use. Low BAS responses during reward predicted frequency of alcohol use at year 3. Low BAS responses during reward and extinction and high BIS responses during extinction predicted frequency of marijuana use at year 3. For cigarette use, low BAS response during extinction predicted use at year 3. Conclusions These findings suggest that the constructs of Reinforcement Sensitivity Theory, as assessed through physiology, contribute to the longitudinal maintenance of substance use. PMID:27306728

Integrating environmental and genetic effects to predict responses of tree populations to climate.

PubMed

Wang, Tongli; O'Neill, Gregory A; Aitken, Sally N

2010-01-01

Climate is a major environmental factor affecting the phenotype of trees and is also a critical agent of natural selection that has molded among-population genetic variation. Population response functions describe the environmental effect of planting site climates on the performance of a single population, whereas transfer functions describe among-population genetic variation molded by natural selection for climate. Although these approaches are widely used to predict the responses of trees to climate change, both have limitations. We present a novel approach that integrates both genetic and environmental effects into a single "universal response function" (URF) to better predict the influence of climate on phenotypes. Using a large lodgepole pine (Pinus contorta Dougl. ex Loud.) field transplant experiment composed of 140 populations planted on 62 sites to demonstrate the methodology, we show that the URF makes full use of data from provenance trials to: (1) improve predictions of climate change impacts on phenotypes; (2) reduce the size and cost of future provenance trials without compromising predictive power; (3) more fully exploit existing, less comprehensive provenance tests; (4) quantify and compare environmental and genetic effects of climate on population performance; and (5) predict the performance of any population growing in any climate. Finally, we discuss how the last attribute allows the URF to be used as a mechanistic model to predict population and species ranges for the future and to guide assisted migration of seed for reforestation, restoration, or afforestation and genetic conservation in a changing climate.

The Representation of Prediction Error in Auditory Cortex

PubMed Central

Rubin, Jonathan; Ulanovsky, Nachum; Tishby, Naftali

2016-01-01

To survive, organisms must extract information from the past that is relevant for their future. How this process is expressed at the neural level remains unclear. We address this problem by developing a novel approach from first principles. We show here how to generate low-complexity representations of the past that produce optimal predictions of future events. We then illustrate this framework by studying the coding of ‘oddball’ sequences in auditory cortex. We find that for many neurons in primary auditory cortex, trial-by-trial fluctuations of neuronal responses correlate with the theoretical prediction error calculated from the short-term past of the stimulation sequence, under constraints on the complexity of the representation of this past sequence. In some neurons, the effect of prediction error accounted for more than 50% of response variability. Reliable predictions often depended on a representation of the sequence of the last ten or more stimuli, although the representation kept only few details of that sequence. PMID:27490251

Future remnant liver function as predictive factor for the hypertrophy response after portal vein embolization.

PubMed

Cieslak, Kasia P; Huisman, Floor; Bais, Thomas; Bennink, Roelof J; van Lienden, Krijn P; Verheij, Joanne; Besselink, Marc G; Busch, Olivier R C; van Gulik, Thomas M

2017-07-01

Preoperative portal vein embolization is widely used to increase the future remnant liver. Identification of nonresponders to portal vein embolization is essential because these patients may benefit from associating liver partition and portal vein ligation for staged hepatectomy (ALPPS), which induces a more powerful hypertrophy response. 99m Tc-mebrofenin hepatobiliary scintigraphy is a quantitative method for assessment of future remnant liver function with a calculated cutoff value for the prediction of postoperative liver failure. The aim of this study was to analyze future remnant liver function before portal vein embolization to predict sufficient functional hypertrophy response after portal vein embolization. Sixty-three patients who underwent preoperative portal vein embolization and computed tomography imaging were included. Hepatobiliary scintigraphy was performed to determine pre-portal vein embolization and post-portal vein embolization future remnant liver function. Receiver operator characteristic analysis of pre-portal vein embolization future remnant liver function was performed to identify patients who would meet the post-portal vein embolization cutoff value for sufficient function (ie, 2.7%/min/m 2 ). Mean pre-portal vein embolization future remnant liver function was 1.80% ± 0.45%/min/m 2 and increased to 2.89% ± 0.97%/min/m 2 post-portal vein embolization. Receiver operator characteristic analysis in 33 patients who did not receive chemotherapy revealed that a pre-portal vein embolization future remnant liver function of ≥1.72%/min/m 2 was able to identify patients who would meet the safe future remnant liver function cutoff value 3 weeks after portal vein embolization (area under the curve = 0.820). The predictive value was less pronounced in 30 patients treated with neoadjuvant chemotherapy (area under the curve = 0.618). A total of 45 of 63 patients underwent liver resection, of whom 5 of 45 developed postoperative liver failure; 4 of 5 patients had a post-portal vein embolization future remnant liver function below the cutoff value for safe resection. When selecting patients for portal vein embolization, future remnant liver function assessed with hepatobiliary scintigraphy can be used as a predictor of insufficient functional hypertrophy after portal vein embolization, especially in nonchemotherapy patients. These patients are potential candidates for ALPPS. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Predicting sun protection behaviors using protection motivation variables.

PubMed

Ch'ng, Joanne W M; Glendon, A Ian

2014-04-01

Protection motivation theory components were used to predict sun protection behaviors (SPBs) using four outcome measures: typical reported behaviors, previous reported behaviors, current sunscreen use as determined by interview, and current observed behaviors (clothing worn) to control for common method bias. Sampled from two SE Queensland public beaches during summer, 199 participants aged 18-29 years completed a questionnaire measuring perceived severity, perceived vulnerability, response efficacy, response costs, and protection motivation (PM). Personal perceived risk (similar to threat appraisal) and response likelihood (similar to coping appraisal) were derived from their respective PM components. Protection motivation predicted all four SPB criterion variables. Personal perceived risk and response likelihood predicted protection motivation. Protection motivation completely mediated the effect of response likelihood on all four criterion variables. Alternative models are considered. Strengths and limitations of the study are outlined and suggestions made for future research.

Distribution analysis for F100(3) engine

NASA Technical Reports Server (NTRS)

Walter, W. A.; Shaw, M.

1980-01-01

The F100(3) compression system response to inlet circumferential distortion was investigated using an analytical compressor flow model. Compression system response to several types of distortion, including pressure, temperature, and combined pressure/temperature distortions, was investigated. The predicted response trends were used in planning future F100(3) distortion tests. Results show that compression system response to combined temperature and pressure distortions depends upon the relative orientation, as well as the individual amplitudes and circumferential extents of the distortions. Also the usefulness of the analytical predictions in planning engine distortion tests is indicated.

Prediction of chemo-response in serous ovarian cancer.

PubMed

Gonzalez Bosquet, Jesus; Newtson, Andreea M; Chung, Rebecca K; Thiel, Kristina W; Ginader, Timothy; Goodheart, Michael J; Leslie, Kimberly K; Smith, Brian J

2016-10-19

Nearly one-third of serous ovarian cancer (OVCA) patients will not respond to initial treatment with surgery and chemotherapy and die within one year of diagnosis. If patients who are unlikely to respond to current standard therapy can be identified up front, enhanced tumor analyses and treatment regimens could potentially be offered. Using the Cancer Genome Atlas (TCGA) serous OVCA database, we previously identified a robust molecular signature of 422-genes associated with chemo-response. Our objective was to test whether this signature is an accurate and sensitive predictor of chemo-response in serous OVCA. We first constructed prediction models to predict chemo-response using our previously described 422-gene signature that was associated with response to treatment in serous OVCA. Performance of all prediction models were measured with area under the curves (AUCs, a measure of the model's accuracy) and their respective confidence intervals (CIs). To optimize the prediction process, we determined which elements of the signature most contributed to chemo-response prediction. All prediction models were replicated and validated using six publicly available independent gene expression datasets. The 422-gene signature prediction models predicted chemo-response with AUCs of ~70 %. Optimization of prediction models identified the 34 most important genes in chemo-response prediction. These 34-gene models had improved performance, with AUCs approaching 80 %. Both 422-gene and 34-gene prediction models were replicated and validated in six independent datasets. These prediction models serve as the foundation for the future development and implementation of a diagnostic tool to predict response to chemotherapy for serous OVCA patients.

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.

Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity.

PubMed

Swann, Abigail L S; Hoffman, Forrest M; Koven, Charles D; Randerson, James T

2016-09-06

Rising atmospheric CO2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area. This area drops to 37% with the use of precipitation minus evapotranspiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.

Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity

PubMed Central

Koven, Charles D.; Randerson, James T.

2016-01-01

Rising atmospheric CO2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area. This area drops to 37% with the use of precipitation minus evapotranspiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment. PMID:27573831

High Speed Research Program Structural Acoustics Multi-Year Summary Report

NASA Technical Reports Server (NTRS)

Beier, Theodor H.; Bhat, Waman V.; Rizzi, Stephen A.; Silcox, Richard J.; Simpson, Myles A.

2005-01-01

This report summarizes the work conducted by the Structural Acoustics Integrated Technology Development (ITD) Team under NASA's High Speed Research (HSR) Phase II program from 1993 to 1999. It is intended to serve as a reference for future researchers by documenting the results of the interior noise and sonic fatigue technology development activities conducted during this period. For interior noise, these activities included excitation modeling, structural acoustic response modeling, development of passive treatments and active controls, and prediction of interior noise. For sonic fatigue, these activities included loads prediction, materials characterization, sonic fatigue code development, development of response reduction techniques, and generation of sonic fatigue design requirements. Also included are lessons learned and recommendations for future work.

Predictive Coding Accelerates Word Recognition and Learning in the Early Stages of Language Development

ERIC Educational Resources Information Center

Ylinen, Sari; Bosseler, Alexis; Junttila, Katja; Huotilainen, Minna

2017-01-01

The ability to predict future events in the environment and learn from them is a fundamental component of adaptive behavior across species. Here we propose that inferring predictions facilitates speech processing and word learning in the early stages of language development. Twelve- and 24-month olds' electrophysiological brain responses to heard…

Enhanced Neural Responses to Imagined Primary Rewards Predict Reduced Monetary Temporal Discounting.

PubMed

Hakimi, Shabnam; Hare, Todd A

2015-09-23

The pervasive tendency to discount the value of future rewards varies considerably across individuals and has important implications for health and well-being. Here, we used fMRI with human participants to examine whether an individual's neural representation of an imagined primary reward predicts the degree to which the value of delayed monetary payments is discounted. Because future rewards can never be experienced at the time of choice, imagining or simulating the benefits of a future reward may play a critical role in decisions between alternatives with either immediate or delayed benefits. We found that enhanced ventromedial prefrontal cortex response during imagined primary reward receipt was correlated with reduced discounting in a separate monetary intertemporal choice task. Furthermore, activity in enhanced ventromedial prefrontal cortex during reward imagination predicted temporal discounting behavior both between- and within-individual decision makers with 62% and 73% mean balanced accuracy, respectively. These results suggest that the quality of reward imagination may impact the degree to which future outcomes are discounted. Significance statement: We report a novel test of the hypothesis that an important factor influencing the discount rate for future rewards is the quality with which they are imagined or estimated in the present. Previous work has shown that temporal discounting is linked to individual characteristics ranging from general intelligence to the propensity for addiction. We demonstrate that individual differences in a neurobiological measure of primary reward imagination are significantly correlated with discounting rates for future monetary payments. Moreover, our neurobiological measure of imagination can be used to accurately predict choice behavior both between and within individuals. These results suggest that improving reward imagination may be a useful therapeutic target for individuals whose high discount rates promote detrimental behaviors. Copyright © 2015 the authors 0270-6474/15/3513103-07$15.00/0.

Theory of Mind: A Neural Prediction Problem

PubMed Central

Koster-Hale, Jorie; Saxe, Rebecca

2014-01-01

Predictive coding posits that neural systems make forward-looking predictions about incoming information. Neural signals contain information not about the currently perceived stimulus, but about the difference between the observed and the predicted stimulus. We propose to extend the predictive coding framework from high-level sensory processing to the more abstract domain of theory of mind; that is, to inferences about others’ goals, thoughts, and personalities. We review evidence that, across brain regions, neural responses to depictions of human behavior, from biological motion to trait descriptions, exhibit a key signature of predictive coding: reduced activity to predictable stimuli. We discuss how future experiments could distinguish predictive coding from alternative explanations of this response profile. This framework may provide an important new window on the neural computations underlying theory of mind. PMID:24012000

Induced optimism as mental rehearsal to decrease depressive predictive certainty.

PubMed

Miranda, Regina; Weierich, Mariann; Khait, Valerie; Jurska, Justyna; Andersen, Susan M

2017-03-01

The present study examined whether practice in making optimistic future-event predictions would result in change in the hopelessness-related cognitions that characterize depression. Individuals (N = 170) with low, mild, and moderate-to-severe depressive symptoms were randomly assigned to a condition in which they practiced making optimistic future-event predictions or to a control condition in which they viewed the same stimuli but practiced determining whether a given phrase contained an adjective. Overall, individuals in the induced optimism condition showed increases in optimistic predictions, relative to the control condition, as a result of practice, but only individuals with moderate-to-severe symptoms of depression who practiced making optimistic future-event predictions showed decreases in depressive predictive certainty, relative to the control condition. In addition, they showed gains in efficiency in making optimistic predictions over the practice blocks, as assessed by response time. There was no difference in depressed mood by practice condition. Mental rehearsal might be one way of changing the hopelessness-related cognitions that characterize depression. Copyright © 2016 Elsevier Ltd. All rights reserved.

The association between early generative concern and caregiving with friends from early to middle adolescence.

PubMed

Lawford, Heather L; Doyle, Anna-Beth; Markiewicz, Dorothy

2013-12-01

Generativity, defined as concern for future generations, is theorized to become a priority in midlife, preceded by a stage in which intimacy is the central issue. Recent research, however, has found evidence of generativity even in adolescence. This longitudinal study explored the associations between caregiving in friendships, closely related to intimacy, and early generative concern in a young adolescent sample. Given the importance of close friendships in adolescence, it was hypothesized that responsive caregiving in early adolescent friendships would predict later generative concern. Approximately 140 adolescents (56 % female, aged 14 at Time 1) completed questionnaires regarding generative concern and responsive caregiving with friends yearly across 2 years. Structural equation modeling revealed that caregiving predicted generative concern 1 year later but generative concern did not predict later caregiving. These results suggest that caregiving in close friendships plays an important role in the development of adolescents' motivation to contribute to future generations.

Large sensitivity in land carbon storage due to geographical and temporal variation in the thermal response of photosynthetic capacity.

PubMed

Mercado, Lina M; Medlyn, Belinda E; Huntingford, Chris; Oliver, Rebecca J; Clark, Douglas B; Sitch, Stephen; Zelazowski, Przemyslaw; Kattge, Jens; Harper, Anna B; Cox, Peter M

2018-06-01

Plant temperature responses vary geographically, reflecting thermally contrasting habitats and long-term species adaptations to their climate of origin. Plants also can acclimate to fast temporal changes in temperature regime to mitigate stress. Although plant photosynthetic responses are known to acclimate to temperature, many global models used to predict future vegetation and climate-carbon interactions do not include this process. We quantify the global and regional impacts of biogeographical variability and thermal acclimation of temperature response of photosynthetic capacity on the terrestrial carbon (C) cycle between 1860 and 2100 within a coupled climate-carbon cycle model, that emulates 22 global climate models. Results indicate that inclusion of biogeographical variation in photosynthetic temperature response is most important for present-day and future C uptake, with increasing importance of thermal acclimation under future warming. Accounting for both effects narrows the range of predictions of the simulated global land C storage in 2100 across climate projections (29% and 43% globally and in the tropics, respectively). Contrary to earlier studies, our results suggest that thermal acclimation of photosynthetic capacity makes tropical and temperate C less vulnerable to warming, but reduces the warming-induced C uptake in the boreal region under elevated CO 2 . © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Navy Enhanced Sierra Mechanics (NESM): Toolbox for predicting Navy shock and damage

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

Moyer, Thomas; Stergiou, Jonathan; Reese, Garth

Here, the US Navy is developing a new suite of computational mechanics tools (Navy Enhanced Sierra Mechanics) for the prediction of ship response, damage, and shock environments transmitted to vital systems during threat weapon encounters. NESM includes fully coupled Euler-Lagrange solvers tailored to ship shock/damage predictions. NESM is optimized to support high-performance computing architectures, providing the physics-based ship response/threat weapon damage predictions needed to support the design and assessment of highly survivable ships. NESM is being employed to support current Navy ship design and acquisition programs while being further developed for future Navy fleet needs.

Navy Enhanced Sierra Mechanics (NESM): Toolbox for predicting Navy shock and damage

DOE PAGES

Moyer, Thomas; Stergiou, Jonathan; Reese, Garth; ...

2016-05-25

Here, the US Navy is developing a new suite of computational mechanics tools (Navy Enhanced Sierra Mechanics) for the prediction of ship response, damage, and shock environments transmitted to vital systems during threat weapon encounters. NESM includes fully coupled Euler-Lagrange solvers tailored to ship shock/damage predictions. NESM is optimized to support high-performance computing architectures, providing the physics-based ship response/threat weapon damage predictions needed to support the design and assessment of highly survivable ships. NESM is being employed to support current Navy ship design and acquisition programs while being further developed for future Navy fleet needs.

Prediction and control of neural responses to pulsatile electrical stimulation

NASA Astrophysics Data System (ADS)

Campbell, Luke J.; Sly, David James; O'Leary, Stephen John

2012-04-01

This paper aims to predict and control the probability of firing of a neuron in response to pulsatile electrical stimulation of the type delivered by neural prostheses such as the cochlear implant, bionic eye or in deep brain stimulation. Using the cochlear implant as a model, we developed an efficient computational model that predicts the responses of auditory nerve fibers to electrical stimulation and evaluated the model's accuracy by comparing the model output with pooled responses from a group of guinea pig auditory nerve fibers. It was found that the model accurately predicted the changes in neural firing probability over time to constant and variable amplitude electrical pulse trains, including speech-derived signals, delivered at rates up to 889 pulses s-1. A simplified version of the model that did not incorporate adaptation was used to adaptively predict, within its limitations, the pulsatile electrical stimulus required to cause a desired response from neurons up to 250 pulses s-1. Future stimulation strategies for cochlear implants and other neural prostheses may be enhanced using similar models that account for the way that neural responses are altered by previous stimulation.

Breast magnetic resonance elastography: a review of clinical work and future perspectives.

PubMed

Bohte, A E; Nelissen, J L; Runge, J H; Holub, O; Lambert, S A; de Graaf, L; Kolkman, S; van der Meij, S; Stoker, J; Strijkers, G J; Nederveen, A J; Sinkus, R

2018-05-30

This review on magnetic resonance elastography (MRE) of the breast provides an overview of available literature and describes current developments in the field of breast MRE, including new transducer technology for data acquisition and multi-frequency-derived power-law behaviour of tissue. Moreover, we discuss the future potential of breast MRE, which goes beyond its original application as an additional tool in differentiating benign from malignant breast lesions. These areas of ongoing and future research include MRE for pre-operative tumour delineation, staging, monitoring and predicting response to treatment, as well as prediction of the metastatic potential of primary tumours. Copyright © 2018 John Wiley & Sons, Ltd.

Deep learning in pharmacogenomics: from gene regulation to patient stratification.

PubMed

Kalinin, Alexandr A; Higgins, Gerald A; Reamaroon, Narathip; Soroushmehr, Sayedmohammadreza; Allyn-Feuer, Ari; Dinov, Ivo D; Najarian, Kayvan; Athey, Brian D

2018-05-01

This Perspective provides examples of current and future applications of deep learning in pharmacogenomics, including: identification of novel regulatory variants located in noncoding domains of the genome and their function as applied to pharmacoepigenomics; patient stratification from medical records; and the mechanistic prediction of drug response, targets and their interactions. Deep learning encapsulates a family of machine learning algorithms that has transformed many important subfields of artificial intelligence over the last decade, and has demonstrated breakthrough performance improvements on a wide range of tasks in biomedicine. We anticipate that in the future, deep learning will be widely used to predict personalized drug response and optimize medication selection and dosing, using knowledge extracted from large and complex molecular, epidemiological, clinical and demographic datasets.

Growth response of conifers in Adirondack plantations to changing environment: Model approaches based on stem-analysis

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

Pan, Y.

1993-01-01

Based on model approaches, three conifer species, red pine, Norway spruce and Scots pine grown in plantations at Pack Demonstration Forest, in the southeastern Adirondack mountains of New York, were chosen to study growth response to different environmental changes, including silvicultural treatments and changes in climate and chemical environment. Detailed stem analysis data provided a basis for constructing tree growth models. These models were organized into three groups: morphological, dynamic and predictive. The morphological model was designed to evaluate relationship between tree attributes and interactive influences of intrinsic and extrinsic factors on the annual increments. Three types of morphological patternsmore » have been characterized: space-time patterns of whole-stem rings, intrinsic wood deposition pattern along the tree-stem, and bolewood allocation ratio patterns along the tree-stem. The dynamic model reflects the growth process as a system which responds to extrinsic signal inputs, including fertilization pulses, spacing effects and climatic disturbance, as well as intrinsic feedback. Growth signals indicative of climatic effects were used to construct growth-climate models using both multivariate analysis and Kalman filter methods. The predictive model utilized GCMs and growth-climate relationships to forecast tree growth responses in relation to future scenarios of CO[sub 2]-induced climate change. Prediction results indicate that different conifer species have individualistic growth response to future climatic change and suggest possible changes in future growth and distribution of naturally occurring conifers in this region.« less

Regional analysis of drought and heat impacts on forests: current and future science directions.

PubMed

Law, Beverly E

2014-12-01

Accurate assessments of forest response to current and future climate and human actions are needed at regional scales. Predicting future impacts on forests will require improved analysis of species-level adaptation, resilience, and vulnerability to mortality. Land system models can be enhanced by creating trait-based groupings of species that better represent climate sensitivity, such as risk of hydraulic failure from drought. This emphasizes the need for more coordinated in situ and remote sensing observations to track changes in ecosystem function, and to improve model inputs, spatio-temporal diagnosis, and predictions of future conditions, including implications of actions to mitigate climate change. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Plant responses to increasing CO 2 reduce estimates of climate impacts on drought severity

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

Swann, Abigail L. S.; Hoffman, Forrest M.; Koven, Charles D.

Rising atmospheric CO 2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO 2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO 2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area.more » This area drops to 37% with the use of precipitation minus evapo-transpiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO 2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO 2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.« less

Plant responses to increasing CO 2 reduce estimates of climate impacts on drought severity

DOE PAGES

Swann, Abigail L. S.; Hoffman, Forrest M.; Koven, Charles D.; ...

2016-08-29

Rising atmospheric CO 2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO 2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO 2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area.more » This area drops to 37% with the use of precipitation minus evapo-transpiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO 2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO 2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.« less

Spatial pattern and scale influence invader demographic response to simulated precipitation change in an annual grassland community

USDA-ARS?s Scientific Manuscript database

It is important to predict which invasive species will benefit from future changes in climate, and thereby identify those invaders that need particular attention and prioritization of management efforts. Because establishment, persistence, and spread determine invasion success, this prediction requ...

Predicting quantitative and qualitative values of recreation participation

Treesearch

Elwood L., Jr. Shafer; George Moeller

1971-01-01

If future recreation consumption and associated intangible values can be predicted, the problem of rapid decision making in recreation-resource management can be reduced, and the problems of implementing those decisions can be anticipated. Management and research responsibilities for meeting recreation demand are discussed, and proved methods for forecasting recreation...

Highly accurate prediction of emotions surrounding the attacks of September 11, 2001 over 1-, 2-, and 7-year prediction intervals.

PubMed

Doré, Bruce P; Meksin, Robert; Mather, Mara; Hirst, William; Ochsner, Kevin N

2016-06-01

In the aftermath of a national tragedy, important decisions are predicated on judgments of the emotional significance of the tragedy in the present and future. Research in affective forecasting has largely focused on ways in which people fail to make accurate predictions about the nature and duration of feelings experienced in the aftermath of an event. Here we ask a related but understudied question: can people forecast how they will feel in the future about a tragic event that has already occurred? We found that people were strikingly accurate when predicting how they would feel about the September 11 attacks over 1-, 2-, and 7-year prediction intervals. Although people slightly under- or overestimated their future feelings at times, they nonetheless showed high accuracy in forecasting (a) the overall intensity of their future negative emotion, and (b) the relative degree of different types of negative emotion (i.e., sadness, fear, or anger). Using a path model, we found that the relationship between forecasted and actual future emotion was partially mediated by current emotion and remembered emotion. These results extend theories of affective forecasting by showing that emotional responses to an event of ongoing national significance can be predicted with high accuracy, and by identifying current and remembered feelings as independent sources of this accuracy. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Highly accurate prediction of emotions surrounding the attacks of September 11, 2001 over 1-, 2-, and 7-year prediction intervals

PubMed Central

Doré, B.P.; Meksin, R.; Mather, M.; Hirst, W.; Ochsner, K.N

2016-01-01

In the aftermath of a national tragedy, important decisions are predicated on judgments of the emotional significance of the tragedy in the present and future. Research in affective forecasting has largely focused on ways in which people fail to make accurate predictions about the nature and duration of feelings experienced in the aftermath of an event. Here we ask a related but understudied question: can people forecast how they will feel in the future about a tragic event that has already occurred? We found that people were strikingly accurate when predicting how they would feel about the September 11 attacks over 1-, 2-, and 7-year prediction intervals. Although people slightly under- or overestimated their future feelings at times, they nonetheless showed high accuracy in forecasting 1) the overall intensity of their future negative emotion, and 2) the relative degree of different types of negative emotion (i.e., sadness, fear, or anger). Using a path model, we found that the relationship between forecasted and actual future emotion was partially mediated by current emotion and remembered emotion. These results extend theories of affective forecasting by showing that emotional responses to an event of ongoing national significance can be predicted with high accuracy, and by identifying current and remembered feelings as independent sources of this accuracy. PMID:27100309

State Space Formulation of Nonlinear Vibration Responses Collected from a Dynamic Rotor-Bearing System: An Extension of Bearing Diagnostics to Bearing Prognostics

PubMed Central

Tse, Peter W.; Wang, Dong

2017-01-01

Bearings are widely used in various industries to support rotating shafts. Their failures accelerate failures of other adjacent components and may cause unexpected machine breakdowns. In recent years, nonlinear vibration responses collected from a dynamic rotor-bearing system have been widely analyzed for bearing diagnostics. Numerous methods have been proposed to identify different bearing faults. However, these methods are unable to predict the future health conditions of bearings. To extend bearing diagnostics to bearing prognostics, this paper reports the design of a state space formulation of nonlinear vibration responses collected from a dynamic rotor-bearing system in order to intelligently predict bearing remaining useful life (RUL). Firstly, analyses of nonlinear vibration responses were conducted to construct a bearing health indicator (BHI) so as to assess the current bearing health condition. Secondly, a state space model of the BHI was developed to mathematically track the health evolution of the BHI. Thirdly, unscented particle filtering was used to predict bearing RUL. Lastly, a new bearing acceleration life testing setup was designed to collect natural bearing degradation data, which were used to validate the effectiveness of the proposed bearing prognostic method. Results show that the prediction accuracy of the proposed bearing prognostic method is promising and the proposed bearing prognostic method is able to reflect future bearing health conditions. PMID:28216586

State Space Formulation of Nonlinear Vibration Responses Collected from a Dynamic Rotor-Bearing System: An Extension of Bearing Diagnostics to Bearing Prognostics.

PubMed

Tse, Peter W; Wang, Dong

2017-02-14

Bearings are widely used in various industries to support rotating shafts. Their failures accelerate failures of other adjacent components and may cause unexpected machine breakdowns. In recent years, nonlinear vibration responses collected from a dynamic rotor-bearing system have been widely analyzed for bearing diagnostics. Numerous methods have been proposed to identify different bearing faults. However, these methods are unable to predict the future health conditions of bearings. To extend bearing diagnostics to bearing prognostics, this paper reports the design of a state space formulation of nonlinear vibration responses collected from a dynamic rotor-bearing system in order to intelligently predict bearing remaining useful life (RUL). Firstly, analyses of nonlinear vibration responses were conducted to construct a bearing health indicator (BHI) so as to assess the current bearing health condition. Secondly, a state space model of the BHI was developed to mathematically track the health evolution of the BHI. Thirdly, unscented particle filtering was used to predict bearing RUL. Lastly, a new bearing acceleration life testing setup was designed to collect natural bearing degradation data, which were used to validate the effectiveness of the proposed bearing prognostic method. Results show that the prediction accuracy of the proposed bearing prognostic method is promising and the proposed bearing prognostic method is able to reflect future bearing health conditions.

Prevalence and determinants of direct and generative modes of production of episodic future thoughts in the word cueing paradigm.

PubMed

Jeunehomme, Olivier; D'Argembeau, Arnaud

2016-01-01

Recent research suggests that episodic future thoughts can be formed through the same dual mechanisms, direct and generative, as autobiographical memories. However, the prevalence and determinants of the direct production of future event representations remain unclear. Here, we addressed this issue by collecting self-reports of production modes, response times (RTs), and verbal protocols for the production past and future events in the word cueing paradigm. Across three experiments, we found that both past and future events were frequently reported to come directly to mind in response to the cue, and RTs confirmed that events were produced faster for direct than for generative responses. When looking at the determinants of direct responses, we found that most past and future events that were directly produced had already been thought of on a previous occasion, and the frequency of previous thoughts predicted the occurrence of direct access. The direct production of autobiographical thoughts was also more frequent for past and future events that were judged important and emotionally intense. Collectively, these findings provide novel evidence that the direct production of episodic future thoughts is frequent in the word cueing paradigm and often involves the activation of personally significant "memories of the future."

Defining the Scope of Prognosis: Primary Care Clinicians' Perspectives on Predicting the Future Health of Older Adults.

PubMed

Thomas, John M; Fried, Terri R

2018-05-01

Studies examining the attitudes of clinicians toward prognostication for older adults have focused on life expectancy prediction. Little is known about whether clinicians approach prognostication in other ways. To describe how clinicians approach prognostication for older adults, defined broadly as making projections about patients' future health. In five focus groups, 30 primary care clinicians from community-based, academic-affiliated, and Veterans Affairs primary care practices were given open-ended questions about how they make projections about their patients' future health and how this informs the approach to care. Content analysis was used to organize responses into themes. Clinicians spoke about future health in terms of a variety of health outcomes in addition to life expectancy, including independence in activities and decision making, quality of life, avoiding hospitalization, and symptom burden. They described approaches in predicting these health outcomes, including making observations about the overall trajectory of patients to predict health outcomes and recognizing increased risk for adverse health outcomes. Clinicians expressed reservations about using estimates of mortality risk and life expectancy to think about and communicate patients' future health. They discussed ways in which future research might help them in thinking about and discussing patients' future health to guide care decisions, including identifying when and whether interventions might impact future health. The perspectives of primary care clinicians in this study confirm that prognostic considerations can go beyond precise estimates of mortality risk and life expectancy to include a number of outcomes and approaches to predicting those outcomes. Published by Elsevier Inc.

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

Future Trends in Education Policy.

ERIC Educational Resources Information Center

Newitt, Jane, Ed.

These essays deal explicitly with the future of the public schools and implicitly with the problem of making responsible predictions. Following an introduction by Herman Kahn, the first two essays deal with the social and social policy context of the schools. B. Bruce-Briggs contrasts alternative long-term and current cultural trends. Jane Newitt,…

Reward Prediction Errors in Drug Addiction and Parkinson's Disease: from Neurophysiology to Neuroimaging.

PubMed

García-García, Isabel; Zeighami, Yashar; Dagher, Alain

2017-06-01

Surprises are important sources of learning. Cognitive scientists often refer to surprises as "reward prediction errors," a parameter that captures discrepancies between expectations and actual outcomes. Here, we integrate neurophysiological and functional magnetic resonance imaging (fMRI) results addressing the processing of reward prediction errors and how they might be altered in drug addiction and Parkinson's disease. By increasing phasic dopamine responses, drugs might accentuate prediction error signals, causing increases in fMRI activity in mesolimbic areas in response to drugs. Chronic substance dependence, by contrast, has been linked with compromised dopaminergic function, which might be associated with blunted fMRI responses to pleasant non-drug stimuli in mesocorticolimbic areas. In Parkinson's disease, dopamine replacement therapies seem to induce impairments in learning from negative outcomes. The present review provides a holistic overview of reward prediction errors across different pathologies and might inform future clinical strategies targeting impulsive/compulsive disorders.

Asthma pharmacogenetics and the development of genetic profiles for personalized medicine

PubMed Central

Ortega, Victor E; Meyers, Deborah A; Bleecker, Eugene R

2015-01-01

Human genetics research will be critical to the development of genetic profiles for personalized or precision medicine in asthma. Genetic profiles will consist of gene variants that predict individual disease susceptibility and risk for progression, predict which pharmacologic therapies will result in a maximal therapeutic benefit, and predict whether a therapy will result in an adverse response and should be avoided in a given individual. Pharmacogenetic studies of the glucocorticoid, leukotriene, and β2-adrenergic receptor pathways have focused on candidate genes within these pathways and, in addition to a small number of genome-wide association studies, have identified genetic loci associated with therapeutic responsiveness. This review summarizes these pharmacogenetic discoveries and the future of genetic profiles for personalized medicine in asthma. The benefit of a personalized, tailored approach to health care delivery is needed in the development of expensive biologic drugs directed at a specific biologic pathway. Prior pharmacogenetic discoveries, in combination with additional variants identified in future studies, will form the basis for future genetic profiles for personalized tailored approaches to maximize therapeutic benefit for an individual asthmatic while minimizing the risk for adverse events. PMID:25691813

The impact of climatological model biases in the North Atlantic jet on predicted future circulation change

NASA Astrophysics Data System (ADS)

Simpson, I.

2015-12-01

A long standing bias among global climate models (GCMs) is their incorrect representation of the wintertime circulation of the North Atlantic region. Specifically models tend to exhibit a North Atlantic jet (and associated storm track) that is too zonal, extending across central Europe, when it should tilt northward toward Scandinavia. GCM's consistently predict substantial changes in the large scale circulation in this region, consisting of a localized anti-cyclonic circulation, centered over the Mediterranean and accompanied by increased aridity there and increased storminess over Northern Europe.Here, we present preliminary results from experiments that are designed to address the question of what the impact of the climatological circulation biases might be on this predicted future response. Climate change experiments will be compared in two versions of the Community Earth System Model: the first is a free running version of the model, as typically used in climate prediction; the second is a bias corrected version of the model in which a seasonally varying cycle of bias correction tendencies are applied to the wind and temperature fields. These bias correction tendencies are designed to account for deficiencies in the fast parameterized processes, with an aim to push the model toward a more realistic climatology.While these experiments come with the caveat that they assume the bias correction tendencies will remain constant with time, they allow for an initial assessment, through controlled experiments, of the impact that biases in the climatological circulation can have on future predictions in this region. They will also motivate future work that can make use of the bias correction tendencies to understand the underlying physical processes responsible for the incorrect tilt of the jet.

Towards a predictive understanding of belowground process responses to climate change: have we moved any closer?

Treesearch

Elise Pendall; Lindsey Rustad; Josh Schimel

2008-01-01

Belowground processes, including root production and exudation, microbial activity and community dynamics, and biogeochemical cycling interact to help regulate climate change. Feedbacks associated with these processes, such as warming-enhanced decomposition rates, give rise to major uncertainties in predictions of future climate. Uncertainties associated with these...

Adaptive Anchoring Model: How Static and Dynamic Presentations of Time Series Influence Judgments and Predictions.

PubMed

Kusev, Petko; van Schaik, Paul; Tsaneva-Atanasova, Krasimira; Juliusson, Asgeir; Chater, Nick

2018-01-01

When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model-the adaptive anchoring model (ADAM)-to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average (ARIMA) and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task. Copyright © 2017 The Authors. Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.

How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability.

PubMed

Fitzpatrick, Matthew C; Blois, Jessica L; Williams, John W; Nieto-Lugilde, Diego; Maguire, Kaitlin C; Lorenz, David J

2018-03-23

Future climates are projected to be highly novel relative to recent climates. Climate novelty challenges models that correlate ecological patterns to climate variables and then use these relationships to forecast ecological responses to future climate change. Here, we quantify the magnitude and ecological significance of future climate novelty by comparing it to novel climates over the past 21,000 years in North America. We then use relationships between model performance and climate novelty derived from the fossil pollen record from eastern North America to estimate the expected decrease in predictive skill of ecological forecasting models as future climate novelty increases. We show that, in the high emissions scenario (RCP 8.5) and by late 21st century, future climate novelty is similar to or higher than peak levels of climate novelty over the last 21,000 years. The accuracy of ecological forecasting models is projected to decline steadily over the coming decades in response to increasing climate novelty, although models that incorporate co-occurrences among species may retain somewhat higher predictive skill. In addition to quantifying future climate novelty in the context of late Quaternary climate change, this work underscores the challenges of making reliable forecasts to an increasingly novel future, while highlighting the need to assess potential avenues for improvement, such as increased reliance on geological analogs for future novel climates and improving existing models by pooling data through time and incorporating assemblage-level information. © 2018 John Wiley & Sons Ltd.

Phylogeny predicts future habitat shifts due to climate change.

PubMed

Kuntner, Matjaž; Năpăruş, Magdalena; Li, Daiqin; Coddington, Jonathan A

2014-01-01

Taxa may respond differently to climatic changes, depending on phylogenetic or ecological effects, but studies that discern among these alternatives are scarce. Here, we use two species pairs from globally distributed spider clades, each pair representing two lifestyles (generalist, specialist) to test the relative importance of phylogeny versus ecology in predicted responses to climate change. We used a recent phylogenetic hypothesis for nephilid spiders to select four species from two genera (Nephilingis and Nephilengys) that match the above criteria, are fully allopatric but combined occupy all subtropical-tropical regions. Based on their records, we modeled each species niche spaces and predicted their ecological shifts 20, 40, 60, and 80 years into the future using customized GIS tools and projected climatic changes. Phylogeny better predicts the species current ecological preferences than do lifestyles. By 2080 all species face dramatic reductions in suitable habitat (54.8-77.1%) and adapt by moving towards higher altitudes and latitudes, although at different tempos. Phylogeny and life style explain simulated habitat shifts in altitude, but phylogeny is the sole best predictor of latitudinal shifts. Models incorporating phylogenetic relatedness are an important additional tool to predict accurately biotic responses to global change.

Body mass index influences infliximab post-infusion levels and correlates with prospective loss of response to the drug in a cohort of inflammatory bowel disease patients under maintenance therapy with Infliximab.

PubMed

Scaldaferri, Franco; D'Ambrosio, Daria; Holleran, Grainne; Poscia, Andrea; Petito, Valentina; Lopetuso, Loris; Graziani, Cristina; Laterza, Lucrezia; Pistone, Maria Teresa; Pecere, Silvia; Currò, Diego; Gaetani, Eleonora; Armuzzi, Alessandro; Papa, Alfredo; Cammarota, Giovanni; Gasbarrini, Antonio

2017-01-01

Infliximab is an effective treatment for inflammatory bowel disease (IBD). Studies differ regarding the influence of body mass index (BMI) on the response to infliximab, with the majority of studies indicating that increased BMI may be associated with a poorer response to Infliximab. However, the pharmacokinetic mechanisms causing this have not yet been reported. Examine the correlation between BMI/immunosuppressant use with clinical response, trough and post-infusion levels of infliximab, tumour necrosis factor-α(TNF-α) and anti-drug antibodies(ATI), and determine if these factors can predict future response. We collected serum from 24 patients receiving Infliximab before and 30 minutes following infusion. Clinical parameters were collected retrospectively and prospectively. ELISA measurements of infliximab, TNF-α and ATI were performed. We confirmed that patients with higher infliximab trough levels have a better response rate and that patients with an elevated BMI display a higher rate of loss of response (20%). Patients with a higher BMI had elevated post-infusion levels of infliximab. Additionally, the ratio of IFX/TNF-α trough levels correlated with clinical response to the following infusion. This study confirms that an elevated BMI is associated with a poorer response to infliximab. For the first time, we describe that a higher BMI correlates with higher post-infusion levels, however this does not correlate with a higher rate of response to the drug, suggesting that circulating drug levels do not correlate with tissue levels. Furthermore, in our small cohort of patients, we identified a possible predictive marker of future response to treatment which may be used to guide dose escalation and predict non-response to infliximab.

Statistical mechanics of ribbons under bending and twisting torques.

PubMed

Sinha, Supurna; Samuel, Joseph

2013-11-20

We present an analytical study of ribbons subjected to an external torque. We first describe the elastic response of a ribbon within a purely mechanical framework. We then study the role of thermal fluctuations in modifying its elastic response. We predict the moment-angle relation of bent and twisted ribbons. Such a study is expected to shed light on the role of twist in DNA looping and on bending elasticity of twisted graphene ribbons. Our quantitative predictions can be tested against future single molecule experiments.

Imagining the future in health anxiety: the impact of rumination on the specificity of illness-related memory and future thinking.

PubMed

Sansom-Daly, Ursula M; Bryant, Richard A; Cohn, Richard J; Wakefield, Claire E

2014-01-01

Individuals with health anxiety experience catastrophic fears relating to future illness. However, little research has explored cognitive processes involved in how health anxious individuals picture the future. Ruminative thinking has been shown to impede the ability to recall specific autobiographical memories, which in turn is related to maladaptive, categoric future thinking processes. This study examined the impact of rumination on memory and future thinking among 60 undergraduate participants with varying health anxiety (35% clinical-level health anxiety). Participants were randomized to experiential/ruminative self-focus conditions, then completed an Autobiographical Memory Test and Future Imaginings Task. Responses were coded for specificity and the presence of illness concerns. Rumination led to more specific illness-concerned memories overall, yet at the same time led to more categoric illness-related future imaginings. Rumination and health anxiety together best predicted overgeneral illness-related future imaginings. Highly specific illness-related memories may be maintained due to their personal salience. However, more overgeneral illness-related future imaginings may reflect cognitive avoidance in response to the threat of future illness. This divergent pattern of results between memory and future imaginings may exacerbate health anxiety, and may also serve to maintain maladaptive responses among individuals with realistic medical concerns, such as individuals living with chronic illness.

The importance of measuring growth in response to intervention models: Testing a core assumption✩

PubMed Central

Schatschneider, Christopher; Wagner, Richard K.; Crawford, Elizabeth C.

2011-01-01

A core assumption of response to instruction or intervention (RTI) models is the importance of measuring growth in achievement over time in response to effective instruction or intervention. Many RTI models actively monitor growth for identifying individuals who need different levels of intervention. A large-scale (N=23,438), two-year longitudinal study of first grade children was carried out to compare the predictive validity of measures of achievement status, growth in achievement, and their combination for predicting future reading achievement. The results indicate that under typical conditions, measures of growth do not make a contribution to prediction that is independent of measures of achievement status. These results question the validity of a core assumption of RTI models. PMID:22224065

Evaluation of Dynamic Coastal Response to Sea-level Rise Modifies Inundation Likelihood

NASA Technical Reports Server (NTRS)

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments, making assessments of SLR-induced hazards essential for informed decision making. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30x30m resolution predictions for more than 38,000 sq km of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Assessing the impact of a future volcanic eruption on decadal predictions

NASA Astrophysics Data System (ADS)

Illing, Sebastian; Kadow, Christopher; Pohlmann, Holger; Timmreck, Claudia

2018-06-01

The likelihood of a large volcanic eruption in the future provides the largest uncertainty concerning the evolution of the climate system on the timescale of a few years, but also an excellent opportunity to learn about the behavior of the climate system, and our models thereof. So the following question emerges: how predictable is the response of the climate system to future eruptions? By this we mean to what extent will the volcanic perturbation affect decadal climate predictions and how does the pre-eruption climate state influence the impact of the volcanic signal on the predictions? To address these questions, we performed decadal forecasts with the MiKlip prediction system, which is based on the MPI-ESM, in the low-resolution configuration for the initialization years 2012 and 2014, which differ in the Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO) phase. Each forecast contains an artificial Pinatubo-like eruption starting in June of the first prediction year and consists of 10 ensemble members. For the construction of the aerosol radiative forcing, we used the global aerosol model ECHAM5-HAM in a version adapted for volcanic eruptions. We investigate the response of different climate variables, including near-surface air temperature, precipitation, frost days, and sea ice area fraction. Our results show that the average global cooling response over 4 years of about 0.2 K and the precipitation decrease of about 0.025 mm day-1 is relatively robust throughout the different experiments and seemingly independent of the initialization state. However, on a regional scale, we find substantial differences between the initializations. The cooling effect in the North Atlantic and Europe lasts longer and the Arctic sea ice increase is stronger in the simulations initialized in 2014. In contrast, the forecast initialized in 2012 with a negative PDO shows a prolonged cooling in the North Pacific basin.

Predicting responses from Rasch measures.

PubMed

Linacre, John M

2010-01-01

There is a growing family of Rasch models for polytomous observations. Selecting a suitable model for an existing dataset, estimating its parameters and evaluating its fit is now routine. Problems arise when the model parameters are to be estimated from the current data, but used to predict future data. In particular, ambiguities in the nature of the current data, or overfit of the model to the current dataset, may mean that better fit to the current data may lead to worse fit to future data. The predictive power of several Rasch and Rasch-related models are discussed in the context of the Netflix Prize. Rasch-related models are proposed based on Singular Value Decomposition (SVD) and Boltzmann Machines.

Do Executive Functions Predict Binge-Drinking Patterns? Evidence from a Longitudinal Study in Young Adulthood

PubMed Central

Bø, Ragnhild; Billieux, Joël; Gjerde, Line C.; Eilertsen, Espen M.; Landrø, Nils I.

2017-01-01

Background: Impairments in executive functions (EFs) are related to binge drinking in young adulthood, but research on how EFs influence future binge drinking is lacking. The aim of the current report is therefore to investigate the association between various EFs and later severity of, and change in, binge drinking over a prolonged period during young adulthood. Methods: At baseline, 121 students reported on their alcohol habits (Alcohol use disorder identification test; Alcohol use questionnaire). Concurrently, EFs [working memory, reversal, set-shifting, response inhibition, response monitoring and decision-making (with ambiguity and implicit risk)] were assessed. Eighteen months later, information on alcohol habits for 103 of the participants were gathered. Data were analyzed by means of multilevel regression modeling. Results: Future severity of binge drinking was uniquely predicted by performance on the Information sampling task, assessing risky decision-making (β = -1.86, 95% CI: -3.69, -0.04). None of the study variables predicted severity or change in binge drinking. Conclusion: Future severity of binge drinking was associated with making risky decisions in the prospect for gain, suggesting reward hypersensitivity. Future studies should aim at clarifying whether there is a causal association between decision-making style and binge drinking. Performance on all executive tasks was unrelated to change in binge drinking patterns; however, the finding was limited by overall small changes, and needs to be confirmed with longer follow-up periods. PMID:28408897

Climate change and the future of seed zones

Treesearch

Francis Kilkenny; Brad St. Clair; Matt Horning

2013-01-01

The use of native plants in wildland restoration is critical to the recovery and health of ecosystems. Information from genecological and reciprocal transplant common garden studies can be used to develop seed transfer guidelines and to predict how plants will respond to future climate change. Tools developed from these data, such as universal response functions and...

MR Imaging in Monitoring and Predicting Treatment Response in Multiple Sclerosis.

PubMed

Río, Jordi; Auger, Cristina; Rovira, Àlex

2017-05-01

MR imaging is the most sensitive tool for identifying lesions in patients with multiple sclerosis (MS). MR imaging has also acquired an essential role in the detection of complications arising from these treatments and in the assessment and prediction of efficacy. In the future, other radiological measures that have shown prognostic value may be incorporated within the models for predicting treatment response. This article examines the role of MR imaging as a prognostic tool in patients with MS and the recommendations that have been proposed in recent years to monitor patients who are treated with disease-modifying drugs. Copyright © 2017 Elsevier Inc. All rights reserved.

Species-specific effects of near-future CO2 on the respiratory performance of two tropical prey fish and their predator

PubMed Central

Couturier, Christine S.; Stecyk, Jonathan A. W.; Rummer, Jodie L.; Munday, Philip L.; Nilsson, Göran E.

2013-01-01

Ocean surface CO2 levels are increasing in line with rising atmospheric CO2 and could exceed 900 μatm by year 2100, with extremes above 2000 μatm in some coastal habitats. The imminent increase in ocean pCO2 is predicted to have negative consequences for marine fishes, including reduced aerobic performance, but variability among species could be expected. Understanding interspecific responses to ocean acidification is important for predicting the consequences of ocean acidification on communities and ecosystems. In the present study, the effects of exposure to near-future seawater CO2 (860 μatm) on resting (Ṁ O2rest) and maximum (Ṁ O2max) oxygen consumption rates were determined for three tropical coral reef fish species interlinked through predator-prey relationships: juvenile Pomacentrus moluccensis and P. amboinensis, and one of their predators: adult Pseudochromis fuscus. Contrary to predictions, one of the prey species, P. amboinensis, displayed a 28 – 39 % increase in Ṁ O2max after both an acute and four-day exposure to near-future CO2 seawater, while maintaining Ṁ O2rest. By contrast, the same treatment had no significant effects on Ṁ O2rest or Ṁ O2max of the other two species. However, acute exposure of P. amboinensis to 1400 and 2400 μatm CO2 resulted in Ṁ O2max returning to control values. Overall, the findings suggest that: (1) the metabolic costs of living in a near-future CO2 seawater environment were insignificant for the species examined at rest; (2) the ṀO2max response of tropical reef species to near-future CO2 seawater can be dependent on the severity of external hypercapnia; and (3) near-future ocean pCO2 may not be detrimental to aerobic scope of all fish species and it may even augment aerobic scope of some species. The present results also highlight that close phylogenetic relatedness and living in the same environment, does not necessarily imply similar physiological responses to near-future CO2. PMID:23916817

Predictive control of hollow-fiber bioreactors for the production of monoclonal antibodies.

PubMed

Dowd, J E; Weber, I; Rodriguez, B; Piret, J M; Kwok, K E

1999-05-20

The selection of medium feed rates for perfusion bioreactors represents a challenge for process optimization, particularly in bioreactors that are sampled infrequently. When the present and immediate future of a bioprocess can be adequately described, predictive control can minimize deviations from set points in a manner that can maximize process consistency. Predictive control of perfusion hollow-fiber bioreactors was investigated in a series of hybridoma cell cultures that compared operator control to computer estimation of feed rates. Adaptive software routines were developed to estimate the current and predict the future glucose uptake and lactate production of the bioprocess at each sampling interval. The current and future glucose uptake rates were used to select the perfusion feed rate in a designed response to deviations from the set point values. The routines presented a graphical user interface through which the operator was able to view the up-to-date culture performance and assess the model description of the immediate future culture performance. In addition, fewer samples were taken in the computer-estimated cultures, reducing labor and analytical expense. The use of these predictive controller routines and the graphical user interface decreased the glucose and lactate concentration variances up to sevenfold, and antibody yields increased by 10% to 43%. Copyright 1999 John Wiley & Sons, Inc.

Transcriptomic responses to ocean acidification in larval sea urchins from a naturally variable pH environment.

PubMed

Evans, Tyler G; Chan, Francis; Menge, Bruce A; Hofmann, Gretchen E

2013-03-01

Some marine ecosystems already experience natural declines in pH approximating those predicted with future anthropogenic ocean acidification (OA), the decline in seawater pH caused by the absorption of atmospheric CO2 . The molecular mechanisms that allow organisms to inhabit these low pH environments, particularly those building calcium carbonate skeletons, are unknown. Also uncertain is whether an enhanced capacity to cope with present day pH variation will confer resistance to future OA. To address these issues, we monitored natural pH dynamics within an intertidal habitat in the Northeast Pacific, demonstrating that upwelling exposes resident species to pH regimes not predicted to occur elsewhere until 2100. Next, we cultured the progeny of adult purple sea urchins (Strongylocentrotus purpuratus) collected from this region in CO2 -acidified seawater representing present day and near future ocean scenarios and monitored gene expression using transcriptomics. We hypothesized that persistent exposure to upwelling during evolutionary history will have selected for increased pH tolerance in this population and that their transcriptomic response to low pH seawater would provide insight into mechanisms underlying pH tolerance in a calcifying species. Resulting expression patterns revealed two important trends. Firstly, S. purpuratus larvae may alter the bioavailability of calcium and adjust skeletogenic pathways to sustain calcification in a low pH ocean. Secondly, larvae use different strategies for coping with different magnitudes of pH stress: initiating a robust transcriptional response to present day pH regimes but a muted response to near future conditions. Thus, an enhanced capacity to cope with present day pH variation may not translate into success in future oceans. © 2013 Blackwell Publishing Ltd.

Differential responses of carbon and water vapor fluxes to climate among evergreen needleleaf forests in the USA

USDA-ARS?s Scientific Manuscript database

Understanding of differences in carbon and water vapor fluxes of spatially distributed evergreen needle leaf forests (ENFs) is crucial to accurately estimating regional carbon and water budgets and when predicting the responses of ENFs to future climate. We investigated cross-site variability in car...

Responses of dead forest fuel moisture to climate change

Treesearch

Yongqiang Liu

2016-01-01

Forest fuel moisture is an important factor for wildland fire behavior. Predicting future wildfire trends and controlled burned conditions is essential to effective natural resource management, but the associated effects of forest fuel moisture remain uncertain. This study investigates the responses of dead forest fuel moisture to climate change in the...

The shaping of genetic variation in edge-of-range populations under past and future climate change

PubMed Central

Razgour, Orly; Juste, Javier; Ibáñez, Carlos; Kiefer, Andreas; Rebelo, Hugo; Puechmaille, Sébastien J; Arlettaz, Raphael; Burke, Terry; Dawson, Deborah A; Beaumont, Mark; Jones, Gareth; Wiens, John

2013-01-01

With rates of climate change exceeding the rate at which many species are able to shift their range or adapt, it is important to understand how future changes are likely to affect biodiversity at all levels of organisation. Understanding past responses and extent of niche conservatism in climatic tolerance can help predict future consequences. We use an integrated approach to determine the genetic consequences of past and future climate changes on a bat species, Plecotus austriacus. Glacial refugia predicted by palaeo-modelling match those identified from analyses of extant genetic diversity and model-based inference of demographic history. Former refugial populations currently contain disproportionately high genetic diversity, but niche conservatism, shifts in suitable areas and barriers to migration mean that these hotspots of genetic diversity are under threat from future climate change. Evidence of population decline despite recent northward migration highlights the need to conserve leading-edge populations for spearheading future range shifts. PMID:23890483

Supraspinal Control Predicts Locomotor Function and Forecasts Responsiveness to Training after Spinal Cord Injury

PubMed Central

Field-Fote, Edelle C.; Yang, Jaynie F.; Basso, D. Michele; Gorassini, Monica A.

2017-01-01

Abstract Restoration of walking ability is an area of great interest in the rehabilitation of persons with spinal cord injury. Because many cortical, subcortical, and spinal neural centers contribute to locomotor function, it is important that intervention strategies be designed to target neural elements at all levels of the neuraxis that are important for walking ability. While to date most strategies have focused on activation of spinal circuits, more recent studies are investigating the value of engaging supraspinal circuits. Despite the apparent potential of pharmacological, biological, and genetic approaches, as yet none has proved more effective than physical therapeutic rehabilitation strategies. By making optimal use of the potential of the nervous system to respond to training, strategies can be developed that meet the unique needs of each person. To complement the development of optimal training interventions, it is valuable to have the ability to predict future walking function based on early clinical presentation, and to forecast responsiveness to training. A number of clinical prediction rules and association models based on common clinical measures have been developed with the intent, respectively, to predict future walking function based on early clinical presentation, and to delineate characteristics associated with responsiveness to training. Further, a number of variables that are correlated with walking function have been identified. Not surprisingly, most of these prediction rules, association models, and correlated variables incorporate measures of volitional lower extremity strength, illustrating the important influence of supraspinal centers in the production of walking behavior in humans. PMID:27673569

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-02-01

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

Standardization of a Hierarchical Transactive Control System

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

Hammerstrom, Donald J.; Oliver, Terry V.; Melton, Ronald B.

2010-12-03

The authors describe work they have conducted toward the generalization and standardization of the transactive control approach that was first demonstrated in the Olympic Peninsula Project for the management of a transmission constraint. The newly generalized approach addresses several potential shortfalls of the prior approach: First, the authors have formalized a hierarchical node structure which defines the nodes and the functional signal pathways between these nodes. Second, by fully generalizing the inputs, outputs, and functional responsibilities of each node, the authors make the approach available to a much wider set of responsive assets and operational objectives. Third, the new, generalizedmore » approach defines transactive signals that include the predicted day-ahead future. This predictive feature allows the market-like bids and offers to become resolved iteratively over time, thus allowing the behaviors of responsive assets to be called upon both for the present and as future dispatch decisions are being made. The hierarchical transactive control approach is a key feature of a proposed Pacific Northwest smart grid demonstration.« less

Drawing the future

PubMed Central

2008-01-01

Gas exchange between the plant and the atmosphere is regulated by controlling both the stomatal density and the aperture of the stomatal pore. Environmental factors such as light, the level of atmospheric CO2 and hormones regulate stomatal development and/or function. Because atmospheric CO2 levels have been rising since the Industrial Revolution, and it is predicted that they will continue doing so in the future, an understanding of the CO2 signalling mechanisms in the stomatal responses will help to know how plants were in the past and will allow predicting how they will respond to climate change in the near future. This article covers the recent knowledge of the CO2 signalling mechanisms that regulate both stomatal function and development. PMID:19513216

The Use of Planning in English and German (NRW) Geography School Textbooks

ERIC Educational Resources Information Center

Maier, Veit; Budke, Alexandra

2016-01-01

Although it is not possible to predict the future, at least some ideas can be developed through planning. Geography focuses on current social, environmental and spatial problems; however, it should, at the same time, teach us to plan its future handling. At school, this is a responsible role for the subject geography. This article compares how…

How to create a health care organization that can succeed in an unpredictable future.

PubMed

Olden, Peter C; Haynos, Jessika

2013-01-01

For those who manage organizations, it has been said that success does not come from predicting the future but instead comes from creating an organization that can succeed in an unpredictable future. Managers are responsible for creating such an organization. To do that, managers can apply management-related principles and methods. This article explains selected principles of organization structure, human resources, culture, decision making, and change management and how to apply them to health care organizations. If done well, that will help such organizations succeed in an unpredictable future.

Plaque Structural Stress Estimations Improve Prediction of Future Major Adverse Cardiovascular Events After Intracoronary Imaging.

PubMed

Brown, Adam J; Teng, Zhongzhao; Calvert, Patrick A; Rajani, Nikil K; Hennessy, Orla; Nerlekar, Nitesh; Obaid, Daniel R; Costopoulos, Charis; Huang, Yuan; Hoole, Stephen P; Goddard, Martin; West, Nick E J; Gillard, Jonathan H; Bennett, Martin R

2016-06-01

Although plaque rupture is responsible for most myocardial infarctions, few high-risk plaques identified by intracoronary imaging actually result in future major adverse cardiovascular events (MACE). Nonimaging markers of individual plaque behavior are therefore required. Rupture occurs when plaque structural stress (PSS) exceeds material strength. We therefore assessed whether PSS could predict future MACE in high-risk nonculprit lesions identified on virtual-histology intravascular ultrasound. Baseline nonculprit lesion features associated with MACE during long-term follow-up (median: 1115 days) were determined in 170 patients undergoing 3-vessel virtual-histology intravascular ultrasound. MACE was associated with plaque burden ≥70% (hazard ratio: 8.6; 95% confidence interval, 2.5-30.6; P<0.001) and minimal luminal area ≤4 mm(2) (hazard ratio: 6.6; 95% confidence interval, 2.1-20.1; P=0.036), although absolute event rates for high-risk lesions remained <10%. PSS derived from virtual-histology intravascular ultrasound was subsequently estimated in nonculprit lesions responsible for MACE (n=22) versus matched control lesions (n=22). PSS showed marked heterogeneity across and between similar lesions but was significantly increased in MACE lesions at high-risk regions, including plaque burden ≥70% (13.9±11.5 versus 10.2±4.7; P<0.001) and thin-cap fibroatheroma (14.0±8.9 versus 11.6±4.5; P=0.02). Furthermore, PSS improved the ability of virtual-histology intravascular ultrasound to predict MACE in plaques with plaque burden ≥70% (adjusted log-rank, P=0.003) and minimal luminal area ≤4 mm(2) (P=0.002). Plaques responsible for MACE had larger superficial calcium inclusions, which acted to increase PSS (P<0.05). Baseline PSS is increased in plaques responsible for MACE and improves the ability of intracoronary imaging to predict events. Biomechanical modeling may complement plaque imaging for risk stratification of coronary nonculprit lesions. © 2016 American Heart Association, Inc.

Validation of catchment models for predicting land-use and climate change impacts. 2. Case study for a Mediterranean catchment

NASA Astrophysics Data System (ADS)

Parkin, G.; O'Donnell, G.; Ewen, J.; Bathurst, J. C.; O'Connell, P. E.; Lavabre, J.

1996-02-01

Validation methods commonly used to test catchment models are not capable of demonstrating a model's fitness for making predictions for catchments where the catchment response is not known (including hypothetical catchments, and future conditions of existing catchments which are subject to land-use or climate change). This paper describes the first use of a new method of validation (Ewen and Parkin, 1996. J. Hydrol., 175: 583-594) designed to address these types of application; the method involves making 'blind' predictions of selected hydrological responses which are considered important for a particular application. SHETRAN (a physically based, distributed catchment modelling system) is tested on a small Mediterranean catchment. The test involves quantification of the uncertainty in four predicted features of the catchment response (continuous hydrograph, peak discharge rates, monthly runoff, and total runoff), and comparison of observations with the predicted ranges for these features. The results of this test are considered encouraging.

Optimal temperature for malaria transmission is dramaticallylower than previously predicted

USGS Publications Warehouse

Mordecai, Eerin A.; Paaijmans, Krijin P.; Johnson, Leah R.; Balzer, Christian; Ben-Horin, Tal; de Moor, Emily; McNally, Amy; Pawar, Samraat; Ryan, Sadie J.; Smith, Thomas C.; Lafferty, Kevin D.

2013-01-01

The ecology of mosquito vectors and malaria parasites affect the incidence, seasonal transmission and geographical range of malaria. Most malaria models to date assume constant or linear responses of mosquito and parasite life-history traits to temperature, predicting optimal transmission at 31 °C. These models are at odds with field observations of transmission dating back nearly a century. We build a model with more realistic ecological assumptions about the thermal physiology of insects. Our model, which includes empirically derived nonlinear thermal responses, predicts optimal malaria transmission at 25 °C (6 °C lower than previous models). Moreover, the model predicts that transmission decreases dramatically at temperatures > 28 °C, altering predictions about how climate change will affect malaria. A large data set on malaria transmission risk in Africa validates both the 25 °C optimum and the decline above 28 °C. Using these more accurate nonlinear thermal-response models will aid in understanding the effects of current and future temperature regimes on disease transmission.

Optimal temperature for malaria transmission is dramatically lower than previously predicted

USGS Publications Warehouse

Mordecai, Erin A.; Paaijmans, Krijn P.; Johnson, Leah R.; Balzer, Christian; Ben-Horin, Tal; de Moor, Emily; McNally, Amy; Pawar, Samraat; Ryan, Sadie J.; Smith, Thomas C.; Lafferty, Kevin D.

2013-01-01

The ecology of mosquito vectors and malaria parasites affect the incidence, seasonal transmission and geographical range of malaria. Most malaria models to date assume constant or linear responses of mosquito and parasite life-history traits to temperature, predicting optimal transmission at 31 °C. These models are at odds with field observations of transmission dating back nearly a century. We build a model with more realistic ecological assumptions about the thermal physiology of insects. Our model, which includes empirically derived nonlinear thermal responses, predicts optimal malaria transmission at 25 °C (6 °C lower than previous models). Moreover, the model predicts that transmission decreases dramatically at temperatures > 28 °C, altering predictions about how climate change will affect malaria. A large data set on malaria transmission risk in Africa validates both the 25 °C optimum and the decline above 28 °C. Using these more accurate nonlinear thermal-response models will aid in understanding the effects of current and future temperature regimes on disease transmission.

Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes.

PubMed

Brown, Jason L; Weber, Jennifer J; Alvarado-Serrano, Diego F; Hickerson, Michael J; Franks, Steven J; Carnaval, Ana C

2016-01-01

Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning. © 2016 Botanical Society of America.

Goal-directed EEG activity evoked by discriminative stimuli in reinforcement learning.

PubMed

Luque, David; Morís, Joaquín; Rushby, Jacqueline A; Le Pelley, Mike E

2015-02-01

In reinforcement learning (RL), discriminative stimuli (S) allow agents to anticipate the value of a future outcome, and the response that will produce that outcome. We examined this processing by recording EEG locked to S during RL. Incentive value of outcomes and predictive value of S were manipulated, allowing us to discriminate between outcome-related and response-related activity. S predicting the correct response differed from nonpredictive S in the P2. S paired with high-value outcomes differed from those paired with low-value outcomes in a frontocentral positivity and in the P3b. A slow negativity then distinguished between predictive and nonpredictive S. These results suggest that, first, attention prioritizes detection of informative S. Activation of mental representations of these informative S then retrieves representations of outcomes, which in turn retrieve representations of responses that previously produced those outcomes. © 2014 Society for Psychophysiological Research.

Predicting biomaterial property-dendritic cell phenotype relationships from the multivariate analysis of responses to polymethacrylates

PubMed Central

Kou, Peng Meng; Pallassana, Narayanan; Bowden, Rebeca; Cunningham, Barry; Joy, Abraham; Kohn, Joachim; Babensee, Julia E.

2011-01-01

Dendritic cells (DCs) play a critical role in orchestrating the host responses to a wide variety of foreign antigens and are essential in maintaining immune tolerance. Distinct biomaterials have been shown to differentially affect the phenotype of DCs, which suggested that biomaterials may be used to modulate immune response towards the biologic component in combination products. The elucidation of biomaterial property-DC phenotype relationships is expected to inform rational design of immuno-modulatory biomaterials. In this study, DC response to a set of 12 polymethacrylates (pMAs) was assessed in terms of surface marker expression and cytokine profile. Principal component analysis (PCA) determined that surface carbon correlated with enhanced DC maturation, while surface oxygen was associated with an immature DC phenotype. Partial square linear regression, a multivariate modeling approach, was implemented and successfully predicted biomaterial-induced DC phenotype in terms of surface marker expression from biomaterial properties with R2prediction = 0.76. Furthermore, prediction of DC phenotype was effective based on only theoretical chemical composition of the bulk polymers with R2prediction = 0.80. These results demonstrated that immune cell response can be predicted from biomaterial properties, and computational models will expedite future biomaterial design and selection. PMID:22136715

[Phenotypic trends and breeding values for canine congenital sensorineural deafness in Dalmatian dogs].

PubMed

Blum, Meike; Distl, Ottmar

2014-01-01

In the present study, breeding values for canine congenital sensorineural deafness, the presence of blue eyes and patches have been predicted using multivariate animal models to test the reliability of the breeding values for planned matings. The dataset consisted of 6669 German Dalmatian dogs born between 1988 and 2009. Data were provided by the Dalmatian kennel clubs which are members of the German Association for Dog Breeding and Husbandry (VDH). The hearing status for all dogs was evaluated using brainstem auditory evoked potentials. The reliability using the prediction error variance of breeding values and the realized reliability of the prediction of the phenotype of future progeny born in each one year between 2006 and 2009 were used as parameters to evaluate the goodness of prediction through breeding values. All animals from the previous birth years were used for prediction of the breeding values of the progeny in each of the up-coming birth years. The breeding values based on pedigree records achieved an average reliability of 0.19 for the future 1951 progeny. The predictive accuracy (R2) for the hearing status of single future progeny was at 1.3%. Combining breeding values for littermates increased the predictive accuracy to 3.5%. Corresponding values for maternal and paternal half-sib groups were at 3.2 and 7.3%. The use of breeding values for planned matings increases the phenotypic selection response over mass selection. The breeding values of sires may be used for planned matings because reliabilities and predictive accuracies for future paternal progeny groups were highest.

Future of Earth Orientation Predictions

DTIC Science & Technology

2010-01-01

introduced into the prediction process will increase . Potential drivers for change are discussed and possible directions for change are outlined. Keywords...is increasing as data latency has been reduced. However, all of these have been natural progressions; straightforward responses to improvements in...7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) U.S. Naval Observatory,3450 Massachusetts Ave NW,Washington,DC,20392 8. PERFORMING ORGANIZATION

Losing ground: past history and future fate of Arctic small mammals in a changing climate.

PubMed

Prost, Stefan; Guralnick, Robert P; Waltari, Eric; Fedorov, Vadim B; Kuzmina, Elena; Smirnov, Nickolay; van Kolfschoten, Thijs; Hofreiter, Michael; Vrieling, Klaas

2013-06-01

According to the IPCC, the global average temperature is likely to increase by 1.4-5.8 °C over the period from 1990 to 2100. In Polar regions, the magnitude of such climatic changes is even larger than in temperate and tropical biomes. This amplified response is particularly worrisome given that the so-far moderate warming is already impacting Arctic ecosystems. Predicting species responses to rapid warming in the near future can be informed by investigating past responses, as, like the rest of the planet, the Arctic experienced recurrent cycles of temperature increase and decrease (glacial-interglacial changes) in the past. In this study, we compare the response of two important prey species of the Arctic ecosystem, the collared lemming and the narrow-skulled vole, to Late Quaternary climate change. Using ancient DNA and Ecological Niche Modeling (ENM), we show that the two species, which occupy similar, but not identical ecological niches, show markedly different responses to climatic and environmental changes within broadly similar habitats. We empirically demonstrate, utilizing coalescent model-testing approaches, that collared lemming populations decreased substantially after the Last Glacial Maximum; a result consistent with distributional loss over the same period based on ENM results. Given this strong association, we projected the current niche onto future climate conditions based on IPCC 4.0 scenarios, and forecast accelerating loss of habitat along southern range boundaries with likely associated demographic consequences. Narrow-skulled vole distribution and demography, by contrast, was only moderately impacted by past climatic changes, but predicted future changes may begin to affect their current western range boundaries. Our work, founded on multiple lines of evidence suggests a future of rapidly geographically shifting Arctic small mammal prey communities, some of whom are on the edge of existence, and whose fate may have ramifications for the whole Arctic food web and ecosystem. © 2013 Blackwell Publishing Ltd.

Predicting pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a systematic review.

PubMed

Ryan, J E; Warrier, S K; Lynch, A C; Ramsay, R G; Phillips, W A; Heriot, A G

2016-03-01

Approximately 20% of patients treated with neoadjuvant chemoradiotherapy (nCRT) for locally advanced rectal cancer achieve a pathological complete response (pCR) while the remainder derive the benefit of improved local control and downstaging and a small proportion show a minimal response. The ability to predict which patients will benefit would allow for improved patient stratification directing therapy to those who are likely to achieve a good response, thereby avoiding ineffective treatment in those unlikely to benefit. A systematic review of the English language literature was conducted to identify pathological factors, imaging modalities and molecular factors that predict pCR following chemoradiotherapy. PubMed, MEDLINE and Cochrane Database searches were conducted with the following keywords and MeSH search terms: 'rectal neoplasm', 'response', 'neoadjuvant', 'preoperative chemoradiation', 'tumor response'. After review of title and abstracts, 85 articles addressing the prediction of pCR were selected. Clear methods to predict pCR before chemoradiotherapy have not been defined. Clinical and radiological features of the primary cancer have limited ability to predict response. Molecular profiling holds the greatest potential to predict pCR but adoption of this technology will require greater concordance between cohorts for the biomarkers currently under investigation. At present no robust markers of the prediction of pCR have been identified and the topic remains an area for future research. This review critically evaluates existing literature providing an overview of the methods currently available to predict pCR to nCRT for locally advanced rectal cancer. The review also provides a comprehensive comparison of the accuracy of each modality. Colorectal Disease © 2015 The Association of Coloproctology of Great Britain and Ireland.

[Media for 21st century--towards human communication media].

PubMed

Harashima, H

2000-05-01

Today, with the approach of the 21st century, attention is focused on multi-media communications combining computer, visual and audio technologies. This article discusses the communication media target and the technological problems constituting the nucleus of multi-media. The communication media is becoming an environment from which no one can escape. Since the media has such a great power, what is needed now is not to predict the future technologies, but to estimate the future world and take to responsibility for future environments.

See it with feeling: affective predictions during object perception

PubMed Central

Barrett, L.F.; Bar, Moshe

2009-01-01

People see with feeling. We ‘gaze’, ‘behold’, ‘stare’, ‘gape’ and ‘glare’. In this paper, we develop the hypothesis that the brain's ability to see in the present incorporates a representation of the affective impact of those visual sensations in the past. This representation makes up part of the brain's prediction of what the visual sensations stand for in the present, including how to act on them in the near future. The affective prediction hypothesis implies that responses signalling an object's salience, relevance or value do not occur as a separate step after the object is identified. Instead, affective responses support vision from the very moment that visual stimulation begins. PMID:19528014

Applications of NASA and NOAA Satellite Observations by NASA's Short-term Prediction Research and Transition (SPoRT) Center in Response to Natural Disasters

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Burks, Jason E.; McGrath, Kevin M.; Jedlovec, Gary J.

2012-01-01

NASA s Short-term Prediction Research and Transition (SPoRT) Center supports the transition of unique NASA and NOAA research activities to the operational weather forecasting community. SPoRT emphasizes real-time analysis and prediction out to 48 hours. SPoRT partners with NOAA s National Weather Service (NWS) Weather Forecast Offices (WFOs) and National Centers to improve current products, demonstrate future satellite capabilities and explore new data assimilation techniques. Recently, the SPoRT Center has been involved in several activities related to disaster response, in collaboration with NOAA s National Weather Service, NASA s Applied Sciences Disasters Program, and other partners.

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.

Learning Temporal Statistics for Sensory Predictions in Aging.

PubMed

Luft, Caroline Di Bernardi; Baker, Rosalind; Goldstone, Aimee; Zhang, Yang; Kourtzi, Zoe

2016-03-01

Predicting future events based on previous knowledge about the environment is critical for successful everyday interactions. Here, we ask which brain regions support our ability to predict the future based on implicit knowledge about the past in young and older age. Combining behavioral and fMRI measurements, we test whether training on structured temporal sequences improves the ability to predict upcoming sensory events; we then compare brain regions involved in learning predictive structures between young and older adults. Our behavioral results demonstrate that exposure to temporal sequences without feedback facilitates the ability of young and older adults to predict the orientation of an upcoming stimulus. Our fMRI results provide evidence for the involvement of corticostriatal regions in learning predictive structures in both young and older learners. In particular, we showed learning-dependent fMRI responses for structured sequences in frontoparietal regions and the striatum (putamen) for young adults. However, for older adults, learning-dependent activations were observed mainly in subcortical (putamen, thalamus) regions but were weaker in frontoparietal regions. Significant correlations of learning-dependent behavioral and fMRI changes in these regions suggest a strong link between brain activations and behavioral improvement rather than general overactivation. Thus, our findings suggest that predicting future events based on knowledge of temporal statistics engages brain regions involved in implicit learning in both young and older adults.

Systems analysis of apoptosis protein expression allows the case-specific prediction of cell death responsiveness of melanoma cells

PubMed Central

Passante, E; Würstle, M L; Hellwig, C T; Leverkus, M; Rehm, M

2013-01-01

Many cancer entities and their associated cell line models are highly heterogeneous in their responsiveness to apoptosis inducers and, despite a detailed understanding of the underlying signaling networks, cell death susceptibility currently cannot be predicted reliably from protein expression profiles. Here, we demonstrate that an integration of quantitative apoptosis protein expression data with pathway knowledge can predict the cell death responsiveness of melanoma cell lines. By a total of 612 measurements, we determined the absolute expression (nM) of 17 core apoptosis regulators in a panel of 11 melanoma cell lines, and enriched these data with systems-level information on apoptosis pathway topology. By applying multivariate statistical analysis and multi-dimensional pattern recognition algorithms, the responsiveness of individual cell lines to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) or dacarbazine (DTIC) could be predicted with very high accuracy (91 and 82% correct predictions), and the most effective treatment option for individual cell lines could be pre-determined in silico. In contrast, cell death responsiveness was poorly predicted when not taking knowledge on protein–protein interactions into account (55 and 36% correct predictions). We also generated mathematical predictions on whether anti-apoptotic Bcl-2 family members or x-linked inhibitor of apoptosis protein (XIAP) can be targeted to enhance TRAIL responsiveness in individual cell lines. Subsequent experiments, making use of pharmacological Bcl-2/Bcl-xL inhibition or siRNA-based XIAP depletion, confirmed the accuracy of these predictions. We therefore demonstrate that cell death responsiveness to TRAIL or DTIC can be predicted reliably in a large number of melanoma cell lines when investigating expression patterns of apoptosis regulators in the context of their network-level interplay. The capacity to predict responsiveness at the cellular level may contribute to personalizing anti-cancer treatments in the future. PMID:23933815

Clinical utility of pretreatment prediction of chemoradiotherapy response in rectal cancer: a review.

PubMed

Yoo, Byong Chul; Yeo, Seung-Gu

2017-03-01

Approximately 20% of all patients with locally advanced rectal cancer experience pathologically complete responses following neoadjuvant chemoradiotherapy (CRT) and standard surgery. The utility of radical surgery for patients exhibiting good CRT responses has been challenged. Organ-sparing strategies for selected patients exhibiting complete clinical responses include local excision or no immediate surgery. The subjects of this tailored management are patients whose presenting disease corresponds to current indications of neoadjuvant CRT, and their post-CRT tumor response is assessed by clinical and radiological examinations. However, a model predictive of the CRT response, applied before any treatment commenced, would be valuable to facilitate such a personalized approach. This would increase organ preservation, particularly in patients for whom upfront CRT is not generally prescribed. Molecular biomarkers hold the greatest promise for development of a pretreatment predictive model of CRT response. A combination of clinicopathological, radiological, and molecular markers will be necessary to render the model robust. Molecular research will also contribute to the development of drugs that can overcome the radioresistance of rectal tumors. Current treatments for rectal cancer are based on the expected prognosis given the presenting disease extent. In the future, treatment schemes may be modified by including the predicted CRT response evaluated at presentation.

Measurement of historical cliff-top changes and estimation of future trends using GIS data between Bridlington and Hornsea - Holderness Coast (UK)

NASA Astrophysics Data System (ADS)

Castedo, Ricardo; de la Vega-Panizo, Rogelio; Fernández-Hernández, Marta; Paredes, Carlos

2015-02-01

A key requirement for effective coastal zone management is good knowledge of historical rates of change and the ability to predict future shoreline evolution, especially for rapidly eroding areas. Historical shoreline recession analysis was used for the prediction of future cliff shoreline positions along a section of 9 km between Bridlington and Hornsea, on the northern area of the Holderness Coast, UK. The analysis was based on historical maps and aerial photographs dating from 1852 to 2011 using the Digital Shoreline Analysis System (DSAS) 4.3, extension of ESRI's ArcInfo 10.×. The prediction of future shorelines was performed for the next 40 years using a variety of techniques, ranging from extrapolation from historical data, geometric approaches like the historical trend analysis, to a process-response numerical model that incorporates physically-based equations and geotechnical stability analysis. With climate change and sea-level rise implying that historical rates of change may not be a reliable guide for the future, enhanced visualization of the evolving coastline has the potential to improve awareness of these changing conditions. Following the IPCC, 2013 report, two sea-level rise rates, 2 mm/yr and 6 mm/yr, have been used to estimate future shoreline conditions. This study illustrated that good predictive models, once their limitations are estimated or at least defined, are available for use by managers, planners, engineers, scientists and the public to make better decisions regarding coastal management, development, and erosion-control strategies.

Let's Walk Outdoors! Self-Paced Walking Outdoors Improves Future Intention to Exercise in Women With Obesity.

PubMed

Krinski, Kleverton; Machado, Daniel G S; Lirani, Luciana S; DaSilva, Sergio G; Costa, Eduardo C; Hardcastle, Sarah J; Elsangedy, Hassan M

2017-04-01

In order to examine whether environmental settings influence psychological and physiological responses of women with obesity during self-paced walking, 38 women performed two exercise sessions (treadmill and outdoors) for 30 min, where oxygen uptake, heart rate, ratings of perceived exertion, affect, attentional focus, enjoyment, and future intentions to walk were analyzed. Physiological responses were similar during both sessions. However, during outdoor exercise, participants displayed higher externally focused attention, positive affect, and lower ratings of perceived exertion, followed by greater enjoyment and future intention to participate in outdoor walking. The more externally focused attention predicted greater future intentions to participate in walking. Therefore, women with obesity self-selected an appropriate exercise intensity to improve fitness and health in both environmental settings. Also, self-paced outdoor walking presented improved psychological responses. Health care professionals should consider promoting outdoor forms of exercise to maximize psychological benefits and promote long-term adherence to a physically active lifestyle.

Achievable future conditions as a framework for guiding forest conservation and management

Treesearch

S.W. Golladay; K.L. Martin; J. M. Vose; D. N. Wear; A.P. Covich; R.J. Hobbs; Kier Klepzig; G.E. Likens; R.J. Naiman; A.W. Shearer

2016-01-01

We contend that traditional approaches to forest conservation and management will be inadequate given the predicted scale of social-economic and biophysical changes in the 21st century. New approaches, focused on anticipating and guiding ecological responses to change, are urgently needed to ensure the full value of forest ecosystem services for future generations....

Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood

USGS Publications Warehouse

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments1, 2, making assessments of SLR-induced hazards essential for informed decision making3. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30 × 30 m resolution predictions for more than 38,000 km2 of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

A Statistical Weather-Driven Streamflow Model: Enabling future flow predictions in data-scarce headwater streams

NASA Astrophysics Data System (ADS)

Rosner, A.; Letcher, B. H.; Vogel, R. M.

2014-12-01

Predicting streamflow in headwaters and over a broad spatial scale pose unique challenges due to limited data availability. Flow observation gages for headwaters streams are less common than for larger rivers, and gages with records lengths of ten year or more are even more scarce. Thus, there is a great need for estimating streamflows in ungaged or sparsely-gaged headwaters. Further, there is often insufficient basin information to develop rainfall-runoff models that could be used to predict future flows under various climate scenarios. Headwaters in the northeastern U.S. are of particular concern to aquatic biologists, as these stream serve as essential habitat for native coldwater fish. In order to understand fish response to past or future environmental drivers, estimates of seasonal streamflow are needed. While there is limited flow data, there is a wealth of data for historic weather conditions. Observed data has been modeled to interpolate a spatially continuous historic weather dataset. (Mauer et al 2002). We present a statistical model developed by pairing streamflow observations with precipitation and temperature information for the same and preceding time-steps. We demonstrate this model's use to predict flow metrics at the seasonal time-step. While not a physical model, this statistical model represents the weather drivers. Since this model can predict flows not directly tied to reference gages, we can generate flow estimates for historic as well as potential future conditions.

Clinical utility of C-reactive protein to predict treatment response during cystic fibrosis pulmonary exacerbations.

PubMed

Sharma, Ashutosh; Kirkpatrick, Gordon; Chen, Virginia; Skolnik, Kate; Hollander, Zsuzsanna; Wilcox, Pearce; Quon, Bradley S

2017-01-01

C-reactive protein (CRP) is a systemic marker of inflammation that correlates with disease status in cystic fibrosis (CF). The clinical utility of CRP measurement to guide pulmonary exacerbation (PEx) treatment decisions remains uncertain. To determine whether monitoring CRP during PEx treatment can be used to predict treatment response. We hypothesized that early changes in CRP can be used to predict treatment response. We reviewed all PEx events requiring hospitalization for intravenous (IV) antibiotics over 2 years at our institution. 83 PEx events met our eligibility criteria. CRP levels from admission to day 5 were evaluated to predict treatment non-response, using a modified version of a prior published composite definition. CRP was also evaluated to predict time until next exacerbation (TUNE). 53% of 83 PEx events were classified as treatment non-response. Paradoxically, 24% of PEx events were characterized by a ≥ 50% increase in CRP levels within the first five days of treatment. Absolute change in CRP from admission to day 5 was not associated with treatment non-response (p = 0.58). Adjusted for FEV1% predicted, admission log10 CRP was associated with treatment non-response (OR: 2.39; 95% CI: 1.14 to 5.91; p = 0.03) and shorter TUNE (HR: 1.60; 95% CI: 1.13 to 2.27; p = 0.008). The area under the receiver operating characteristics (ROC) curve of admission CRP to predict treatment non-response was 0.72 (95% CI 0.61-0.83; p<0.001). 23% of PEx events were characterized by an admission CRP of > 75 mg/L with a specificity of 90% for treatment non-response. Admission CRP predicts treatment non-response and time until next exacerbation. A very elevated admission CRP (>75mg/L) is highly specific for treatment non-response and might be used to target high-risk patients for future interventional studies aimed at improving exacerbation outcomes.

Reactive stepping behaviour in response to forward loss of balance predicts future falls in community-dwelling older adults.

PubMed

Carty, Christopher P; Cronin, Neil J; Nicholson, Deanne; Lichtwark, Glen A; Mills, Peter M; Kerr, Graham; Cresswell, Andrew G; Barrett, Rod S

2015-01-01

a fall occurs when an individual experiences a loss of balance from which they are unable to recover. Assessment of balance recovery ability in older adults may therefore help to identify individuals at risk of falls. The purpose of this 12-month prospective study was to assess whether the ability to recover from a forward loss of balance with a single step across a range of lean magnitudes was predictive of falls. two hundred and one community-dwelling older adults, aged 65-90 years, underwent baseline testing of sensori-motor function and balance recovery ability followed by 12-month prospective falls evaluation. Balance recovery ability was defined by whether participants required either single or multiple steps to recover from forward loss of balance from three lean magnitudes, as well as the maximum lean magnitude participants could recover from with a single step. forty-four (22%) participants experienced one or more falls during the follow-up period. Maximal recoverable lean magnitude and use of multiple steps to recover at the 15% body weight (BW) and 25%BW lean magnitudes significantly predicted a future fall (odds ratios 1.08-1.26). The Physiological Profile Assessment, an established tool that assesses variety of sensori-motor aspects of falls risk, was also predictive of falls (Odds ratios 1.22 and 1.27, respectively), whereas age, sex, postural sway and timed up and go were not predictive. reactive stepping behaviour in response to forward loss of balance and physiological profile assessment are independent predictors of a future fall in community-dwelling older adults. Exercise interventions designed to improve reactive stepping behaviour may protect against future falls. © The Author 2014. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

PubMed

Ellis, Alicia M; Post, Eric

2004-03-31

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

Nonlinear analyses of composite aerospace structures in sonic fatigue

NASA Technical Reports Server (NTRS)

Mei, Chuh

1993-01-01

This report summarizes the semiannual research progress, accomplishments, and future plans performed under the NASA Langley Research Center Grant No. NAG-1-1358. The primary research effort of this project is the development of analytical methods for the prediction of nonlinear random response of composite aerospace structures subjected to combined acoustic and thermal loads. The progress, accomplishments, and future plates on four sonic fatigue research topics are described. The sonic fatigue design and passive control of random response of shape memory alloy hybrid composites presented in section 4, which is suited especially for HSCT, is a new initiative.

Nonlinear analyses of composite aerospace structures in sonic fatigue

NASA Astrophysics Data System (ADS)

Mei, Chuh

1993-06-01

This report summarizes the semiannual research progress, accomplishments, and future plans performed under the NASA Langley Research Center Grant No. NAG-1-1358. The primary research effort of this project is the development of analytical methods for the prediction of nonlinear random response of composite aerospace structures subjected to combined acoustic and thermal loads. The progress, accomplishments, and future plates on four sonic fatigue research topics are described. The sonic fatigue design and passive control of random response of shape memory alloy hybrid composites presented in section 4, which is suited especially for HSCT, is a new initiative.

Agricultural drought in a future climate: results from 15 global climate models participating in the IPCC 4th assessment

NASA Astrophysics Data System (ADS)

Wang, Guiling

2005-12-01

This study examines the impact of greenhouse gas warming on soil moisture based on predictions of 15 global climate models by comparing the after-stabilization climate in the SRESA1b experiment with the pre-industrial control climate. The models are consistent in predicting summer dryness and winter wetness in only part of the northern middle and high latitudes. Slightly over half of the models predict year-round wetness in central Eurasia and/or year-round dryness in Siberia and mid-latitude Northeast Asia. One explanation is offered that relates such lack of seasonality to the carryover effect of soil moisture storage from season to season. In the tropics and subtropics, a decrease of soil moisture is the dominant response. The models are especially consistent in predicting drier soil over the southwest North America, Central America, the Mediterranean, Australia, and the South Africa in all seasons, and over much of the Amazon and West Africa in the June July August (JJA) season and the Asian monsoon region in the December January February (DJF) season. Since the only major areas of future wetness predicted with a high level of model consistency are part of the northern middle and high latitudes during the non-growing season, it is suggested that greenhouse gas warming will cause a worldwide agricultural drought. Over regions where there is considerable consistency among the analyzed models in predicting the sign of soil moisture changes, there is a wide range of magnitudes of the soil moisture response, indicating a high degree of model dependency in terrestrial hydrological sensitivity. A major part of the inter-model differences in the sensitivity of soil moisture response are attributable to differences in land surface parameterization.

Associations of Affective Responses During Free-Living Physical Activity and Future Physical Activity Levels: an Ecological Momentary Assessment Study.

PubMed

Liao, Yue; Chou, Chih-Ping; Huh, Jimi; Leventhal, Adam; Dunton, Genevieve

2017-08-01

Affective response during physical activity may influence motivation to perform future physical activity behavior. However, affective response during physical activity is often assessed under controlled laboratory conditions. The current study used ecological momentary assessment (EMA) to capture affective responses during free-living physical activity performed by adults, and determined whether these affective responses predict future moderate-to-vigorous physical activity (MVPA) levels after 6 and 12 months. At baseline, electronic EMA surveys were randomly prompted across 4 days asking about current activities and affective states (e.g., happy, stressed, energetic, tired). Affective response during physical activity was operationalized as the level of positive or negative affect reported when concurrent physical activity (e.g., exercise or sports) was also reported. Data were available for 82 adults. Future levels of moderate-to-vigorous physical activity (MVPA) were measured using accelerometers, worn for seven consecutive days at 6 and 12 months after the baseline assessment. Feeling more energetic during physical activity was associated with performing more minutes of daily MVPA after both 6 and 12 months. Feeling less negative affect during physical activity was associated with engaging in more daily MVPA minutes after 12 months only. This study demonstrated how EMA can be used to capture affective responses during free-living physical activity. Results found that feelings more energetic and less negative during physical activity were associated with more future physical activity, suggesting that positive emotional benefits may reinforce behavior.

Genomic signals of selection predict climate-driven population declines in a migratory bird.

PubMed

Bay, Rachael A; Harrigan, Ryan J; Underwood, Vinh Le; Gibbs, H Lisle; Smith, Thomas B; Ruegg, Kristen

2018-01-05

The ongoing loss of biodiversity caused by rapid climatic shifts requires accurate models for predicting species' responses. Despite evidence that evolutionary adaptation could mitigate climate change impacts, evolution is rarely integrated into predictive models. Integrating population genomics and environmental data, we identified genomic variation associated with climate across the breeding range of the migratory songbird, yellow warbler ( Setophaga petechia ). Populations requiring the greatest shifts in allele frequencies to keep pace with future climate change have experienced the largest population declines, suggesting that failure to adapt may have already negatively affected populations. Broadly, our study suggests that the integration of genomic adaptation can increase the accuracy of future species distribution models and ultimately guide more effective mitigation efforts. Copyright © 2018, American Association for the Advancement of Science.

Discrimination of amygdala response predicts future separation anxiety in youth with early deprivation.

PubMed

Green, Shulamite A; Goff, Bonnie; Gee, Dylan G; Gabard-Durnam, Laurel; Flannery, Jessica; Telzer, Eva H; Humphreys, Kathryn L; Louie, Jennifer; Tottenham, Nim

2016-10-01

Significant disruption in caregiving is associated with increased internalizing symptoms, most notably heightened separation anxiety symptoms during childhood. It is also associated with altered functional development of the amygdala, a neurobiological correlate of anxious behavior. However, much less is known about how functional alterations of amygdala predict individual differences in anxiety. Here, we probed amygdala function following institutional caregiving using very subtle social-affective stimuli (trustworthy and untrustworthy faces), which typically result in large differences in amygdala signal, and change in separation anxiety behaviors over a 2-year period. We hypothesized that the degree of differentiation of amygdala signal to trustworthy versus untrustworthy face stimuli would predict separation anxiety symptoms. Seventy-four youths mean (SD) age = 9.7 years (2.64) with and without previous institutional care, who were all living in families at the time of testing, participated in an fMRI task designed to examine differential amygdala response to trustworthy versus untrustworthy faces. Parents reported on their children's separation anxiety symptoms at the time of scan and again 2 years later. Previous institutional care was associated with diminished amygdala signal differences and behavioral differences to the contrast of untrustworthy and trustworthy faces. Diminished differentiation of these stimuli types predicted more severe separation anxiety symptoms 2 years later. Older age at adoption was associated with diminished differentiation of amygdala responses. A history of institutional care is associated with reduced differential amygdala responses to social-affective cues of trustworthiness that are typically exhibited by comparison samples. Individual differences in the degree of amygdala differential responding to these cues predict the severity of separation anxiety symptoms over a 2-year period. These findings provide a biological mechanism to explain the associations between early caregiving adversity and individual differences in internalizing symptomology during development, thereby contributing to individualized predictions of future clinical outcomes. © 2016 Association for Child and Adolescent Mental Health.

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.

Review of Nearshore Morphologic Prediction

NASA Astrophysics Data System (ADS)

Plant, N. G.; Dalyander, S.; Long, J.

2014-12-01

The evolution of the world's erodible coastlines will determine the balance between the benefits and costs associated with human and ecological utilization of shores, beaches, dunes, barrier islands, wetlands, and estuaries. So, we would like to predict coastal evolution to guide management and planning of human and ecological response to coastal changes. After decades of research investment in data collection, theoretical and statistical analysis, and model development we have a number of empirical, statistical, and deterministic models that can predict the evolution of the shoreline, beaches, dunes, and wetlands over time scales of hours to decades, and even predict the evolution of geologic strata over the course of millennia. Comparisons of predictions to data have demonstrated that these models can have meaningful predictive skill. But these comparisons also highlight the deficiencies in fundamental understanding, formulations, or data that are responsible for prediction errors and uncertainty. Here, we review a subset of predictive models of the nearshore to illustrate tradeoffs in complexity, predictive skill, and sensitivity to input data and parameterization errors. We identify where future improvement in prediction skill will result from improved theoretical understanding, and data collection, and model-data assimilation.

A case of collective responsibility: who else was to blame for the Columbine high school shootings?

PubMed

Lickel, Brian; Schmader, Toni; Hamilton, David L

2003-02-01

Two studies examined perceptions of collective responsibility for the April 20, 1999, shootings at Columbine High School in Littleton, Colorado. Collective responsibility refers to the perception that others, besides the wrongdoers themselves, are responsible for the event. In Study 1, the authors assessed perceptions of the shooters' parents and their peer group (the Trenchcoat Mafia), whereas Study 2 tested perceptions of collective responsibility across a range of groups. In both studies, perceptions of a target group's entitativity predicted judgments of collective responsibility. This relationship was mediated by two situational construals that justify applying collective responsibility: responsibility by commission (encouraging or facilitating the event) and responsibility by omission (failing to prevent the event). Study 2 also determined that perceptions of authority predicted judgments of collective responsibility for the Columbine shootings and was mediated by inferences of omission. Future directions in collective responsibility research are discussed. Copyright 2003 Society for Personality and Social Psychology, Inc.

Making smart social judgments takes time: infants' recruitment of goal information when generating action predictions.

PubMed

Krogh-Jespersen, Sheila; Woodward, Amanda L

2014-01-01

Previous research has shown that young infants perceive others' actions as structured by goals. One open question is whether the recruitment of this understanding when predicting others' actions imposes a cognitive challenge for young infants. The current study explored infants' ability to utilize their knowledge of others' goals to rapidly predict future behavior in complex social environments and distinguish goal-directed actions from other kinds of movements. Fifteen-month-olds (N = 40) viewed videos of an actor engaged in either a goal-directed (grasping) or an ambiguous (brushing the back of her hand) action on a Tobii eye-tracker. At test, critical elements of the scene were changed and infants' predictive fixations were examined to determine whether they relied on goal information to anticipate the actor's future behavior. Results revealed that infants reliably generated goal-based visual predictions for the grasping action, but not for the back-of-hand behavior. Moreover, response latencies were longer for goal-based predictions than for location-based predictions, suggesting that goal-based predictions are cognitively taxing. Analyses of areas of interest indicated that heightened attention to the overall scene, as opposed to specific patterns of attention, was the critical indicator of successful judgments regarding an actor's future goal-directed behavior. These findings shed light on the processes that support "smart" social behavior in infants, as it may be a challenge for young infants to use information about others' intentions to inform rapid predictions.

Impact of climate change on mercury concentrations and deposition in the eastern United States.

PubMed

Megaritis, Athanasios G; Murphy, Benjamin N; Racherla, Pavan N; Adams, Peter J; Pandis, Spyros N

2014-07-15

The global-regional climate-air pollution modeling system (GRE-CAPS) was applied over the eastern United States to study the impact of climate change on the concentration and deposition of atmospheric mercury. Summer and winter periods (300 days for each) were simulated, and the present-day model predictions (2000s) were compared to the future ones (2050s) assuming constant emissions. Climate change affects Hg(2+) concentrations in both periods. On average, atmospheric Hg(2+) levels are predicted to increase in the future by 3% in summer and 5% in winter respectively due to enhanced oxidation of Hg(0) under higher temperatures. The predicted concentration change of Hg(2+) was found to vary significantly in space due to regional-scale changes in precipitation, ranging from -30% to 30% during summer and -20% to 40% during winter. Particulate mercury, Hg(p) has a similar spatial response to climate change as Hg(2+), while Hg(0) levels are not predicted to change significantly. In both periods, the response of mercury deposition to climate change varies spatially with an average predicted increase of 6% during summer and 4% during winter. During summer, deposition increases are predicted mostly in the western parts of the domain while mercury deposition is predicted to decrease in the Northeast and also in many areas in the Midwest and Southeast. During winter mercury deposition is predicted to change from -30% to 50% mainly due to the changes in rainfall and the corresponding changes in wet deposition. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Treesearch

Franco Biondi; Scotty Strachan

2011-01-01

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

Infrared heater system for warming tropical forest understory plants and soils

Treesearch

Bruce A. Kimball; Aura M. Alonso-Rodríguez; Molly A. Cavaleri; Sasha C. Reed; Grizelle González; Tana E. Wood

2018-01-01

The response of tropical forests to global warming is one of the largest uncertainties in predicting the future carbon balance of Earth. To determine the likely effects of elevated temperatures on tropical forest understory plants and soils, as well as other ecosystems, an infrared (IR) heater system was developed to provide in situ warming for the Tropical Responses...

Developing Civic Engagement in University Education: Predicting Current and Future Engagement in Community Services

ERIC Educational Resources Information Center

Li, Manyu; Frieze, Irene Hanson

2016-01-01

One of the important goals of education is for students to learn to be responsible civic participants. Thus, the time students spend in college is invaluable. It is important that students learn to participate and be responsible citizens of their community during their time in college (Giles and Eyler in "Mich J Community Serv Learn"…

Data-Constrained Projections of Methane Fluxes in a Northern Minnesota Peatland in Response to Elevated CO2 and Warming

Treesearch

Shuang Ma; Jiang Jiang; Yuanyuan Huang; Zheng Shi; Rachel M. Wilson; Daniel Ricciuto; Stephen D. Sebestyen; Paul J. Hanson; Yiqi Luo

2017-01-01

Large uncertainties exist in predicting responses of wetland methane (CH4) fluxes to future climate change. However, sources of the uncertainty have not been clearly identified despite the fact that methane production and emission processes have been extensively explored. In this study, we took advantage of manual CH4 flux...

Reflecting on the Present and Looking Ahead: A Response to Shuler

ERIC Educational Resources Information Center

Tobias, Evan S.

2014-01-01

In considering how policy work might forward arts education, it is helpful to reflect on the present state of music and arts education while looking ahead at future challenges and possibilities. This response to Shuler's (2001) set of predictions related to music education and policy in the twenty-first century addresses such work in the…

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

Treesearch

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

2010-01-01

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

Temperament and Parenting during the First Year of Life Predict Future Child Conduct Problems

PubMed Central

Lahey, Benjamin B.; Van Hulle, Carol A.; Keenan, Kate; Rathouz, Paul J.; D’Onofrio, Brian M.; Rodgers, Joseph Lee; Waldman, Irwin D.

2010-01-01

Predictive associations between parenting and temperament during the first year of life and child conduct problems were assessed longitudinally in 1,863 offspring of a representative sample of women. Maternal ratings of infant fussiness, activity level, predictability, and positive affect each independently predicted maternal ratings of conduct problems during ages 4–13 years. Furthermore, a significant interaction indicated that infants who were both low in fussiness and high in predictability were at very low risk for future conduct problems. Fussiness was a stronger predictor of conduct problems in boys whereas fearfulness was a stronger predictor in girls. Conduct problems also were robustly predicted by low levels of early mother-report cognitive stimulation. Interviewer-rated maternal responsiveness was a robust predictor of conduct problems, but only among infants low in fearfulness. Spanking during infancy predicted slightly more severe conduct problems, but the prediction was moderated by infant fussiness and positive affect. Thus, individual differences in risk for mother-rated conduct problems across childhood are already partly evident in maternal ratings of temperament during the first year of life and are predicted by early parenting and parenting-by-temperament interactions. PMID:18568397

Cetacean range and climate in the eastern North Atlantic: future predictions and implications for conservation.

PubMed

Lambert, Emily; Pierce, Graham J; Hall, Karen; Brereton, Tom; Dunn, Timothy E; Wall, Dave; Jepson, Paul D; Deaville, Rob; MacLeod, Colin D

2014-06-01

There is increasing evidence that the distributions of a large number of species are shifting with global climate change as they track changing surface temperatures that define their thermal niche. Modelling efforts to predict species distributions under future climates have increased with concern about the overall impact of these distribution shifts on species ecology, and especially where barriers to dispersal exist. Here we apply a bio-climatic envelope modelling technique to investigate the impacts of climate change on the geographic range of ten cetacean species in the eastern North Atlantic and to assess how such modelling can be used to inform conservation and management. The modelling process integrates elements of a species' habitat and thermal niche, and employs "hindcasting" of historical distribution changes in order to verify the accuracy of the modelled relationship between temperature and species range. If this ability is not verified, there is a risk that inappropriate or inaccurate models will be used to make future predictions of species distributions. Of the ten species investigated, we found that while the models for nine could successfully explain current spatial distribution, only four had a good ability to predict distribution changes over time in response to changes in water temperature. Applied to future climate scenarios, the four species-specific models with good predictive abilities indicated range expansion in one species and range contraction in three others, including the potential loss of up to 80% of suitable white-beaked dolphin habitat. Model predictions allow identification of affected areas and the likely time-scales over which impacts will occur. Thus, this work provides important information on both our ability to predict how individual species will respond to future climate change and the applicability of predictive distribution models as a tool to help construct viable conservation and management strategies. © 2014 John Wiley & Sons Ltd.

Developmental trajectory from early responses to transgressions to future antisocial behavior: Evidence for the role of the parent-child relationship from two longitudinal studies

PubMed Central

Kim, Sanghag; Kochanska, Grazyna; Boldt, Lea J.; Nordling, Jamie Koenig; O’Bleness, Jessica J.

2014-01-01

Parent-child relationships are critical in development, but much remains to be learned about mechanisms of their impact. We examined early parent-child relationship as a moderator of the developmental trajectory from children’s affective and behavioral responses to transgressions to future antisocial, externalizing behavior problems in Family Study (102 community mothers, fathers, and infants, followed through age 8) and Play Study (186 low-income, diverse mothers and toddlers, followed for 10 months). The relationship quality was indexed by attachment security in Family Study and maternal responsiveness in Play Study. Responses to transgressions (tense discomfort and reparation) were observed in laboratory mishaps that led children to believe they had damaged a valued object. Antisocial outcomes were rated by parents. In both studies, early relationship moderated the future developmental trajectory: Children’s attenuated tense discomfort predicted more antisocial outcomes, but only in insecure or unresponsive relationships. That risk was defused in secure or responsive relationships. Moderated mediation analyses in Family Study indicated that the links between low tense discomfort and future antisocial behavior in insecure parent-child dyads were mediated by parental stronger discipline pressure. By influencing indirectly future developmental sequelae, early relationship may increase or decrease the probability that the parent-child dyad will embark on a path toward antisocial outcomes. PMID:24280347

Developmental trajectory from early responses to transgressions to future antisocial behavior: evidence for the role of the parent-child relationship from two longitudinal studies.

PubMed

Kim, Sanghag; Kochanska, Grazyna; Boldt, Lea J; Nordling, Jamie Koenig; O'Bleness, Jessica J

2014-02-01

Parent-child relationships are critical in development, but much remains to be learned about the mechanisms of their impact. We examined the early parent-child relationship as a moderator of the developmental trajectory from children's affective and behavioral responses to transgressions to future antisocial, externalizing behavior problems in the Family Study (102 community mothers, fathers, and infants, followed through age 8) and the Play Study (186 low-income, diverse mothers and toddlers, followed for 10 months). The relationship quality was indexed by attachment security in the Family Study and maternal responsiveness in the Play Study. Responses to transgressions (tense discomfort and reparation) were observed in laboratory mishaps wherein children believed they had damaged a valued object. Antisocial outcomes were rated by parents. In both studies, early relationships moderated the future developmental trajectory: diminished tense discomfort predicted more antisocial outcomes, but only in insecure or unresponsive relationships. That risk was defused in secure or responsive relationships. Moderated mediation analyses in the Family Study indicated that the links between diminished tense discomfort and future antisocial behavior in insecure parent-child dyads were mediated by stronger discipline pressure from parents. By indirectly influencing future developmental sequelae, early relationships may increase or decrease the probability that the parent-child dyad will embark on a path toward antisocial outcomes.

Modeling the potential impacts of climate change on the water table level of selected forested wetlands in the southeastern United States

NASA Astrophysics Data System (ADS)

Zhu, Jie; Sun, Ge; Li, Wenhong; Zhang, Yu; Miao, Guofang; Noormets, Asko; McNulty, Steve G.; King, John S.; Kumar, Mukesh; Wang, Xuan

2017-12-01

The southeastern United States hosts extensive forested wetlands, providing ecosystem services including carbon sequestration, water quality improvement, groundwater recharge, and wildlife habitat. However, these wetland ecosystems are dependent on local climate and hydrology, and are therefore at risk due to climate and land use change. This study develops site-specific empirical hydrologic models for five forested wetlands with different characteristics by analyzing long-term observed meteorological and hydrological data. These wetlands represent typical cypress ponds/swamps, Carolina bays, pine flatwoods, drained pocosins, and natural bottomland hardwood ecosystems. The validated empirical models are then applied at each wetland to predict future water table changes using climate projections from 20 general circulation models (GCMs) participating in Coupled Model Inter-comparison Project 5 (CMIP5) under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios. We show that combined future changes in precipitation and potential evapotranspiration would significantly alter wetland hydrology including groundwater dynamics by the end of the 21st century. Compared to the historical period, all five wetlands are predicted to become drier over time. The mean water table depth is predicted to drop by 4 to 22 cm in response to the decrease in water availability (i.e., precipitation minus potential evapotranspiration) by the year 2100. Among the five examined wetlands, the depressional wetland in hot and humid Florida appears to be most vulnerable to future climate change. This study provides quantitative information on the potential magnitude of wetland hydrological response to future climate change in typical forested wetlands in the southeastern US.

Diversity of deep-water cetaceans in relation to temperature: implications for ocean warming.

PubMed

Whitehead, Hal; McGill, Brian; Worm, Boris

2008-11-01

Understanding the effects of natural environmental variation on biodiversity can help predict response to future anthropogenic change. Here we analyse a large, long-term data set of sightings of deep-water cetaceans from the Atlantic, Pacific and Indian Oceans. Seasonal and geographic changes in the diversity of these genera are well predicted by a convex function of sea-surface temperature peaking at c. 21 degrees C. Thus, diversity is highest at intermediate latitudes - an emerging general pattern for the pelagic ocean. When applied to a range of Intergovernmental Panel on Climate Change global change scenarios, the predicted response is a decline of cetacean diversity across the tropics and increases at higher latitudes. This suggests that deep-water oceanic communities that dominate > 60% of the planet's surface may reorganize in response to ocean warming, with low-latitude losses of diversity and resilience.

A neuronal model of predictive coding accounting for the mismatch negativity.

PubMed

Wacongne, Catherine; Changeux, Jean-Pierre; Dehaene, Stanislas

2012-03-14

The mismatch negativity (MMN) is thought to index the activation of specialized neural networks for active prediction and deviance detection. However, a detailed neuronal model of the neurobiological mechanisms underlying the MMN is still lacking, and its computational foundations remain debated. We propose here a detailed neuronal model of auditory cortex, based on predictive coding, that accounts for the critical features of MMN. The model is entirely composed of spiking excitatory and inhibitory neurons interconnected in a layered cortical architecture with distinct input, predictive, and prediction error units. A spike-timing dependent learning rule, relying upon NMDA receptor synaptic transmission, allows the network to adjust its internal predictions and use a memory of the recent past inputs to anticipate on future stimuli based on transition statistics. We demonstrate that this simple architecture can account for the major empirical properties of the MMN. These include a frequency-dependent response to rare deviants, a response to unexpected repeats in alternating sequences (ABABAA…), a lack of consideration of the global sequence context, a response to sound omission, and a sensitivity of the MMN to NMDA receptor antagonists. Novel predictions are presented, and a new magnetoencephalography experiment in healthy human subjects is presented that validates our key hypothesis: the MMN results from active cortical prediction rather than passive synaptic habituation.

The role of topic, interviewee and question in predicting rich interview data in the field of health research.

PubMed

Ogden, Jane; Cornwell, Danielle

2010-11-01

Although texts recommend the generation of rich data from interviews, no empirical evidence base exists for achieving this. This study aimed to operationalise richness and to assess which components of the interview (for example, topic, interviewee, question) were predictive. A total of 400 interview questions and their corresponding responses were selected from 10 qualitative studies in the area of health identified from university colleagues and the UK Data Archive database. The analysis used the text analysis program, Linguistic Inquiry and Word Count, and additional rating scales. Richness was operationalised along five dimensions. 'Length of response' was predicted by a personal, less specific or positive topic, not being a layperson, later questions, open or double questions; 'personal richness' was predicted by being a healthy participant and questions about the past and future; 'analytical responses' were predicted by a personal or less specific topic, not being a layperson, later questions, questions relating to insight and causation; 'action responses' were predicted by a less specific topic, not being a layperson, being healthy, later and open questions. The model for 'descriptive richness' was not significant. Overall, open questions, located later on and framed in the present or past tense, tended to be most predictive of richness. This could inform improvements in interview technique. © 2010 The Authors. Sociology of Health & Illness © 2010 Foundation for the Sociology of Health & Illness/Blackwell Publishing Ltd.

Idiosyncratic species effects confound size-based predictions of responses to climate change.

PubMed

Twomey, Marion; Brodte, Eva; Jacob, Ute; Brose, Ulrich; Crowe, Tasman P; Emmerson, Mark C

2012-11-05

Understanding and predicting the consequences of warming for complex ecosystems and indeed individual species remains a major ecological challenge. Here, we investigated the effect of increased seawater temperatures on the metabolic and consumption rates of five distinct marine species. The experimental species reflected different trophic positions within a typical benthic East Atlantic food web, and included a herbivorous gastropod, a scavenging decapod, a predatory echinoderm, a decapod and a benthic-feeding fish. We examined the metabolism-body mass and consumption-body mass scaling for each species, and assessed changes in their consumption efficiencies. Our results indicate that body mass and temperature effects on metabolism were inconsistent across species and that some species were unable to meet metabolic demand at higher temperatures, thus highlighting the vulnerability of individual species to warming. While body size explains a large proportion of the variation in species' physiological responses to warming, it is clear that idiosyncratic species responses, irrespective of body size, complicate predictions of population and ecosystem level response to future scenarios of climate change.

Prediction of the cause, effects, and prevention of drug-nutrient interactions using attributes and attribute values.

PubMed

Roe, D A

1985-01-01

Drug-nutrient interactions and their adverse outcomes have previously been identified by observation, investigation, and literature reports. Knowing the attributes of the drugs, availability of knowledge base management systems for microcomputer use can facilitate prediction of the mechanism and the effects of drug-nutrient interactions. Examples used to illustrate this approach are prediction of lactose intolerance in drug-induced malabsorption, and prediction of the mechanism responsible for drug-induced flush reactions. In the future we see that there may be many opportunities to use this system further in the investigation of complex drug-nutrient interactions.

Comparing multiple statistical methods for inverse prediction in nuclear forensics applications

DOE PAGES

Lewis, John R.; Zhang, Adah; Anderson-Cook, Christine Michaela

2017-10-29

Forensic science seeks to predict source characteristics using measured observables. Statistically, this objective can be thought of as an inverse problem where interest is in the unknown source characteristics or factors ( X) of some underlying causal model producing the observables or responses (Y = g ( X) + error). Here, this paper reviews several statistical methods for use in inverse problems and demonstrates that comparing results from multiple methods can be used to assess predictive capability. Motivation for assessing inverse predictions comes from the desired application to historical and future experiments involving nuclear material production for forensics research inmore » which inverse predictions, along with an assessment of predictive capability, are desired.« less

Comparing multiple statistical methods for inverse prediction in nuclear forensics applications

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

Lewis, John R.; Zhang, Adah; Anderson-Cook, Christine Michaela

Forensic science seeks to predict source characteristics using measured observables. Statistically, this objective can be thought of as an inverse problem where interest is in the unknown source characteristics or factors ( X) of some underlying causal model producing the observables or responses (Y = g ( X) + error). Here, this paper reviews several statistical methods for use in inverse problems and demonstrates that comparing results from multiple methods can be used to assess predictive capability. Motivation for assessing inverse predictions comes from the desired application to historical and future experiments involving nuclear material production for forensics research inmore » which inverse predictions, along with an assessment of predictive capability, are desired.« less

Statistical modelling predicts almost complete loss of major periglacial processes in Northern Europe by 2100.

PubMed

Aalto, Juha; Harrison, Stephan; Luoto, Miska

2017-09-11

The periglacial realm is a major part of the cryosphere, covering a quarter of Earth's land surface. Cryogenic land surface processes (LSPs) control landscape development, ecosystem functioning and climate through biogeochemical feedbacks, but their response to contemporary climate change is unclear. Here, by statistically modelling the current and future distributions of four major LSPs unique to periglacial regions at fine scale, we show fundamental changes in the periglacial climate realm are inevitable with future climate change. Even with the most optimistic CO 2 emissions scenario (Representative Concentration Pathway (RCP) 2.6) we predict a 72% reduction in the current periglacial climate realm by 2050 in our climatically sensitive northern Europe study area. These impacts are projected to be especially severe in high-latitude continental interiors. We further predict that by the end of the twenty-first century active periglacial LSPs will exist only at high elevations. These results forecast a future tipping point in the operation of cold-region LSP, and predict fundamental landscape-level modifications in ground conditions and related atmospheric feedbacks.Cryogenic land surface processes characterise the periglacial realm and control landscape development and ecosystem functioning. Here, via statistical modelling, the authors predict a 72% reduction of the periglacial realm in Northern Europe by 2050, and almost complete disappearance by 2100.

Spatial analysis of plague in California: niche modeling predictions of the current distribution and potential response to climate change

PubMed Central

Holt, Ashley C; Salkeld, Daniel J; Fritz, Curtis L; Tucker, James R; Gong, Peng

2009-01-01

Background Plague, caused by the bacterium Yersinia pestis, is a public and wildlife health concern in California and the western United States. This study explores the spatial characteristics of positive plague samples in California and tests Maxent, a machine-learning method that can be used to develop niche-based models from presence-only data, for mapping the potential distribution of plague foci. Maxent models were constructed using geocoded seroprevalence data from surveillance of California ground squirrels (Spermophilus beecheyi) as case points and Worldclim bioclimatic data as predictor variables, and compared and validated using area under the receiver operating curve (AUC) statistics. Additionally, model results were compared to locations of positive and negative coyote (Canis latrans) samples, in order to determine the correlation between Maxent model predictions and areas of plague risk as determined via wild carnivore surveillance. Results Models of plague activity in California ground squirrels, based on recent climate conditions, accurately identified case locations (AUC of 0.913 to 0.948) and were significantly correlated with coyote samples. The final models were used to identify potential plague risk areas based on an ensemble of six future climate scenarios. These models suggest that by 2050, climate conditions may reduce plague risk in the southern parts of California and increase risk along the northern coast and Sierras. Conclusion Because different modeling approaches can yield substantially different results, care should be taken when interpreting future model predictions. Nonetheless, niche modeling can be a useful tool for exploring and mapping the potential response of plague activity to climate change. The final models in this study were used to identify potential plague risk areas based on an ensemble of six future climate scenarios, which can help public managers decide where to allocate surveillance resources. In addition, Maxent model results were significantly correlated with coyote samples, indicating that carnivore surveillance programs will continue to be important for tracking the response of plague to future climate conditions. PMID:19558717

Effects of drought on forest soil structure and hydrological soil functions

NASA Astrophysics Data System (ADS)

Gimbel, K.; Puhlmann, H.; Weiler, M.

2012-04-01

Climate change is predicted to severely affect precipitation patterns across central Europe. Soil structure is closely linked to the activity of soil microbiota and plant roots, which modify flow pathways along roots, organic matter and water repellence of soils. Through shrinkage and fracturing of soil aggregates, soil structure is also responding to changing climate (in particular drought) conditions. We investigate the possible effects on biogeochemical and hydropedological processes in response to predicted future reduced precipitation, and the interaction of these processes with the biodiversity of the forest understorey and soil biota. The hypotheses of this study are: (i) drought causes a change in soil structure, which affects hydrological soil functions (water infiltration, uptake and redistribution); (ii) changes in rooting patterns and microbial community composition, in response to drought, influence the hydrological soil functions. To test our hypotheses, we built adaptive roofing systems on nine sites in Germany, which allow a flexible reduction of precipitation in order to achieve the long-term minimum precipitation of a site. Here we present first measurements of our repeated measuring/sampling campaign, which will be conducted over a period of three years. The aim of our experiments is to analyze soil pore architecture and related flow and transport behaviour with dye tracer sprinkling experiments, soil column experiments with stable isotope (deuterium, oxygen-18) enriched water, computed tomography at soil monoliths (~70 l) and multi-step outflow experiments with 100 ml soil cores. Finally, we sketch our idea how to relate the observed temporal changes of soil structure and hydrological soil functions to the observed dynamics of hydrometeorological site conditions, soil moisture and desiccation as well as changes in rooting patterns, herb layer and soil microbiotic communities. The results of this study may help to assess future behavior of the plant-soil-water-microbiology-system and may help to adjust models to predict future response to different precipitation patterns as well as help coping with existing and future emerging challenges in forest management.

The dynamic range of response set activation during action sequencing.

PubMed

Behmer, Lawrence P; Crump, Matthew J C

2017-03-01

We show that theories of response scheduling for sequential action can be discriminated on the basis of their predictions for the dynamic range of response set activation during sequencing, which refers to the momentary span of activation states for completed and to-be-completed actions in a response set. In particular, theories allow that future actions in a plan are partially activated, but differ with respect to the width of the range, which refers to the number of future actions that are partially activated. Similarly, theories differ on the width of the range for recently completed actions that are assumed to be rapidly deactivated or gradually deactivated in a passive fashion. We validate a new typing task for measuring momentary activation states of actions across a response set during action sequencing. Typists recruited from Amazon Mechanical Turk copied a paragraph by responding to a "go" signal that usually cued the next letter but sometimes cued a near-past or future letter (n-3, -2, -1, 0, +2, +3). The activation states for producing letters across go-signal positions can be inferred from RTs and errors. In general, we found evidence of graded parallel activation for future actions and rapid deactivation of more distal past actions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Predicting response of fuel load to future changes in climate and atmospheric composition in the Southern United States.

Treesearch

Chi Zhang; Hanqin Tian; Yuhang Wang; Tao Zeng; Yongqiang Liu

2010-01-01

The model projected ecosystem carbon dynamics were incorporated into the default (contemporary) fuel load map developed by FCCS (Fuel Characteristic Classification System) to estimate the dynamics of fuel load in the Southern United States in response to projected changes in climate and atmosphere (CO2 and nitrogen deposition) from 2002 to 2050. The study results...

Anger responses to psychosocial stress predict heart rate and cortisol stress responses in men but not women.

PubMed

Lupis, Sarah B; Lerman, Michelle; Wolf, Jutta M

2014-11-01

While previous research has suggested that anger and fear responses to stress are linked to distinct sympathetic nervous system (SNS) stress responses, little is known about how these emotions predict hypothalamus-pituitary-adrenal (HPA) axis reactivity. Further, earlier research primarily relied on retrospective self-report of emotion. The current study aimed at addressing both issues in male and female individuals by assessing the role of anger and fear in predicting heart rate and cortisol stress responses using both self-report and facial coding analysis to assess emotion responses. We exposed 32 healthy students (18 female; 19.6±1.7 yr) to an acute psychosocial stress paradigm (TSST) and measured heart rate and salivary cortisol levels throughout the protocol. Anger and fear before and after stress exposure was assessed by self-report, and video recordings of the TSST were assessed by a certified facial coder to determine emotion expression (FACS). Self-reported emotions and emotion expressions did not correlate (all p>.23). Increases in self-reported fear predicted blunted cortisol responses in men (β=0.41, p=.04). Also for men, longer durations of anger expression predicted exaggerated cortisol responses (β=0.67 p=.004), and more anger incidences predicted exaggerated cortisol and heart rate responses (β=0.51, p=.033; β=0.46, p=.066, resp.). Anger and fear did not predict SNS or HPA activity for females (all p>.23). The current differential self-report and facial coding findings support the use of multiple modes of emotion assessment. Particularly, FACS but not self-report revealed a robust anger-stress association that could have important downstream health effects for men. For women, future research may clarify the role of other emotions, such as self-conscious expressions of shame, for physiological stress responses. A better understanding of the emotion-stress link may contribute to behavioral interventions targeting health-promoting ways of responding emotionally to stress. Copyright © 2014 Elsevier Ltd. All rights reserved.

Anger responses to psychosocial stress predict heart rate and cortisol stress responses in men but not women

PubMed Central

Lupis, Sarah B.; Lerman, Michelle; Wolf, Jutta M.

2014-01-01

While previous research has suggested that anger and fear responses to stress are linked to distinct sympathetic nervous system (SNS) stress responses, little is known about how these emotions predict hypothalamus-pituitary-adrenal (HPA) axis reactivity. Further, earlier research primarily relied on retrospective self-report of emotion. The current study aimed at addressing both issues in male and female individuals by assessing the role of anger and fear in predicting heart rate and cortisol stress responses using both self-report and facial coding analysis to assess emotion responses. We exposed 32 healthy students (18 female; 19.6+/−1.7 yrs.) to an acute psychosocial stress paradigm (TSST) and measured heart rate and salivary cortisol levels throughout the protocol. Anger and fear before and after stress exposure was assessed by self-report, and video recordings of the TSST were assessed by a certified facial coder to determine emotion expression (FACS). Self-reported emotions and emotion expressions did not correlate (all p > .23). Increases in self-reported fear predicted blunted cortisol responses in men (β = 0.41, p = .04). Also for men, longer durations of anger expression predicted exaggerated cortisol responses (β = 0.67 p = .004), and more anger incidences predicted exaggerated cortisol and heart rate responses (β = 0.51, p = .033; β = 0.46, p = .066, resp.). Anger and fear did not predict SNS or HPA activity for females (all p > .23). The current differential self-report and facial coding findings support the use of multiple modes of emotion assessment. Particularly, FACS but not self-report revealed a robust anger-stress association that could have important downstream health effects for men. For women, future research may clarify the role of other emotions, such as self-conscious expressions of shame, for physiological stress responses. A better understanding of the emotion-stress link may contribute to behavioral interventions targeting health-promoting ways of responding emotionally to stress. PMID:25064831

The history and future of nursing labor research in a cost-control environment.

PubMed

Brewer, C S

1998-04-01

For the first time in nursing's history, the downsizing of hospitals, the increased use of managed care, reduced use of registered nurses and other factors may result in significant unemployment in nursing, with resulting downward adjustments in the wage. Understanding the labor supply response of nurses to changes in the wage is critical to predicting accurately how nurses will respond to changes in the market demand as it influences wages, and determining rational policy responses to the labor market. In this article, three generations of nursing labor research are summarized and critiqued. Methodological issues are discussed and specific directions for future studies are suggested.

Homeostatic Regulation of Memory Systems and Adaptive Decisions

PubMed Central

Mizumori, Sheri JY; Jo, Yong Sang

2013-01-01

While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The “multiple memory systems of the brain” have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in rigid and suboptimal decision making and memory as seen in addiction and neurological disease. © 2013 The Authors. Hippocampus Published by Wiley Periodicals, Inc. PMID:23929788

Homeostatic regulation of memory systems and adaptive decisions.

PubMed

Mizumori, Sheri J Y; Jo, Yong Sang

2013-11-01

While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The "multiple memory systems of the brain" have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in rigid and suboptimal decision making and memory as seen in addiction and neurological disease. Copyright © 2013 Wiley Periodicals, Inc.

Macroweather Predictions and Climate Projections using Scaling and Historical Observations

NASA Astrophysics Data System (ADS)

Hébert, R.; Lovejoy, S.; Del Rio Amador, L.

2017-12-01

There are two fundamental time scales that are pertinent to decadal forecasts and multidecadal projections. The first is the lifetime of planetary scale structures, about 10 days (equal to the deterministic predictability limit), and the second is - in the anthropocene - the scale at which the forced anthropogenic variability exceeds the internal variability (around 16 - 18 years). These two time scales define three regimes of variability: weather, macroweather and climate that are respectively characterized by increasing, decreasing and then increasing varibility with scale.We discuss how macroweather temperature variability can be skilfully predicted to its theoretical stochastic predictability limits by exploiting its long-range memory with the Stochastic Seasonal and Interannual Prediction System (StocSIPS). At multi-decadal timescales, the temperature response to forcing is approximately linear and this can be exploited to make projections with a Green's function, or Climate Response Function (CRF). To make the problem tractable, we exploit the temporal scaling symmetry and restrict our attention to global mean forcing and temperature response using a scaling CRF characterized by the scaling exponent H and an inner scale of linearity τ. An aerosol linear scaling factor α and a non-linear volcanic damping exponent ν were introduced to account for the large uncertainty in these forcings. We estimate the model and forcing parameters by Bayesian inference using historical data and these allow us to analytically calculate a median (and likely 66% range) for the transient climate response, and for the equilibrium climate sensitivity: 1.6K ([1.5,1.8]K) and 2.4K ([1.9,3.4]K) respectively. Aerosol forcing typically has large uncertainty and we find a modern (2005) forcing very likely range (90%) of [-1.0, -0.3] Wm-2 with median at -0.7 Wm-2. Projecting to 2100, we find that to keep the warming below 1.5 K, future emissions must undergo cuts similar to Representative Concentration Pathway (RCP) 2.6 for which the probability to remain under 1.5 K is 48%. RCP 4.5 and RCP 8.5-like futures overshoot with very high probability. This underscores that over the next century, the state of the environment will be strongly influenced by past, present and future economical policies.

Bayesian Analysis for Inference of an Emerging Epidemic: Citrus Canker in Urban Landscapes

PubMed Central

Neri, Franco M.; Cook, Alex R.; Gibson, Gavin J.; Gottwald, Tim R.; Gilligan, Christopher A.

2014-01-01

Outbreaks of infectious diseases require a rapid response from policy makers. The choice of an adequate level of response relies upon available knowledge of the spatial and temporal parameters governing pathogen spread, affecting, amongst others, the predicted severity of the epidemic. Yet, when a new pathogen is introduced into an alien environment, such information is often lacking or of no use, and epidemiological parameters must be estimated from the first observations of the epidemic. This poses a challenge to epidemiologists: how quickly can the parameters of an emerging disease be estimated? How soon can the future progress of the epidemic be reliably predicted? We investigate these issues using a unique, spatially and temporally resolved dataset for the invasion of a plant disease, Asiatic citrus canker in urban Miami. We use epidemiological models, Bayesian Markov-chain Monte Carlo, and advanced spatial statistical methods to analyse rates and extent of spread of the disease. A rich and complex epidemic behaviour is revealed. The spatial scale of spread is approximately constant over time and can be estimated rapidly with great precision (although the evidence for long-range transmission is inconclusive). In contrast, the rate of infection is characterised by strong monthly fluctuations that we associate with extreme weather events. Uninformed predictions from the early stages of the epidemic, assuming complete ignorance of the future environmental drivers, fail because of the unpredictable variability of the infection rate. Conversely, predictions improve dramatically if we assume prior knowledge of either the main environmental trend, or the main environmental events. A contrast emerges between the high detail attained by modelling in the spatiotemporal description of the epidemic and the bottleneck imposed on epidemic prediction by the limits of meteorological predictability. We argue that identifying such bottlenecks will be a fundamental step in future modelling of weather-driven epidemics. PMID:24762851

Gender differences in coping responses and bulimic symptoms among undergraduate students.

PubMed

Kwan, Mun Yee; Gordon, Kathryn H; Eddy, Kamryn T; Thomas, Jennifer J; Franko, Debra L; Troop-Gordon, Wendy

2014-12-01

This prospective study examined the predictive role of three types of coping responses (i.e., voluntary disengagement, involuntary engagement, and involuntary disengagement) in response to social stress on bulimic symptoms among undergraduate women and men. A total of 883 (308 men; 35%) participants completed the Response to Stress Questionnaire, the Beck Depression Inventory, and the Eating Disorder Inventory (EDI) at baseline assessment and the EDI at follow-up assessment 8-12 weeks later. After controlling for baseline bulimic symptoms, depression, and body dissatisfaction, involuntary disengagement predicted bulimic symptoms at follow-up among men (b=.21, p<.001), but not among women (b=.06, p>.05). Results indicated that men who responded to social stress through involuntary disengagement (e.g., emotional numbing, inaction) had higher risk for increased bulimic symptoms. Future studies are needed to replicate these findings and to further understand the role of these coping responses on bulimic symptoms. Published by Elsevier Ltd.

Predictive models of forest dynamics.

PubMed

Purves, Drew; Pacala, Stephen

2008-06-13

Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.

Using changes in agricultural utility to quantify future climate-induced risk to conservation.

PubMed

Estes, Lyndon D; Paroz, Lydie-Line; Bradley, Bethany A; Green, Jonathan M H; Hole, David G; Holness, Stephen; Ziv, Guy; Oppenheimer, Michael G; Wilcove, David S

2014-04-01

Much of the biodiversity-related climate change impacts research has focused on the direct effects to species and ecosystems. Far less attention has been paid to the potential ecological consequences of human efforts to address the effects of climate change, which may equal or exceed the direct effects of climate change on biodiversity. One of the most significant human responses is likely to be mediated through changes in the agricultural utility of land. As farmers adapt their practices to changing climates, they may increase pressure on some areas that are important to conserve (conservation lands) whereas lessening it on others. We quantified how the agricultural utility of South African conservation lands may be altered by climate change. We assumed that the probability of an area being farmed is linked to the economic benefits of doing so, using land productivity values to represent production benefit and topographic ruggedness as a proxy for costs associated with mechanical workability. We computed current and future values of maize and wheat production in key conservation lands using the DSSAT4.5 model and 36 crop-climate response scenarios. Most conservation lands had, and were predicted to continue to have, low agricultural utility because of their location in rugged terrain. However, several areas were predicted to maintain or gain high agricultural utility and may therefore be at risk of near-term or future conversion to cropland. Conversely, some areas were predicted to decrease in agricultural utility and may therefore prove easier to protect from conversion. Our study provides an approximate but readily transferable method for incorporating potential human responses to climate change into conservation planning. © 2013 Society for Conservation Biology.

Modeling Rabbit Responses to Single and Multiple Aerosol ...

EPA Pesticide Factsheets

Journal Article Survival models are developed here to predict response and time-to-response for mortality in rabbits following exposures to single or multiple aerosol doses of Bacillus anthracis spores. Hazard function models were developed for a multiple dose dataset to predict the probability of death through specifying dose-response functions and the time between exposure and the time-to-death (TTD). Among the models developed, the best-fitting survival model (baseline model) has an exponential dose-response model with a Weibull TTD distribution. Alternative models assessed employ different underlying dose-response functions and use the assumption that, in a multiple dose scenario, earlier doses affect the hazard functions of each subsequent dose. In addition, published mechanistic models are analyzed and compared with models developed in this paper. None of the alternative models that were assessed provided a statistically significant improvement in fit over the baseline model. The general approach utilizes simple empirical data analysis to develop parsimonious models with limited reliance on mechanistic assumptions. The baseline model predicts TTDs consistent with reported results from three independent high-dose rabbit datasets. More accurate survival models depend upon future development of dose-response datasets specifically designed to assess potential multiple dose effects on response and time-to-response. The process used in this paper to dev

Predicting the distributions of predator (snow leopard) and prey (blue sheep) under climate change in the Himalaya.

PubMed

Aryal, Achyut; Shrestha, Uttam Babu; Ji, Weihong; Ale, Som B; Shrestha, Sujata; Ingty, Tenzing; Maraseni, Tek; Cockfield, Geoff; Raubenheimer, David

2016-06-01

Future climate change is likely to affect distributions of species, disrupt biotic interactions, and cause spatial incongruity of predator-prey habitats. Understanding the impacts of future climate change on species distribution will help in the formulation of conservation policies to reduce the risks of future biodiversity losses. Using a species distribution modeling approach by MaxEnt, we modeled current and future distributions of snow leopard (Panthera uncia) and its common prey, blue sheep (Pseudois nayaur), and observed the changes in niche overlap in the Nepal Himalaya. Annual mean temperature is the major climatic factor responsible for the snow leopard and blue sheep distributions in the energy-deficient environments of high altitudes. Currently, about 15.32% and 15.93% area of the Nepal Himalaya are suitable for snow leopard and blue sheep habitats, respectively. The bioclimatic models show that the current suitable habitats of both snow leopard and blue sheep will be reduced under future climate change. The predicted suitable habitat of the snow leopard is decreased when blue sheep habitats is incorporated in the model. Our climate-only model shows that only 11.64% (17,190 km(2)) area of Nepal is suitable for the snow leopard under current climate and the suitable habitat reduces to 5,435 km(2) (reduced by 24.02%) after incorporating the predicted distribution of blue sheep. The predicted distribution of snow leopard reduces by 14.57% in 2030 and by 21.57% in 2050 when the predicted distribution of blue sheep is included as compared to 1.98% reduction in 2030 and 3.80% reduction in 2050 based on the climate-only model. It is predicted that future climate may alter the predator-prey spatial interaction inducing a lower degree of overlap and a higher degree of mismatch between snow leopard and blue sheep niches. This suggests increased energetic costs of finding preferred prey for snow leopards - a species already facing energetic constraints due to the limited dietary resources in its alpine habitat. Our findings provide valuable information for extension of protected areas in future.

Cortical Responses to Chinese Phonemes in Preschoolers Predict Their Literacy Skills at School Age.

PubMed

Hong, Tian; Shuai, Lan; Frost, Stephen J; Landi, Nicole; Pugh, Kenneth R; Shu, Hua

2018-01-01

We investigated whether preschoolers with poor phonological awareness (PA) skills had impaired cortical basis for detecting speech feature, and whether speech perception influences future literacy outcomes in preschoolers. We recorded ERP responses to speech in 52 Chinese preschoolers. The results showed that the poor PA group processed speech changes differentially compared to control group in mismatch negativity (MMN) and late discriminative negativity (LDN). Furthermore, speech perception in kindergarten could predict literacy outcomes after literacy acquisition. These suggest that impairment in detecting speech features occurs before formal reading instruction, and that speech perception plays an important role in reading development.

On the internal target model in a tracking task

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Baron, S.

1981-01-01

An optimal control model for predicting operator's dynamic responses and errors in target tracking ability is summarized. The model, which predicts asymmetry in the tracking data, is dependent on target maneuvers and trajectories. Gunners perception, decision making, control, and estimate of target positions and velocity related to crossover intervals are discussed. The model provides estimates for means, standard deviations, and variances for variables investigated and for operator estimates of future target positions and velocities.

Assessing impacts of climate change on species range shifts and extirpation on the local scale through Late Pleistocene fossils of Sequoia sempervirens in the Los Angeles Basin.

NASA Astrophysics Data System (ADS)

George, J.; MacDonald, G. M.

2017-12-01

As the effects of climate change become more apparent, increased importance must be placed on species' response to changing environments for ecosystem management and threat mitigation. While many studies have focused on the response of ecosystem types, few venture to the species level, as true limiting factors of species can be difficult to discern. Paleoproxies provide a valuable resource for predicting responses to future change through observation of similar responses in the past. This study uses plant paleorecords of Sequoia sempervirens to more closely examine the relationship of local climate change and species response in the Los Angeles Basin during the Late Pleistocene. The modern distribution of S. sempervirens has a southern extent, today, reaching the south end of Monterey County, California. Fossilized material from the La Brea Tar Pits extends that range to the farthest known point south, 200 miles from the southernmost modern stands, and has previously not been dated. A coupled analysis of 8 S. sempervirens specimens preserved in asphalt using Accelerator Mass Spectrometry (AMS) dates paired with δC13 values will help to illuminate patterns of changing climate on a local scale, as well as provide valuable data on primary environmental factors in plant community change. Understanding the intricacies of species' range shifts and factors behind local extirpation on a local scale is necessary to interpret species response in the past as well as predicting response in the future.

Consumer factors predicting level of treatment response to illness management and recovery.

PubMed

White, Dominique A; McGuire, Alan B; Luther, Lauren; Anderson, Adrienne I; Phalen, Peter; McGrew, John H

2017-12-01

This study aims to identify consumer-level predictors of level of treatment response to illness management and recovery (IMR) to target the appropriate consumers and aid psychiatric rehabilitation settings in developing intervention adaptations. Secondary analyses from a multisite study of IMR were conducted. Self-report data from consumer participants of the parent study (n = 236) were analyzed for the current study. Consumers completed prepost surveys assessing illness management, coping, goal-related hope, social support, medication adherence, and working alliance. Correlations and multiple regression analyses were run to identify self-report variables that predicted level of treatment response to IMR. Analyses revealed that goal-related hope significantly predicted level of improved illness self-management, F(1, 164) = 10.93, p < .001, R2 = .248, R2 change = .05. Additionally, we found that higher levels of maladaptive coping at baseline were predictive of higher levels of adaptive coping at follow-up, F(2, 180) = 5.29, p < .02, R2 = .38, R2 change = .02. Evidence did not support additional predictors. Previously, consumer-level predictors of level of treatment response have not been explored for IMR. Although 2 significant predictors were identified, study findings suggest more work is needed. Future research is needed to identify additional consumer-level factors predictive of IMR treatment response in order to identify who would benefit most from this treatment program. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Spatial segregation of adaptation and predictive sensitization in retinal ganglion cells

PubMed Central

Kastner, David B.; Baccus, Stephen A.

2014-01-01

Sensory systems change their sensitivity based upon recent stimuli to adjust their response range to the range of inputs, and to predict future sensory input. Here we report the presence of retinal ganglion cells that have antagonistic plasticity, showing central adaptation and peripheral sensitization. Ganglion cell responses were captured by a spatiotemporal model with independently adapting excitatory and inhibitory subunits, and sensitization requires GABAergic inhibition. Using a simple theory of signal detection we show that the sensitizing surround conforms to an optimal inference model that continually updates the prior signal probability. This indicates that small receptive field regions have dual functionality—to adapt to the local range of signals, but sensitize based upon the probability of the presence of that signal. Within this framework, we show that sensitization predicts the location of a nearby object, revealing prediction as a new functional role for adapting inhibition in the nervous system. PMID:23932000

Scenario planning.

PubMed

Enzmann, Dieter R; Beauchamp, Norman J; Norbash, Alexander

2011-03-01

In facing future developments in health care, scenario planning offers a complementary approach to traditional strategic planning. Whereas traditional strategic planning typically consists of predicting the future at a single point on a chosen time horizon and mapping the preferred plans to address such a future, scenario planning creates stories about multiple likely potential futures on a given time horizon and maps the preferred plans to address the multiple described potential futures. Each scenario is purposefully different and specifically not a consensus worst-case, average, or best-case forecast; nor is scenario planning a process in probabilistic prediction. Scenario planning focuses on high-impact, uncertain driving forces that in the authors' example affect the field of radiology. Uncertainty is the key concept as these forces are mapped onto axes of uncertainty, the poles of which have opposed effects on radiology. One chosen axis was "market focus," with poles of centralized health care (government control) vs a decentralized private market. Another axis was "radiology's business model," with one pole being a unified, single specialty vs a splintered, disaggregated subspecialty. The third axis was "technology and science," with one pole representing technology enabling to radiology vs technology threatening to radiology. Selected poles of these axes were then combined to create 3 scenarios. One scenario, termed "entrepreneurialism," consisted of a decentralized private market, a disaggregated business model, and threatening technology and science. A second scenario, termed "socialized medicine," had a centralized market focus, a unified specialty business model, and enabling technology and science. A third scenario, termed "freefall," had a centralized market focus, a disaggregated business model, and threatening technology and science. These scenarios provide a range of futures that ultimately allow the identification of defined "signposts" that can suggest which basic features among the "possible futures" are playing out. Scenario planning provides for the implementation of appropriate constructed strategic responses. Scenarios allow for a pre-prepared game plan available for ready use as the future unfolds. They allow a deliberative response rather than a hastily constructed, urgent response. Copyright © 2011 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Predictor symbology in computer-generated pictorial displays

NASA Technical Reports Server (NTRS)

Grunwald, A. J.

1981-01-01

The display under investigation, is a tunnel display for the four-dimensional commercial aircraft approach-to-landing under instrument flight rules. It is investigated whether more complex predictive information such as a three-dimensional perspective vehicle symbol, predicting the future vehicle position as well as future vehicle attitude angles, contributes to a better system response, and suitable predictor laws for the predictor motions, are formulated. Methods for utilizing the predictor symbol in controlling the forward velocity of the aircraft in four-dimensional approaches, are investigated. The simulator tests show, that the complex perspective vehicle symbol yields improved damping in the lateral response as compared to a flat two-dimensional predictor cross, but yields generally larger vertical deviations. Methods of using the predictor symbol in controlling the forward velocity of the vehicle are shown to be effective. The tunnel display with superimposed perspective vehicle symbol yields very satisfactory results and pilot acceptance in the lateral control but is found to be unsatisfactory in the vertical control, as a result of too large vertical path-angle deviations.

Prediction and control of coupled-mode flutter in future wind turbine blades

NASA Astrophysics Data System (ADS)

Modarres-Sadeghi, Yahya; Currier, Todd; Caracoglia, Luca; Lackner, Matthew; Hollot, Christopher

2017-11-01

Coupled-mode flutter can be observed in future offshore wind turbine blades. We have shown this fact by considering various candidate blade designs, in all of which the blade's first torsional mode couples with one of its flapwise modes, resulting in coupled-mode flutter. We have shown how the ratio of these two natural frequencies can result in blades with a critical flutter speed even lower than their rated speed, especially for blades with low torsional natural frequencies. We have also shown how the stochastic nature of the system parameters (as an example, due to uncertainties in the manufacturing process) can significantly influence the onset of instability. We have proposed techniques to predict the onset of these instabilities and the resulting limit-cycle response, and strategies to control them, by either postponing the onset of instability, or lowering the magnitude of the limit-cycle response. The work is supported by the National Science Foundation, Award CBET-1437988 and Collaborative Awards CMMI-1462646 and CMMI-1462774.

Personality traits predict treatment outcome with an antidepressant in patients with functional gastrointestinal disorder.

PubMed

Tanum, L; Malt, U F

2000-09-01

We investigated the relationship between personality traits and response to treatment with the tetracyclic antidepressant mianserin or placebo in patients with functional gastrointestinal disorder (FGD) without psychopathology. Forty-eight patients completed the Buss-Durkee Hostility Inventory, Neuroticism Extroversion Openness -Personality Inventory (NEO-PI), and Eysenck Personality Questionnaire (EPQ), neuroticism + lie subscales, before they were consecutively allocated to a 7-week double-blind treatment study with mianserin or placebo. Treatment response to pain and target symptoms were recorded daily with the Visual Analogue Scale and Clinical Global Improvement Scale at every visit. A low level of neuroticism and little concealed aggressiveness predicted treatment outcome with the antidepressant drug mianserin in non-psychiatric patients with FGD. Inversely, moderate to high neuroticism and marked concealed aggressiveness predicted poor response to treatment. These findings were most prominent in women. Personality traits were better predictors of treatment outcome than serotonergic sensitivity assessed with the fenfluramine test. Assessment of the personality traits negativism, irritability, aggression, and neuroticism may predict response to drug treatment of FGD even when serotonergic sensitivity is controlled for. If confirmed in future studies, the findings point towards a more differential psychopharmacologic treatment of FGD.

Forecasting Responses of a Northern Peatland Carbon Cycle to Elevated CO2 and a Gradient of Experimental Warming

NASA Astrophysics Data System (ADS)

Jiang, Jiang; Huang, Yuanyuan; Ma, Shuang; Stacy, Mark; Shi, Zheng; Ricciuto, Daniel M.; Hanson, Paul J.; Luo, Yiqi

2018-03-01

The ability to forecast ecological carbon cycling is imperative to land management in a world where past carbon fluxes are no longer a clear guide in the Anthropocene. However, carbon-flux forecasting has not been practiced routinely like numerical weather prediction. This study explored (1) the relative contributions of model forcing data and parameters to uncertainty in forecasting flux- versus pool-based carbon cycle variables and (2) the time points when temperature and CO2 treatments may cause statistically detectable differences in those variables. We developed an online forecasting workflow (Ecological Platform for Assimilation of Data (EcoPAD)), which facilitates iterative data-model integration. EcoPAD automates data transfer from sensor networks, data assimilation, and ecological forecasting. We used the Spruce and Peatland Responses Under Changing Experiments data collected from 2011 to 2014 to constrain the parameters in the Terrestrial Ecosystem Model, forecast carbon cycle responses to elevated CO2 and a gradient of warming from 2015 to 2024, and specify uncertainties in the model output. Our results showed that data assimilation substantially reduces forecasting uncertainties. Interestingly, we found that the stochasticity of future external forcing contributed more to the uncertainty of forecasting future dynamics of C flux-related variables than model parameters. However, the parameter uncertainty primarily contributes to the uncertainty in forecasting C pool-related response variables. Given the uncertainties in forecasting carbon fluxes and pools, our analysis showed that statistically different responses of fast-turnover pools to various CO2 and warming treatments were observed sooner than slow-turnover pools. Our study has identified the sources of uncertainties in model prediction and thus leads to improve ecological carbon cycling forecasts in the future.

Establishing Esri ArcGIS Enterprise Platform Capabilities to Support Response Activities of the NASA Earth Science Disasters Program

NASA Astrophysics Data System (ADS)

Molthan, A.; Seepersad, J.; Shute, J.; Carriere, L.; Duffy, D.; Tisdale, B.; Kirschbaum, D.; Green, D. S.; Schwizer, L.

2017-12-01

NASA's Earth Science Disasters Program promotes the use of Earth observations to improve the prediction of, preparation for, response to, and recovery from natural and technological disasters. NASA Earth observations and those of domestic and international partners are combined with in situ observations and models by NASA scientists and partners to develop products supporting disaster mitigation, response, and recovery activities among several end-user partners. These products are accompanied by training to ensure proper integration and use of these materials in their organizations. Many products are integrated along with other observations available from other sources in GIS-capable formats to improve situational awareness and response efforts before, during and after a disaster. Large volumes of NASA observations support the generation of disaster response products by NASA field center scientists, partners in academia, and other institutions. For example, a prediction of high streamflows and inundation from a NASA-supported model may provide spatial detail of flood extent that can be combined with GIS information on population density, infrastructure, and land value to facilitate a prediction of who will be affected, and the economic impact. To facilitate the sharing of these outputs in a common framework that can be easily ingested by downstream partners, the NASA Earth Science Disasters Program partnered with Esri and the NASA Center for Climate Simulation (NCCS) to establish a suite of Esri/ArcGIS services to support the dissemination of routine and event-specific products to end users. This capability has been demonstrated to key partners including the Federal Emergency Management Agency using a case-study example of Hurricane Matthew, and will also help to support future domestic and international disaster events. The Earth Science Disasters Program has also established a longer-term vision to leverage scientists' expertise in the development and delivery of end-user training, increase public awareness of NASA's Disasters Program, and facilitate new partnerships with disaster response organizations. Future research and development will foster generation of products that leverage NASA's Earth observations for disaster prediction, preparation and mitigation, response, and recovery.

Body composition impacts appetite regulation in middle childhood. A prospective study of Norwegian community children.

PubMed

Steinsbekk, Silje; Llewellyn, Clare H; Fildes, Alison; Wichstrøm, Lars

2017-05-30

Research suggests a role for both fat mass and muscle mass in appetite regulation, but the longitudinal relationships between them have not yet been examined in children. The present study therefore aimed to explore the prospective relationships between fat mass, muscle mass and the appetitive traits food responsiveness and satiety responsiveness in middle childhood. Food responsiveness and satiety responsiveness were measured using the parent-reported Children's Eating Behavior Questionnaire in a representative sample of Norwegian 6 year olds, followed up at 8 and 10 years of age (n = 807). Body composition was measured by bioelectrical impedance. Applying a structural equation modeling framework we found that higher fat mass predicted greater increases in food responsiveness over time, whereas greater muscle mass predicted decreases in satiety responsiveness. This pattern was consistent both from ages 6 to 8 and from ages 8 to 10 years. Our study is the first to reveal that fat mass and muscle mass predict distinct changes in different appetitive traits over time. Replication of findings in non-European populations are needed, as are studies of children in other age groups. Future studies should also aim to reveal the underlying mechanisms.

Military’s Peacetime Role (Implications of the Civilian Conservation Corps Experience)

DTIC Science & Technology

1986-06-06

containing data and opinion pertinent to various study orientetions . Throughout the literature there are numaeroum but scattered references to the impact of...was indirect and evidenced only by extrapolation. President Roosevelt had predicted that CCC work would be "a means of creating future national wealth...foreseeable future . 2 5 There was virtually no chance of a situation that would require a military response. Furthermore, if the General Staff had 122 thought

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis.

PubMed

Sieberts, Solveig K; Zhu, Fan; García-García, Javier; Stahl, Eli; Pratap, Abhishek; Pandey, Gaurav; Pappas, Dimitrios; Aguilar, Daniel; Anton, Bernat; Bonet, Jaume; Eksi, Ridvan; Fornés, Oriol; Guney, Emre; Li, Hongdong; Marín, Manuel Alejandro; Panwar, Bharat; Planas-Iglesias, Joan; Poglayen, Daniel; Cui, Jing; Falcao, Andre O; Suver, Christine; Hoff, Bruce; Balagurusamy, Venkat S K; Dillenberger, Donna; Neto, Elias Chaibub; Norman, Thea; Aittokallio, Tero; Ammad-Ud-Din, Muhammad; Azencott, Chloe-Agathe; Bellón, Víctor; Boeva, Valentina; Bunte, Kerstin; Chheda, Himanshu; Cheng, Lu; Corander, Jukka; Dumontier, Michel; Goldenberg, Anna; Gopalacharyulu, Peddinti; Hajiloo, Mohsen; Hidru, Daniel; Jaiswal, Alok; Kaski, Samuel; Khalfaoui, Beyrem; Khan, Suleiman Ali; Kramer, Eric R; Marttinen, Pekka; Mezlini, Aziz M; Molparia, Bhuvan; Pirinen, Matti; Saarela, Janna; Samwald, Matthias; Stoven, Véronique; Tang, Hao; Tang, Jing; Torkamani, Ali; Vert, Jean-Phillipe; Wang, Bo; Wang, Tao; Wennerberg, Krister; Wineinger, Nathan E; Xiao, Guanghua; Xie, Yang; Yeung, Rae; Zhan, Xiaowei; Zhao, Cheng; Greenberg, Jeff; Kremer, Joel; Michaud, Kaleb; Barton, Anne; Coenen, Marieke; Mariette, Xavier; Miceli, Corinne; Shadick, Nancy; Weinblatt, Michael; de Vries, Niek; Tak, Paul P; Gerlag, Danielle; Huizinga, Tom W J; Kurreeman, Fina; Allaart, Cornelia F; Louis Bridges, S; Criswell, Lindsey; Moreland, Larry; Klareskog, Lars; Saevarsdottir, Saedis; Padyukov, Leonid; Gregersen, Peter K; Friend, Stephen; Plenge, Robert; Stolovitzky, Gustavo; Oliva, Baldo; Guan, Yuanfang; Mangravite, Lara M; Bridges, S Louis; Criswell, Lindsey; Moreland, Larry; Klareskog, Lars; Saevarsdottir, Saedis; Padyukov, Leonid; Gregersen, Peter K; Friend, Stephen; Plenge, Robert; Stolovitzky, Gustavo; Oliva, Baldo; Guan, Yuanfang; Mangravite, Lara M

2016-08-23

Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2)=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.

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.

Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model.

PubMed

Fernandes, Jose A; Cheung, William W L; Jennings, Simon; Butenschön, Momme; de Mora, Lee; Frölicher, Thomas L; Barange, Manuel; Grant, Alastair

2013-08-01

Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species-based Dynamic Bioclimate Envelope Model (DBEM) with a size-based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness-of-fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter-specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment. © 2013 John Wiley & Sons Ltd.

Effects of near-future ocean acidification, fishing, and marine protection on a temperate coastal ecosystem.

PubMed

Cornwall, Christopher E; Eddy, Tyler D

2015-02-01

Understanding ecosystem responses to global and local anthropogenic impacts is paramount to predicting future ecosystem states. We used an ecosystem modeling approach to investigate the independent and cumulative effects of fishing, marine protection, and ocean acidification on a coastal ecosystem. To quantify the effects of ocean acidification at the ecosystem level, we used information from the peer-reviewed literature on the effects of ocean acidification. Using an Ecopath with Ecosim ecosystem model for the Wellington south coast, including the Taputeranga Marine Reserve (MR), New Zealand, we predicted ecosystem responses under 4 scenarios: ocean acidification + fishing; ocean acidification + MR (no fishing); no ocean acidification + fishing; no ocean acidification + MR for the year 2050. Fishing had a larger effect on trophic group biomasses and trophic structure than ocean acidification, whereas the effects of ocean acidification were only large in the absence of fishing. Mortality by fishing had large, negative effects on trophic group biomasses. These effects were similar regardless of the presence of ocean acidification. Ocean acidification was predicted to indirectly benefit certain species in the MR scenario. This was because lobster (Jasus edwardsii) only recovered to 58% of the MR biomass in the ocean acidification + MR scenario, a situation that benefited the trophic groups lobsters prey on. Most trophic groups responded antagonistically to the interactive effects of ocean acidification and marine protection (46%; reduced response); however, many groups responded synergistically (33%; amplified response). Conservation and fisheries management strategies need to account for the reduced recovery potential of some exploited species under ocean acidification, nonadditive interactions of multiple factors, and indirect responses of species to ocean acidification caused by declines in calcareous predators. © 2014 Society for Conservation Biology.

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.

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

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

USGS Publications Warehouse

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

2015-01-01

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

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.

Striatal Activation Predicts Differential Therapeutic Responses to Methylphenidate and Atomoxetine.

PubMed

Schulz, Kurt P; Bédard, Anne-Claude V; Fan, Jin; Hildebrandt, Thomas B; Stein, Mark A; Ivanov, Iliyan; Halperin, Jeffrey M; Newcorn, Jeffrey H

2017-07-01

Methylphenidate has prominent effects in the dopamine-rich striatum that are absent for the selective norepinephrine transporter inhibitor atomoxetine. This study tested whether baseline striatal activation would predict differential response to the two medications in youth with attention-deficit/hyperactivity disorder (ADHD). A total of 36 youth with ADHD performed a Go/No-Go test during functional magnetic resonance imaging at baseline and were treated with methylphenidate and atomoxetine using a randomized cross-over design. Whole-brain task-related activation was regressed on clinical response. Task-related activation in right caudate nucleus was predicted by an interaction of clinical responses to methylphenidate and atomoxetine (F 1,30  = 17.00; p < .001). Elevated caudate activation was associated with robust improvement for methylphenidate and little improvement for atomoxetine. The rate of robust response was higher for methylphenidate than for atomoxetine in youth with high (94.4% vs. 38.8%; p = .003; number needed to treat = 2, 95% CI = 1.31-3.73) but not low (33.3% vs. 50.0%; p = .375) caudate activation. Furthermore, response to atomoxetine predicted motor cortex activation (F 1,30  = 14.99; p < .001). Enhanced caudate activation for response inhibition may be a candidate biomarker of superior response to methylphenidate over atomoxetine in youth with ADHD, purportedly reflecting the dopaminergic effects of methylphenidate but not atomoxetine in the striatum, whereas motor cortex activation may predict response to atomoxetine. These data do not yet translate directly to the clinical setting, but the approach is potentially important for informing future research and illustrates that it may be possible to predict differential treatment response using a biomarker-driven approach. Stimulant Versus Nonstimulant Medication for Attention Deficit Hyperactivity Disorder in Children; https://clinicaltrials.gov/; NCT00183391. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Antecedent conditions influence soil respiration differences in shrub and grass patches

USDA-ARS?s Scientific Manuscript database

Quantifying the response of soil respiration to past environmental conditions is critical for predicting how future climate and vegetation change will impact ecosystem carbon balance. Increased shrub dominance in semiarid grasslands has potentially large effects on soil carbon cycling. The goal of t...

Workforce 2000. A Bibliography.

ERIC Educational Resources Information Center

Florida State Univ., Tallahassee. Center for Instructional Development and Services.

This bibliography contains citations locating information about the future U.S. work force. Because of demographic, economic, and technological developments, significant changes are predicted in both the nature of work and the composition of the work force by the year 2000. Projections, viewpoints, and suggested responses to these changes from…

Exploring Resource Sharing between Secondary School Teachers of Agriculture and Science Departments Nationally.

ERIC Educational Resources Information Center

Dormody, Thomas J.

1992-01-01

A survey of 372 secondary agriculture teachers received 274 responses showing a majority of agriculture and science departments share resources, although at low levels. Many more predicted future sharing. Equipment and supplies were most often shared, instructional services least often. (SK)

Modeling behavioral thermoregulation in a climate change sentinel.

PubMed

Moyer-Horner, Lucas; Mathewson, Paul D; Jones, Gavin M; Kearney, Michael R; Porter, Warren P

2015-12-01

When possible, many species will shift in elevation or latitude in response to rising temperatures. However, before such shifts occur, individuals will first tolerate environmental change and then modify their behavior to maintain heat balance. Behavioral thermoregulation allows animals a range of climatic tolerances and makes predicting geographic responses under future warming scenarios challenging. Because behavioral modification may reduce an individual's fecundity by, for example, limiting foraging time and thus caloric intake, we must consider the range of behavioral options available for thermoregulation to accurately predict climate change impacts on individual species. To date, few studies have identified mechanistic links between an organism's daily activities and the need to thermoregulate. We used a biophysical model, Niche Mapper, to mechanistically model microclimate conditions and thermoregulatory behavior for a temperature-sensitive mammal, the American pika (Ochotona princeps). Niche Mapper accurately simulated microclimate conditions, as well as empirical metabolic chamber data for a range of fur properties, animal sizes, and environmental parameters. Niche Mapper predicted pikas would be behaviorally constrained because of the need to thermoregulate during the hottest times of the day. We also showed that pikas at low elevations could receive energetic benefits by being smaller in size and maintaining summer pelage during longer stretches of the active season under a future warming scenario. We observed pika behavior for 288 h in Glacier National Park, Montana, and thermally characterized their rocky, montane environment. We found that pikas were most active when temperatures were cooler, and at sites characterized by high elevations and north-facing slopes. Pikas became significantly less active across a suite of behaviors in the field when temperatures surpassed 20°C, which supported a metabolic threshold predicted by Niche Mapper. In general, mechanistic predictions and empirical observations were congruent. This research is unique in providing both an empirical and mechanistic description of the effects of temperature on a mammalian sentinel of climate change, the American pika. Our results suggest that previously underinvestigated characteristics, specifically fur properties and body size, may play critical roles in pika populations' response to climate change. We also demonstrate the potential importance of considering behavioral thermoregulation and microclimate variability when predicting animal responses to climate change.

Anticipating the future: Automatic prediction failures in schizophrenia

PubMed Central

Ford, Judith M.; Mathalon, Daniel H.

2011-01-01

People with schizophrenia often misperceive sensations and misinterpret experiences, perhaps contributing to psychotic symptoms. These misperceptions and misinterpretations might result from an inability to make valid predictions about expected sensations and experiences. Healthy normal people take advantage of neural mechanisms that allow them to make predictions unconsciously, facilitating processing of expected sensations and distinguishing the expected from the unexpected. In this paper, we focus on two types of automatic, unconscious mechanisms that allow us to predict our perceptions. The first involves predictions made via innate mechanisms basic to all species in the animal kingdom—the efference copy and corollary discharge mechanisms. They accompany our voluntary movements and allow us to suppress sensations resulting from our actions. We study this during talking, and show that auditory cortical response to the speech sounds during talking is reduced compared to when they are played back. This suppression is reduced in schizophrenia, suggesting a failure to predict the sensations resulting from talking. The second mechanism involves implicitly learning what to expect from the current context of events. We study this by observing the brain's response to an unexpected repetition of an event, when a change would have been predicted. That patients have a reduced response suggests they failed to predict that it was time for a change. Both types of predictions should happen automatically and effortlessly, allowing for economic processing of expected events and orientation to unexpected ones. These prediction failures characterize the diagnosis of schizophrenia rather than reflecting specific symptoms. PMID:21959054

Emergence, reductionism and landscape response to climate change

NASA Astrophysics Data System (ADS)

Harrison, Stephan; Mighall, Tim

2010-05-01

Predicting landscape response to external forcing is hampered by the non-linear, stochastic and contingent (ie dominated by historical accidents) forcings inherent in landscape evolution. Using examples from research carried out in southwest Ireland we suggest that non-linearity in landform evolution is likely to be a strong control making regional predictions of landscape response to climate change very difficult. While uncertainties in GCM projections have been widely explored in climate science much less attention has been directed by geomorphologists to the uncertainties in landform evolution under conditions of climate change and this problem may be viewed within the context of philosophical approaches to reductionsim and emergence. Understanding the present and future trajectory of landform change may also guide us to provide an enhanced appreciation of how landforms evolved in the past.

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

PubMed

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

2017-04-01

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

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

USGS Publications Warehouse

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-01-01

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

The Recalibrated Sunspot Number: Impact on Solar Cycle Predictions

NASA Astrophysics Data System (ADS)

Clette, F.; Lefevre, L.

2017-12-01

Recently and for the first time since their creation, the sunspot number and group number series were entirely revisited and a first fully recalibrated version was officially released in July 2015 by the World Data Center SILSO (Brussels). Those reference long-term series are widely used as input data or as a calibration reference by various solar cycle prediction methods. Therefore, past predictions may now need to be redone using the new sunspot series, and methods already used for predicting cycle 24 will require adaptations before attempting predictions of the next cycles.In order to clarify the nature of the applied changes, we describe the different corrections applied to the sunspot and group number series, which affect extended time periods and can reach up to 40%. While some changes simply involve constant scale factors, other corrections vary with time or follow the solar cycle modulation. Depending on the prediction method and on the selected time interval, this can lead to different responses and biases. Moreover, together with the new series, standard error estimates are also progressively added to the new sunspot numbers, which may help deriving more accurate uncertainties for predicted activity indices. We conclude on the new round of recalibration that is now undertaken in the framework of a broad multi-team collaboration articulated around upcoming ISSI workshops. We outline the future corrections that can still be expected in the future, as part of a permanent upgrading process and quality control. From now on, future sunspot-based predictive models should thus be made more adaptable, and regular updates of predictions should become common practice in order to track periodic upgrades of the sunspot number series, just like it is done when using other modern solar observational series.

Watchful Waiting for Cases of Pediatric Otitis Media: Modeling Parental Response to Physician Advice.

PubMed

MacGeorge, Erina L; Smith, Rachel A; Caldes, Emily P; Hackman, Nicole M

2016-08-01

Watchful waiting (WW) can reduce unnecessary antibiotic use in the treatment of pediatric otitis media (ear infection), but its utility is impaired by underutilization and noncompliance. Guided by advice response theory, the current study proposes advantage and capacity as factors that predict how caregivers evaluate and respond affectively to WW. Parents (N = 373) of at least 1 child age 5 years or younger completed questionnaires that assessed responses to hypothetical WW advice for their youngest child. Perceptions of advantage from WW and the capacity to monitor and manage symptoms predicted advice quality, physician trust, and future compliance both directly and indirectly through negative affect. The findings suggest the elaboration of advice response theory to include more aspects of advice content evaluation (e.g., advantage) and the influence of negative affect. The study also provides practical guidance for physicians seeking to improve caregiver reception of WW advice.

A Bayesian predictive two-stage design for phase II clinical trials.

PubMed

Sambucini, Valeria

2008-04-15

In this paper, we propose a Bayesian two-stage design for phase II clinical trials, which represents a predictive version of the single threshold design (STD) recently introduced by Tan and Machin. The STD two-stage sample sizes are determined specifying a minimum threshold for the posterior probability that the true response rate exceeds a pre-specified target value and assuming that the observed response rate is slightly higher than the target. Unlike the STD, we do not refer to a fixed experimental outcome, but take into account the uncertainty about future data. In both stages, the design aims to control the probability of getting a large posterior probability that the true response rate exceeds the target value. Such a probability is expressed in terms of prior predictive distributions of the data. The performance of the design is based on the distinction between analysis and design priors, recently introduced in the literature. The properties of the method are studied when all the design parameters vary.

Use of plethysmographic variability index derived from the Massimo(®) pulse oximeter to predict fluid or preload responsiveness: a systematic review and meta-analysis.

PubMed

Yin, J Y; Ho, K M

2012-07-01

This systematic review and meta-analysis assessed the accuracy of plethysmographic variability index derived from the Massimo(®) pulse oximeter to predict preload responsiveness in peri-operative and critically ill patients. A total of 10 studies were retrieved from the literature, involving 328 patients who met the selection criteria. Overall, the diagnostic odds ratio (16.0; 95% CI 5-48) and area under the summary receiver operating characteristic curve (0.87; 95% CI 0.78-0.95) for plethysmographic variability index to predict fluid or preload responsiveness was very good, but significant heterogeneity existed. This could be explained by a lower accuracy of plethysmographic variability index in spontaneously breathing or paediatric patients and those studies that used pre-load challenges other than colloid fluid. The results indicate specific directions for future studies. Anaesthesia © 2012 The Association of Anaesthetists of Great Britain and Ireland.

Increasing sugar transport to improve soybean response to elevated [CO2

USDA-ARS?s Scientific Manuscript database

Elevated atmospheric [CO2] causes a direct increase in instantaneous photosynthesis and sugar production in C3 plants, leading to a yield increase which is promising to meet future food demand. However, previous studies have shown that soybean yield does not increase as much as predicted under eleva...

Vegetation productivity responds to sub-annual climate conditions across semiarid biomes

USDA-ARS?s Scientific Manuscript database

In the Southwestern United States (SW), the current prolonged warm drought is similar to the predicted future climate change scenarios for the region. This study aimed to determine patterns in vegetation response to the early 21st century drought across multiple biomes. We hypothesized that differen...

Space-time modeling of timber prices

Treesearch

Mo Zhou; Joseph Buongriorno

2006-01-01

A space-time econometric model was developed for pine sawtimber timber prices of 21 geographically contiguous regions in the southern United States. The correlations between prices in neighboring regions helped predict future prices. The impulse response analysis showed that although southern pine sawtimber markets were not globally integrated, local supply and demand...

The Response of Fish Habitat to Environmental Flows in the Albemarle-Pamlico Watershed

EPA Science Inventory

The provision of habitat for fish is an important service provided by rivers. Future land development and climate change will likely alter several aspects of habitat, including flow. We have used hierarchical models to predict the presence of 25 fish species within the Albemarle-...

Microclimate and ecological threshold responses in a warming and wetting experiment following whole-tree harvest

USDA-ARS?s Scientific Manuscript database

Ecosystem climate manipulation experiments (ECMEs) are a key tool for predicting the effects of climate on ecosystems. However, the strength of inferences drawn from these experiments depends on whether the manipulated conditions mimic future climate changes. While ECMEs have examined mean tempera...

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.

Likelihood of achieving air quality targets under model uncertainties.

PubMed

Digar, Antara; Cohan, Daniel S; Cox, Dennis D; Kim, Byeong-Uk; Boylan, James W

2011-01-01

Regulatory attainment demonstrations in the United States typically apply a bright-line test to predict whether a control strategy is sufficient to attain an air quality standard. Photochemical models are the best tools available to project future pollutant levels and are a critical part of regulatory attainment demonstrations. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed. This paper introduces a computationally efficient methodology for estimating the likelihood that an emission control strategy will achieve an air quality objective in light of uncertainties in photochemical model input parameters (e.g., uncertain emission and reaction rates, deposition velocities, and boundary conditions). The method incorporates Monte Carlo simulations of a reduced form model representing pollutant-precursor response under parametric uncertainty to probabilistically predict the improvement in air quality due to emission control. The method is applied to recent 8-h ozone attainment modeling for Atlanta, Georgia, to assess the likelihood that additional controls would achieve fixed (well-defined) or flexible (due to meteorological variability and uncertain emission trends) targets of air pollution reduction. The results show that in certain instances ranking of the predicted effectiveness of control strategies may differ between probabilistic and deterministic analyses.

Intracranial pressure-induced optic nerve sheath response as a predictive biomarker for optic disc edema in astronauts.

PubMed

Wostyn, Peter; De Deyn, Peter Paul

2017-11-01

A significant proportion of the astronauts who spend extended periods in microgravity develop ophthalmic abnormalities. Understanding this syndrome, called visual impairment and intracranial pressure (VIIP), has become a high priority for National Aeronautics and Space Administration, especially in view of future long-duration missions (e.g., Mars missions). Moreover, to ensure selection of astronaut candidates who will be able to complete long-duration missions with low risk of the VIIP syndrome, it is imperative to identify biomarkers for VIIP risk prediction. Here, we hypothesize that the optic nerve sheath response to alterations in intracranial pressure may be a potential predictive biomarker for optic disc edema in astronauts. If confirmed, this biomarker could be used for preflight identification of astronauts at risk for developing VIIP-associated optic disc edema.

[Predictive factors of virological response in chronically HCV infected].

PubMed

Lapiński, Tadeusz Wojciech; Flisiak, Robert

2012-09-01

Research on new antivirals drugs applied in the treatment of chronically HCV infected indicate that even the most perfect therapeutic molecules do not guarantee 100% efficacy. Since the beginning of the history of HCV infection treatment clinicians looked for predictors of treatment efficacy. Numerous studies confirm the high probability of cure in patients who cleared HCVinfectional 4 and 12 weeks of therapy. However despite of viral factors, recent research demonstrated predictive role of some host dependent factors. The most important role seems to play genetic factors including polymorphism rs12979860, as well as chemokins including first of all CXCL10 (IP-10). Very interesting seems to be also results of studies on association between vitamine D concentration and treatment efficacy. However in the future the most important predictive factor remain probably early on-treatment viral response.

The potential for technology in brief interventions for substance use, and during-session prediction of computer-delivered brief intervention response.

PubMed

Ondersma, Steven J; Grekin, Emily R; Svikis, Dace

2011-01-01

We first provide an overview of the potential of technology in the area of brief interventions for substance use and describe recent projects from our lab that are illustrative of that potential. Second, we present data from a study of during-session predictors of brief intervention response. In a sample of postpartum women (N = 39), several variables showed promise as predictors of later drug use, and a brief index derived from them predicted abstinence with a sensitivity of .7 and a specificity of .89. This promising approach and initial study findings support the importance of future research in this area.

Subjective response as a consideration in the pharmacogenetics of alcoholism treatment.

PubMed

Roche, Daniel Jo; Ray, Lara A

2015-01-01

Currently available pharmacological treatments for alcoholism have modest efficacy and high individual variability in treatment outcomes, both of which have been partially attributed to genetic factors. One path to reducing the variability and improving the efficacy associated with these pharmacotherapies may be to identify overlapping genetic contributions to individual differences in both subjective responses to alcohol and alcoholism pharmacotherapy outcomes. As acute subjective response to alcohol is highly predictive of future alcohol related problems, identifying such shared genetic mechanisms may inform the development of personalized treatments that can effectively target converging pathophysiological mechanisms that convey risk for alcoholism. The focus of this review is to revisit the association between subjective response to alcohol and the etiology of alcoholism while also describing genetic contributions to this relationship, discuss potential pharmacogenetic approaches to target subjective response to alcohol in order to improve the treatment of alcoholism and examine conceptual and methodological issues associated with these topics, and outline future approaches to overcome these challenges.

Application of scenario-neutral methods to quantify impacts of climate change on water resources in East Africa

NASA Astrophysics Data System (ADS)

Ascott, M.; Macdonald, D.; Lapworth, D.; Tindimugaya, C.

2017-12-01

Quantification of the impact of climate change on water resources is essential for future resource planning. Unfortunately, climate change impact studies in African regions are often hindered by the extent in variability in future rainfall predictions, which also diverge from current drying trends. To overcome this limitation, "scenario-neutral" methods have been developed which stress a hydrological system using a wide range of climate futures to build a "climate response surface". We developed a hydrological model and scenario-neutral framework to quantify climate change impacts on river flows in the Katonga catchment, Uganda. Using the lumped catchment model GR4J, an acceptable calibration to historic daily flows (1966 - 2010, NSE = 0.69) was achieved. Using a delta change approach, we then systematically changed rainfall and PET inputs to develop response surfaces for key metrics, developed with Ugandan water resources planners (e.g. Q5, Q95). Scenarios from the CMIP5 models for 2030s and 2050s were then overlain on the response surface. The CMIP5 scenarios show consistent increases in temperature but large variability in rainfall increases, which results in substantial variability in increases in river flows. The developed response surface covers a wide range of climate futures beyond the CMIP5 projections, and can help water resources planners understand the sensitivity of water resource systems to future changes. When future climate scenarios are available, these can be directly overlain on the response surface without the need to re-run the hydrological model. Further work will consider using scenario-neutral approaches in more complex, semi-distributed models (e.g. SWAT), and will consider land use and socioeconomic change.

Exploring uncertainty of Amazon dieback in a perturbed parameter Earth system ensemble.

PubMed

Boulton, Chris A; Booth, Ben B B; Good, Peter

2017-12-01

The future of the Amazon rainforest is unknown due to uncertainties in projected climate change and the response of the forest to this change (forest resiliency). Here, we explore the effect of some uncertainties in climate and land surface processes on the future of the forest, using a perturbed physics ensemble of HadCM3C. This is the first time Amazon forest changes are presented using an ensemble exploring both land vegetation processes and physical climate feedbacks in a fully coupled modelling framework. Under three different emissions scenarios, we measure the change in the forest coverage by the end of the 21st century (the transient response) and make a novel adaptation to a previously used method known as "dry-season resilience" to predict the long-term committed response of the forest, should the state of the climate remain constant past 2100. Our analysis of this ensemble suggests that there will be a high chance of greater forest loss on longer timescales than is realized by 2100, especially for mid-range and low emissions scenarios. In both the transient and predicted committed responses, there is an increasing uncertainty in the outcome of the forest as the strength of the emissions scenarios increases. It is important to note however, that very few of the simulations produce future forest loss of the magnitude previously shown under the standard model configuration. We find that low optimum temperatures for photosynthesis and a high minimum leaf area index needed for the forest to compete for space appear to be precursors for dieback. We then decompose the uncertainty into that associated with future climate change and that associated with forest resiliency, finding that it is important to reduce the uncertainty in both of these if we are to better determine the Amazon's outcome. © 2017 John Wiley & Sons Ltd.

Predicting Individual Differences in Placebo Analgesia: Contributions of Brain Activity during Anticipation and Pain Experience

PubMed Central

Wager, Tor D.; Atlas, Lauren Y.; Leotti, Lauren A.; Rilling, James K.

2012-01-01

Recent studies have identified brain correlates of placebo analgesia, but none have assessed how accurately patterns of brain activity can predict individual differences in placebo responses. We reanalyzed data from two fMRI studies of placebo analgesia (N = 47), using patterns of fMRI activity during the anticipation and experience of pain to predict new subjects’ scores on placebo analgesia and placebo-induced changes in pain processing. We used a cross-validated regression procedure, LASSO-PCR, which provided both unbiased estimates of predictive accuracy and interpretable maps of which regions are most important for prediction. Increased anticipatory activity in a frontoparietal network and decreases in a posterior insular/temporal network predicted placebo analgesia. Patterns of anticipatory activity across the cortex predicted a moderate amount of variance in the placebo response (~12% overall, ~40% for study 2 alone), which is substantial considering the multiple likely contributing factors. The most predictive regions were those associated with emotional appraisal, rather than cognitive control or pain processing. During pain, decreases in limbic and paralimbic regions most strongly predicted placebo analgesia. Responses within canonical pain-processing regions explained significant variance in placebo analgesia, but the pattern of effects was inconsistent with widespread decreases in nociceptive processing. Together, the findings suggest that engagement of emotional appraisal circuits drives individual variation in placebo analgesia, rather than early suppression of nociceptive processing. This approach provides a framework that will allow prediction accuracy to increase as new studies provide more precise information for future predictive models. PMID:21228154

Wetter subtropics in a warmer world: Contrasting past and future hydrological cycles

NASA Astrophysics Data System (ADS)

Burls, Natalie J.; Fedorov, Alexey V.

2017-12-01

During the warm Miocene and Pliocene Epochs, vast subtropical regions had enough precipitation to support rich vegetation and fauna. Only with global cooling and the onset of glacial cycles some 3 Mya, toward the end of the Pliocene, did the broad patterns of arid and semiarid subtropical regions become fully developed. However, current projections of future global warming caused by CO2 rise generally suggest the intensification of dry conditions over these subtropical regions, rather than the return to a wetter state. What makes future projections different from these past warm climates? Here, we investigate this question by comparing a typical quadrupling-of-CO2 experiment with a simulation driven by sea-surface temperatures closely resembling available reconstructions for the early Pliocene. Based on these two experiments and a suite of other perturbed climate simulations, we argue that this puzzle is explained by weaker atmospheric circulation in response to the different ocean surface temperature patterns of the Pliocene, specifically reduced meridional and zonal temperature gradients. Thus, our results highlight that accurately predicting the response of the hydrological cycle to global warming requires predicting not only how global mean temperature responds to elevated CO2 forcing (climate sensitivity) but also accurately quantifying how meridional sea-surface temperature patterns will change (structural climate sensitivity).

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.

Spatial Prediction of Coxiella burnetii Outbreak Exposure via Notified Case Counts in a Dose-Response Model.

PubMed

Brooke, Russell J; Kretzschmar, Mirjam E E; Hackert, Volker; Hoebe, Christian J P A; Teunis, Peter F M; Waller, Lance A

2017-01-01

We develop a novel approach to study an outbreak of Q fever in 2009 in the Netherlands by combining a human dose-response model with geostatistics prediction to relate probability of infection and associated probability of illness to an effective dose of Coxiella burnetii. The spatial distribution of the 220 notified cases in the at-risk population are translated into a smooth spatial field of dose. Based on these symptomatic cases, the dose-response model predicts a median of 611 asymptomatic infections (95% range: 410, 1,084) for the 220 reported symptomatic cases in the at-risk population; 2.78 (95% range: 1.86, 4.93) asymptomatic infections for each reported case. The low attack rates observed during the outbreak range from (Equation is included in full-text article.)to (Equation is included in full-text article.). The estimated peak levels of exposure extend to the north-east from the point source with an increasing proportion of asymptomatic infections further from the source. Our work combines established methodology from model-based geostatistics and dose-response modeling allowing for a novel approach to study outbreaks. Unobserved infections and the spatially varying effective dose can be predicted using the flexible framework without assuming any underlying spatial structure of the outbreak process. Such predictions are important for targeting interventions during an outbreak, estimating future disease burden, and determining acceptable risk levels.

Utilization of the Generalized Method of Cells to Analyze the Deformation Response of Laminated Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.

2012-01-01

In order to practically utilize ceramic matrix composites in aircraft engine components, robust analysis tools are required that can simulate the material response in a computationally efficient manner. The MAC/GMC software developed at NASA Glenn Research Center, based on the Generalized Method of Cells micromechanics method, has the potential to meet this need. Utilizing MAC/GMC, the effective stiffness properties, proportional limit stress and ultimate strength can be predicted based on the properties and response of the individual constituents. In this paper, the effective stiffness and strength properties for a representative laminated ceramic matrix composite with a large diameter fiber are predicted for a variety of fiber orientation angles and laminate orientations. As part of the analytical study, methods to determine the in-situ stiffness and strength properties of the constituents required to appropriately simulate the effective composite response are developed. The stiffness properties of the representative composite have been adequately predicted for all of the fiber orientations and laminate configurations examined in this study. The proportional limit stresses and strains and ultimate stresses and strains were predicted with varying levels of accuracy, depending on the laminate orientation. However, for the cases where the predictions did not have the desired level of accuracy, the specific issues related to the micromechanics theory were identified which could lead to difficulties that were encountered that could be addressed in future work.

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.

Human Thermal Model Evaluation Using the JSC Human Thermal Database

NASA Technical Reports Server (NTRS)

Cognata, T.; Bue, G.; Makinen, J.

2011-01-01

The human thermal database developed at the Johnson Space Center (JSC) is used to evaluate a set of widely used human thermal models. This database will facilitate a more accurate evaluation of human thermoregulatory response using in a variety of situations, including those situations that might otherwise prove too dangerous for actual testing--such as extreme hot or cold splashdown conditions. This set includes the Wissler human thermal model, a model that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. These models are statistically compared to the current database, which contains experiments of human subjects primarily in air from a literature survey ranging between 1953 and 2004 and from a suited experiment recently performed by the authors, for a quantitative study of relative strength and predictive quality of the models. Human thermal modeling has considerable long term utility to human space flight. Such models provide a tool to predict crew survivability in support of vehicle design and to evaluate crew response in untested environments. It is to the benefit of any such model not only to collect relevant experimental data to correlate it against, but also to maintain an experimental standard or benchmark for future development in a readily and rapidly searchable and software accessible format. The Human thermal database project is intended to do just so; to collect relevant data from literature and experimentation and to store the data in a database structure for immediate and future use as a benchmark to judge human thermal models against, in identifying model strengths and weakness, to support model development and improve correlation, and to statistically quantify a model s predictive quality.

New methods in hydrologic modeling and decision support for culvert flood risk under climate change

NASA Astrophysics Data System (ADS)

Rosner, A.; Letcher, B. H.; Vogel, R. M.; Rees, P. S.

2015-12-01

Assessing culvert flood vulnerability under climate change poses an unusual combination of challenges. We seek a robust method of planning for an uncertain future, and therefore must consider a wide range of plausible future conditions. Culverts in our case study area, northwestern Massachusetts, USA, are predominantly found in small, ungaged basins. The need to predict flows both at numerous sites and under numerous plausible climate conditions requires a statistical model with low data and computational requirements. We present a statistical streamflow model that is driven by precipitation and temperature, allowing us to predict flows without reliance on reference gages of observed flows. The hydrological analysis is used to determine each culvert's risk of failure under current conditions. We also explore the hydrological response to a range of plausible future climate conditions. These results are used to determine the tolerance of each culvert to future increases in precipitation. In a decision support context, current flood risk as well as tolerance to potential climate changes are used to provide a robust assessment and prioritization for culvert replacements.

Causes of variation among rice models in yield response to CO2 examined with Free-Air CO2 Enrichment and growth chamber experiments.

PubMed

Hasegawa, Toshihiro; Li, Tao; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Baker, Jeffrey; Bregaglio, Simone; Buis, Samuel; Confalonieri, Roberto; Fugice, Job; Fumoto, Tamon; Gaydon, Donald; Kumar, Soora Naresh; Lafarge, Tanguy; Marcaida Iii, Manuel; Masutomi, Yuji; Nakagawa, Hiroshi; Oriol, Philippe; Ruget, Françoise; Singh, Upendra; Tang, Liang; Tao, Fulu; Wakatsuki, Hitomi; Wallach, Daniel; Wang, Yulong; Wilson, Lloyd Ted; Yang, Lianxin; Yang, Yubin; Yoshida, Hiroe; Zhang, Zhao; Zhu, Jianguo

2017-11-01

The CO 2 fertilization effect is a major source of uncertainty in crop models for future yield forecasts, but coordinated efforts to determine the mechanisms of this uncertainty have been lacking. Here, we studied causes of uncertainty among 16 crop models in predicting rice yield in response to elevated [CO 2 ] (E-[CO 2 ]) by comparison to free-air CO 2 enrichment (FACE) and chamber experiments. The model ensemble reproduced the experimental results well. However, yield prediction in response to E-[CO 2 ] varied significantly among the rice models. The variation was not random: models that overestimated at one experiment simulated greater yield enhancements at the others. The variation was not associated with model structure or magnitude of photosynthetic response to E-[CO 2 ] but was significantly associated with the predictions of leaf area. This suggests that modelled secondary effects of E-[CO 2 ] on morphological development, primarily leaf area, are the sources of model uncertainty. Rice morphological development is conservative to carbon acquisition. Uncertainty will be reduced by incorporating this conservative nature of the morphological response to E-[CO 2 ] into the models. Nitrogen levels, particularly under limited situations, make the prediction more uncertain. Improving models to account for [CO 2 ] × N interactions is necessary to better evaluate management practices under climate change.

Blood eosinophil levels as a biomarker in COPD.

PubMed

Brusselle, Guy; Pavord, Ian D; Landis, Sarah; Pascoe, Steven; Lettis, Sally; Morjaria, Nikhil; Barnes, Neil; Hilton, Emma

2018-05-01

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disorder and patients respond differently to treatment. Blood eosinophils are a potential biomarker to stratify patient subsets for COPD therapy. We reviewed the value of blood eosinophils in predicting exacerbation risk and response to corticosteroid treatment in the available literature (PubMed articles in English; keywords: "COPD" and "eosinophil"; published prior to May 2017). Overall, clinical data suggest that in patients with a history of COPD exacerbations, a higher blood eosinophil count predicts an increased risk of future exacerbations and is associated with improved response to treatment with inhaled corticosteroids (in combination with long-acting bronchodilator[s]). Blood eosinophils are therefore a promising biomarker for phenotyping patients with COPD, although prospective studies are needed to assess blood eosinophils as a biomarker of corticosteroid response for this. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Prediction-based dynamic load-sharing heuristics

NASA Technical Reports Server (NTRS)

Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.

1993-01-01

The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.

Incorporating adaptive responses into future projections of coral bleaching.

PubMed

Logan, Cheryl A; Dunne, John P; Eakin, C Mark; Donner, Simon D

2014-01-01

Climate warming threatens to increase mass coral bleaching events, and several studies have projected the demise of tropical coral reefs this century. However, recent evidence indicates corals may be able to respond to thermal stress though adaptive processes (e.g., genetic adaptation, acclimatization, and symbiont shuffling). How these mechanisms might influence warming-induced bleaching remains largely unknown. This study compared how different adaptive processes could affect coral bleaching projections. We used the latest bias-corrected global sea surface temperature (SST) output from the NOAA/GFDL Earth System Model 2 (ESM2M) for the preindustrial period through 2100 to project coral bleaching trajectories. Initial results showed that, in the absence of adaptive processes, application of a preindustrial climatology to the NOAA Coral Reef Watch bleaching prediction method overpredicts the present-day bleaching frequency. This suggests that corals may have already responded adaptively to some warming over the industrial period. We then modified the prediction method so that the bleaching threshold either permanently increased in response to thermal history (e.g., simulating directional genetic selection) or temporarily increased for 2-10 years in response to a bleaching event (e.g., simulating symbiont shuffling). A bleaching threshold that changes relative to the preceding 60 years of thermal history reduced the frequency of mass bleaching events by 20-80% compared with the 'no adaptive response' prediction model by 2100, depending on the emissions scenario. When both types of adaptive responses were applied, up to 14% more reef cells avoided high-frequency bleaching by 2100. However, temporary increases in bleaching thresholds alone only delayed the occurrence of high-frequency bleaching by ca. 10 years in all but the lowest emissions scenario. Future research should test the rate and limit of different adaptive responses for coral species across latitudes and ocean basins to determine if and how much corals can respond to increasing thermal stress.

Change in avian abundance predicted from regional forest inventory data

USGS Publications Warehouse

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

2010-01-01

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

2011 Souris River flood—Will it happen again?

USGS Publications Warehouse

Nustad, Rochelle A.; Kolars, Kelsey A.; Vecchia, Aldo V.; Ryberg, Karen R.

2016-09-29

The Souris River Basin is a 61,000 square kilometer basin in the provinces of Saskatchewan and Manitoba and the state of North Dakota. Record setting rains in May and June of 2011 led to record flooding with peak annual streamflow values (762 cubic meters per second [m3/s]) more than twice that of any previously recorded peak streamflow and more than five times the estimated 100 year postregulation streamflow (142 m3/s) at the U.S. Geological Survey (USGS) streamflow-gaging station above Minot, North Dakota. Upstream from Minot, N. Dak., the Souris River is regulated by three reservoirs in Saskatchewan (Rafferty, Boundary, and Alameda) and Lake Darling in North Dakota. During the 2011 flood, the city of Minot, N. Dak., experienced devastating damages with more than 4,000 homes flooded and 11,000 evacuated. As a result, the Souris River Basin Task Force recommended the U.S. Geological Survey (in cooperation with the North Dakota State Water Commission) develop a model for estimating the probabilities of future flooding and drought. The model that was developed took on four parts: (1) looking at past climate, (2) predicting future climate, (3) developing a streamflow model in response to certain climatic variables, and (4) combining future climate estimates with the streamflow model to predict future streamflow events. By taking into consideration historical climate record and trends in basin response to various climatic conditions, it was determined flood risk will remain high in the Souris River Basin until the wet climate state ends.

Cancer Precision Medicine: Why More Is More and DNA Is Not Enough.

PubMed

Schütte, Moritz; Ogilvie, Lesley A; Rieke, Damian T; Lange, Bodo M H; Yaspo, Marie-Laure; Lehrach, Hans

2017-01-01

Every tumour is different. They arise in patients with different genomes, from cells with different epigenetic modifications, and by random processes affecting the genome and/or epigenome of a somatic cell, allowing it to escape the usual controls on its growth. Tumours and patients therefore often respond very differently to the drugs they receive. Cancer precision medicine aims to characterise the tumour (and often also the patient) to be able to predict, with high accuracy, its response to different treatments, with options ranging from the selective characterisation of a few genomic variants considered particularly important to predict the response of the tumour to specific drugs, to deep genome analysis of both tumour and patient, combined with deep transcriptome analysis of the tumour. Here, we compare the expected results of carrying out such analyses at different levels, from different size panels to a comprehensive analysis incorporating both patient and tumour at the DNA and RNA levels. In doing so, we illustrate the additional power gained by this unusually deep analysis strategy, a potential basis for a future precision medicine first strategy in cancer drug therapy. However, this is only a step along the way of increasingly detailed molecular characterisation, which in our view will, in the future, introduce additional molecular characterisation techniques, including systematic analysis of proteins and protein modification states and different types of metabolites in the tumour, systematic analysis of circulating tumour cells and nucleic acids, the use of spatially resolved analysis techniques to address the problem of tumour heterogeneity as well as the deep analyses of the immune system of the patient to, e.g., predict the response of the patient to different types of immunotherapy. Such analyses will generate data sets of even greater complexity, requiring mechanistic modelling approaches to capture enough of the complex situation in the real patient to be able to accurately predict his/her responses to all available therapies. © 2017 S. Karger AG, Basel.

Pathogen-Host Associations and Predicted Range Shifts of Human Monkeypox in Response to Climate Change in Central Africa

PubMed Central

Thomassen, Henri A.; Fuller, Trevon; Asefi-Najafabady, Salvi; Shiplacoff, Julia A. G.; Mulembakani, Prime M.; Blumberg, Seth; Johnston, Sara C.; Kisalu, Neville K.; Kinkela, Timothée L.; Fair, Joseph N.; Wolfe, Nathan D.; Shongo, Robert L.; LeBreton, Matthew; Meyer, Hermann; Wright, Linda L.; Muyembe, Jean-Jacques; Buermann, Wolfgang; Okitolonda, Emile; Hensley, Lisa E.; Lloyd-Smith, James O.; Smith, Thomas B.; Rimoin, Anne W.

2013-01-01

Climate change is predicted to result in changes in the geographic ranges and local prevalence of infectious diseases, either through direct effects on the pathogen, or indirectly through range shifts in vector and reservoir species. To better understand the occurrence of monkeypox virus (MPXV), an emerging Orthopoxvirus in humans, under contemporary and future climate conditions, we used ecological niche modeling techniques in conjunction with climate and remote-sensing variables. We first created spatially explicit probability distributions of its candidate reservoir species in Africa's Congo Basin. Reservoir species distributions were subsequently used to model current and projected future distributions of human monkeypox (MPX). Results indicate that forest clearing and climate are significant driving factors of the transmission of MPX from wildlife to humans under current climate conditions. Models under contemporary climate conditions performed well, as indicated by high values for the area under the receiver operator curve (AUC), and tests on spatially randomly and non-randomly omitted test data. Future projections were made on IPCC 4th Assessment climate change scenarios for 2050 and 2080, ranging from more conservative to more aggressive, and representing the potential variation within which range shifts can be expected to occur. Future projections showed range shifts into regions where MPX has not been recorded previously. Increased suitability for MPX was predicted in eastern Democratic Republic of Congo. Models developed here are useful for identifying areas where environmental conditions may become more suitable for human MPX; targeting candidate reservoir species for future screening efforts; and prioritizing regions for future MPX surveillance efforts. PMID:23935820

Increase in observed net carbon dioxide uptake by land and oceans during the past 50 years.

PubMed

Ballantyne, A P; Alden, C B; Miller, J B; Tans, P P; White, J W C

2012-08-02

One of the greatest sources of uncertainty for future climate predictions is the response of the global carbon cycle to climate change. Although approximately one-half of total CO(2) emissions is at present taken up by combined land and ocean carbon reservoirs, models predict a decline in future carbon uptake by these reservoirs, resulting in a positive carbon-climate feedback. Several recent studies suggest that rates of carbon uptake by the land and ocean have remained constant or declined in recent decades. Other work, however, has called into question the reported decline. Here we use global-scale atmospheric CO(2) measurements, CO(2) emission inventories and their full range of uncertainties to calculate changes in global CO(2) sources and sinks during the past 50 years. Our mass balance analysis shows that net global carbon uptake has increased significantly by about 0.05 billion tonnes of carbon per year and that global carbon uptake doubled, from 2.4 ± 0.8 to 5.0 ± 0.9 billion tonnes per year, between 1960 and 2010. Therefore, it is very unlikely that both land and ocean carbon sinks have decreased on a global scale. Since 1959, approximately 350 billion tonnes of carbon have been emitted by humans to the atmosphere, of which about 55 per cent has moved into the land and oceans. Thus, identifying the mechanisms and locations responsible for increasing global carbon uptake remains a critical challenge in constraining the modern global carbon budget and predicting future carbon-climate interactions.

Fear of Terrorism in New York After the September 11 Terrorist Attacks: Implications for Emergency Mental Health and Preparedness

PubMed Central

Boscarino, Joseph A.; Figley, Charles R.; Adams, Richard E.

2009-01-01

To examine the public’s response to future terrorist attacks, we surveyed 1,001 New Yorkers in the community one year after the September 11 attacks. Overall, New Yorkers were very concerned about future terrorist attacks and also concerned about attacks involving biological or nuclear weapons. In addition, while most New Yorkers reported that if a biological or nuclear attack occurred they would evaluate available information before evacuating, a significant number reported they would immediately evacuate, regardless of police or public health communications to the contrary. The level of public concern was significantly higher on all measures among New York City and Long Island residents (downstate) compared to the rest of the state. A model predicting higher fear of terrorism indicated that downstate residents, women, those 45 to 64 years old, African Americans and Hispanics, those with less education/income, and those more likely to flee, were more fearful of future attacks. In addition, making disaster preparations and carefully evaluating emergency information also predicted a higher level of fear as well. A second model predicting who would flee suggested that those more likely to evaluate available information were less likely to immediately evacuate, while those with a higher fear of future attacks were more likely to flee the area. Given these findings and the possibility of future attacks, mental health professionals need to be more involved in preparedness efforts, especially related to the psychological impact of attacks involving weapons of mass destruction. PMID:14730761

Fear of terrorism in New York after the September 11 terrorist attacks: implications for emergency mental health and preparedness.

PubMed

Boscarino, Joseph A; Figley, Charles R; Adams, Richard E

2003-01-01

To examine the public's response to future terrorist attacks, we surveyed 1,001 New Yorkers in the community one year after the September 11 attacks. Overall, New Yorkers were very concerned about future terrorist attacks and also concerned about attacks involving biological or nuclear weapons. In addition, while most New Yorkers reported that if a biological or nuclear attack occurred they would evaluate available information before evacuating, a significant number reported they would immediately evacuate, regardless of police or public health communications to the contrary. The level of public concern was significantly higher on all measures among New York City and Long Island residents (downstate) compared to the rest of the state. A model predicting higher fear of terrorism indicated that downstate residents, women, those 45 to 64 years old, African Americans and Hispanics, those with less education/income, and those more likely to flee, were more fearful of future attacks. In addition, making disaster preparations and carefully evaluating emergency information also predicted a higher level of fear as well. A second model predicting who would flee suggested that those more likely to evaluate available information were less likely to immediately evacuate, while those with a higher fear of future attacks were more likely to flee the area. Given these findings and the possibility of future attacks, mental health professionals need to be more involved in preparedness efforts, especially related to the psychological impact of attacks involving weapons of mass destruction.

Individual to Community-Level Faunal Responses to Environmental Change from a Marine Fossil Record of Early Miocene Global Warming

PubMed Central

Belanger, Christina L.

2012-01-01

Modern climate change has a strong potential to shift earth systems and biological communities into novel states that have no present-day analog, leaving ecologists with no observational basis to predict the likely biotic effects. Fossil records contain long time-series of past environmental changes outside the range of modern observation, which are vital for predicting future ecological responses, and are capable of (a) providing detailed information on rates of ecological change, (b) illuminating the environmental drivers of those changes, and (c) recording the effects of environmental change on individual physiological rates. Outcrops of Early Miocene Newport Member of the Astoria Formation (Oregon) provide one such time series. This record of benthic foraminiferal and molluscan community change from continental shelf depths spans a past interval environmental change (∼20.3-16.7 mya) during which the region warmed 2.1–4.5°C, surface productivity and benthic organic carbon flux increased, and benthic oxygenation decreased, perhaps driven by intensified upwelling as on the modern Oregon coast. The Newport Member record shows that (a) ecological responses to natural environmental change can be abrupt, (b) productivity can be the primary driver of faunal change during global warming, (c) molluscs had a threshold response to productivity change while foraminifera changed gradually, and (d) changes in bivalve body size and growth rates parallel changes in taxonomic composition at the community level, indicating that, either directly or indirectly through some other biological parameter, the physiological tolerances of species do influence community change. Ecological studies in modern and fossil records that consider multiple ecological levels, environmental parameters, and taxonomic groups can provide critical information for predicting future ecological change and evaluating species vulnerability. PMID:22558424

Modelling the feedbacks between mass balance, ice flow and debris transport to predict the response to climate change of debris-covered glaciers in the Himalaya

NASA Astrophysics Data System (ADS)

Rowan, Ann V.; Egholm, David L.; Quincey, Duncan J.; Glasser, Neil F.

2015-11-01

Many Himalayan glaciers are characterised in their lower reaches by a rock debris layer. This debris insulates the glacier surface from atmospheric warming and complicates the response to climate change compared to glaciers with clean-ice surfaces. Debris-covered glaciers can persist well below the altitude that would be sustainable for clean-ice glaciers, resulting in much longer timescales of mass loss and meltwater production. The properties and evolution of supraglacial debris present a considerable challenge to understanding future glacier change. Existing approaches to predicting variations in glacier volume and meltwater production rely on numerical models that represent the processes governing glaciers with clean-ice surfaces, and yield conflicting results. We developed a numerical model that couples the flow of ice and debris and includes important feedbacks between debris accumulation and glacier mass balance. To investigate the impact of debris transport on the response of a glacier to recent and future climate change, we applied this model to a large debris-covered Himalayan glacier-Khumbu Glacier in Nepal. Our results demonstrate that supraglacial debris prolongs the response of the glacier to warming and causes lowering of the glacier surface in situ, concealing the magnitude of mass loss when compared with estimates based on glacierised area. Since the Little Ice Age, Khumbu Glacier has lost 34% of its volume while its area has reduced by only 6%. We predict a decrease in glacier volume of 8-10% by AD2100, accompanied by dynamic and physical detachment of the debris-covered tongue from the active glacier within the next 150 yr. This detachment will accelerate rates of glacier decay, and similar changes are likely for other debris-covered glaciers in the Himalaya.

University Policies under Varying Market Conditions: The Training of Electrical Engineers.

ERIC Educational Resources Information Center

Eckstein, Zvi; And Others

1988-01-01

Analyzes an Israeli university's problem in optimizing the quality and quantity of electrical engineers in response to fluctuating enrollment. An equilibrium model considers the effect of students' occupation choice and the university's decision on the current and future demand and supply of engineers, in order to predict the equilibrium number of…

Belowground Response to Drought in a Tropical Forest Soil. I. Changes in Microbial Functional Potential and Metabolism

Treesearch

Nicholas J. Bouskill; Tana E. Wood; Richard Baran; Zaw Ye; Benjamin P. Bowen; HsiaoChien Lim; Jizhong Zhou; Joy D. Van Nostrand; Peter Nico; Trent R. Northen; Whendee L. Silver; Eoin L. Brodie

2016-01-01

Global climate models predict a future of increased severity of drought in many tropical forests. Soil microbes are central to the balance of these systems as sources or sinks of atmospheric carbon (C), yet how they respond metabolically to drought is not well-understood. We simulated...

Attitudes of Preschool and Primary School Pre-Service Teachers towards Inclusive Education

ERIC Educational Resources Information Center

Kraska, Jake; Boyle, Christopher

2014-01-01

Teachers' attitudes towards inclusion are important as they have the primary responsibility of implementing inclusive education. Attitudes at the beginning of teaching careers are likely to predict future attitudes. Some studies show a drop in attitudes after leaving university education. Using the Teachers' Attitudes Towards Inclusion (Amended)…

Shallow aquifer response to climate change scenarios in a small catchment in the Guarani Aquifer outcrop zone.

PubMed

Melo, Davi C D; Wendland, Edson

2017-05-01

Water availability restrictions are already a reality in several countries. This issue is likely to worsen due to climate change, predicted for the upcoming decades. This study aims to estimate the impacts of climate change on groundwater system in the Guarani Aquifer outcrop zone. Global Climate Models (GCM) outputs were used as inputs to a water balance model, which produced recharge estimates for the groundwater model. Recharge was estimated across different land use types considering a control period from 2004 to 2014, and a future period from 2081 to 2099. Major changes in monthly rainfall means are expected to take place in dry seasons. Most of the analysed scenarios predict increase of more than 2 ºC in monthly mean temperatures. Comparing the control and future runs, our results showed a mean recharge change among scenarios that ranged from ~-80 to ~+60%, depending on the land use type. As a result of such decrease in recharge rates, the response given by the groundwater model indicates a lowering of the water table under most scenarios.

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

PubMed Central

Sieberts, Solveig K.; Zhu, Fan; García-García, Javier; Stahl, Eli; Pratap, Abhishek; Pandey, Gaurav; Pappas, Dimitrios; Aguilar, Daniel; Anton, Bernat; Bonet, Jaume; Eksi, Ridvan; Fornés, Oriol; Guney, Emre; Li, Hongdong; Marín, Manuel Alejandro; Panwar, Bharat; Planas-Iglesias, Joan; Poglayen, Daniel; Cui, Jing; Falcao, Andre O.; Suver, Christine; Hoff, Bruce; Balagurusamy, Venkat S. K.; Dillenberger, Donna; Neto, Elias Chaibub; Norman, Thea; Aittokallio, Tero; Ammad-ud-din, Muhammad; Azencott, Chloe-Agathe; Bellón, Víctor; Boeva, Valentina; Bunte, Kerstin; Chheda, Himanshu; Cheng, Lu; Corander, Jukka; Dumontier, Michel; Goldenberg, Anna; Gopalacharyulu, Peddinti; Hajiloo, Mohsen; Hidru, Daniel; Jaiswal, Alok; Kaski, Samuel; Khalfaoui, Beyrem; Khan, Suleiman Ali; Kramer, Eric R.; Marttinen, Pekka; Mezlini, Aziz M.; Molparia, Bhuvan; Pirinen, Matti; Saarela, Janna; Samwald, Matthias; Stoven, Véronique; Tang, Hao; Tang, Jing; Torkamani, Ali; Vert, Jean-Phillipe; Wang, Bo; Wang, Tao; Wennerberg, Krister; Wineinger, Nathan E.; Xiao, Guanghua; Xie, Yang; Yeung, Rae; Zhan, Xiaowei; Zhao, Cheng; Calaza, Manuel; Elmarakeby, Haitham; Heath, Lenwood S.; Long, Quan; Moore, Jonathan D.; Opiyo, Stephen Obol; Savage, Richard S.; Zhu, Jun; Greenberg, Jeff; Kremer, Joel; Michaud, Kaleb; Barton, Anne; Coenen, Marieke; Mariette, Xavier; Miceli, Corinne; Shadick, Nancy; Weinblatt, Michael; de Vries, Niek; Tak, Paul P.; Gerlag, Danielle; Huizinga, Tom W. J.; Kurreeman, Fina; Allaart, Cornelia F.; Louis Bridges Jr., S.; Criswell, Lindsey; Moreland, Larry; Klareskog, Lars; Saevarsdottir, Saedis; Padyukov, Leonid; Gregersen, Peter K.; Friend, Stephen; Plenge, Robert; Stolovitzky, Gustavo; Oliva, Baldo; Guan, Yuanfang; Mangravite, Lara M.

2016-01-01

Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h2=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data. PMID:27549343

Predicted and experienced affective responses to the outcome of the 2008 U.S. presidential election.

PubMed

Kitchens, Michael B; Corser, Grant C; Gohm, Carol L; VonWaldner, Kristen L; Foreman, Elizabeth L

2010-12-01

People typically have intense feelings about politics. Therefore, it was no surprise that the campaign and eventual election of Barack Obama were highly anticipated and emotionally charged events, making it and the emotion experienced afterward a useful situation in which to replicate prior research showing that people typically overestimate the intensity and duration of their future affective states. Consequently, it was expected that Obama supporters and McCain supporters might overestimate the intensity of their affective responses to the outcome of the election. Data showed that while McCain supporters underestimated how happy they would be following the election, Obama supporters accurately predicted how happy they would be following the election. These data provide descriptive information on the accuracy of people's predicted reactions to the 2008 U.S. presidential election. The findings are discussed in the context of the broad literature and this specific and unique event.

Illness severity and self-efficacy as course predictors of DSM-IV alcohol dependence in a multisite clinical sample.

PubMed

Langenbucher, J; Sulesund, D; Chung, T; Morgenstern, J

1996-01-01

Illness severity and self-efficacy are two constructs of growing interest as predictors of clinical response in alcoholism. Using alternative measures of illness severity (DSM-IV symptom count, Alcohol Dependence Scale, and Addiction Severity Index) and self-efficacy (brief version of the Situational Confidence Questionnaire) rigorously controlled for theoretically important background variables, we studied their unique contribution to multiple indices of relapse, relapse latency, and use of alternative coping behaviors in a large, heterogeneous clinical sample. The Alcohol Dependence Scale contributed to the prediction of 4 of 5 relapse indicators. The SCQ failed to predict relapse behavior or its precursor, coping response. The findings emphasize the predictive validity of severity of dependence as a course specifier and underline the need for more sensitive and externally valid measures of cognitive processes such as self-efficacy for application in future studies of posttreatment behavior.

Attachment, social support, and responses following the death of a companion animal.

PubMed

King, Loren C; Werner, Paul D

This research tested hypotheses concerning attachment, social support, and grief responses to the loss of animal companionship. Participants whose companion cat or dog had recently died (N = 429) completed the Attachment Style Questionnaire, the Inventory of Complicated Grief, and the Multidimensional Health Profile-Psychosocial Functioning questionnaires. Both attachment anxiety and attachment avoidance were found to be positively associated with respondents' grief, depression, anxiety, and somatic symptoms. Social support was found to be negatively associated with these outcomes as well as with attachment anxiety and attachment avoidance. In multiple regression analyses, attachment anxiety incrementally predicted grief, anxiety and somatic symptoms, attachment avoidance incrementally predicted grief and depression, and social support incrementally predicted all outcomes. Interaction effects of attachment and social support in relation to outcomes were not found. The present study's implications and limitations are discussed, as are directions for future research.

Predictive potential of IL-28B genetic testing for interferon based hepatitis C virus therapy in Pakistan: Current scenario and future perspective.

PubMed

Afzal, Muhammad Sohail

2016-09-18

In Pakistan which ranked second in terms of hepatitis C virus (HCV) infection, it is highly needed to have an established diagnostic test for antiviral therapy response prediction. Interleukin 28B (IL-28B) genetic testing is widely used throughout the world for interferon based therapy prediction for HCV patients and is quite helpful not only for health care workers but also for the patients. There is a strong relationship between single nucleotide polymorphisms at or near the IL-28B gene and the sustained virological response with pegylated interferon plus ribavirin treatment for chronic hepatitis C. Pakistan is a resource limited country, with very low per capita income and there is no proper social security (health insurance) system. The allocated health budget by the government is very low and is used on other health emergencies like polio virus and dengue virus infection. Therefore it is proposed that there should be a well established diagnostic test on the basis of IL-28B which can predict the antiviral therapy response to strengthen health care set-up of Pakistan. This test once established will help in better management of HCV infected patients.

Ready or Not: Microbial Adaptive Responses in Dynamic Symbiosis Environments.

PubMed

Cao, Mengyi; Goodrich-Blair, Heidi

2017-08-01

In mutually beneficial and pathogenic symbiotic associations, microbes must adapt to the host environment for optimal fitness. Both within an individual host and during transmission between hosts, microbes are exposed to temporal and spatial variation in environmental conditions. The phenomenon of phenotypic variation, in which different subpopulations of cells express distinctive and potentially adaptive characteristics, can contribute to microbial adaptation to a lifestyle that includes rapidly changing environments. The environments experienced by a symbiotic microbe during its life history can be erratic or predictable, and each can impact the evolution of adaptive responses. In particular, the predictability of a rhythmic or cyclical series of environments may promote the evolution of signal transduction cascades that allow preadaptive responses to environments that are likely to be encountered in the future, a phenomenon known as adaptive prediction. In this review, we summarize environmental variations known to occur in some well-studied models of symbiosis and how these may contribute to the evolution of microbial population heterogeneity and anticipatory behavior. We provide details about the symbiosis between Xenorhabdus bacteria and Steinernema nematodes as a model to investigate the concept of environmental adaptation and adaptive prediction in a microbial symbiosis. Copyright © 2017 American Society for Microbiology.

Human Thermal Model Evaluation Using the JSC Human Thermal Database

NASA Technical Reports Server (NTRS)

Bue, Grant; Makinen, Janice; Cognata, Thomas

2012-01-01

Human thermal modeling has considerable long term utility to human space flight. Such models provide a tool to predict crew survivability in support of vehicle design and to evaluate crew response in untested space environments. It is to the benefit of any such model not only to collect relevant experimental data to correlate it against, but also to maintain an experimental standard or benchmark for future development in a readily and rapidly searchable and software accessible format. The Human thermal database project is intended to do just so; to collect relevant data from literature and experimentation and to store the data in a database structure for immediate and future use as a benchmark to judge human thermal models against, in identifying model strengths and weakness, to support model development and improve correlation, and to statistically quantify a model s predictive quality. The human thermal database developed at the Johnson Space Center (JSC) is intended to evaluate a set of widely used human thermal models. This set includes the Wissler human thermal model, a model that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. These models are statistically compared to the current database, which contains experiments of human subjects primarily in air from a literature survey ranging between 1953 and 2004 and from a suited experiment recently performed by the authors, for a quantitative study of relative strength and predictive quality of the models.

Emotional distress impacts fear of the future among breast cancer survivors not the reverse.

PubMed

Lebel, Sophie; Rosberger, Zeev; Edgar, Linda; Devins, Gerald M

2009-06-01

Fear of the future is one of the most stressful aspects of having cancer. Research to date has conceptualized fear of the future as a precursor of distress or stress-response symptoms. Yet it is equally plausible that distress would predict increased fear of the future or that they would have a reciprocal influence on each other. The purpose of the present study was to examine the bidirectional relations between fear of the future and distress as well as intrusion and avoidance among breast cancer survivors at 3, 7, 11, and 15 months after diagnosis. We used a bivariate latent difference score model for dynamic change to examine these bidirectional relationships among 146 early-stage breast cancer survivors. Using Lisrel version 8.80, we examined four models testing different hypothesized relationships between fear of the future and distress and intrusion and avoidance. Based on model fit evaluation, our data shows that decreases in distress over time lead to a reduction of fear of the future but that changes in fear do not lead to changes in distress. On the other hand, there is no relationship between changes in fear of the future and intrusion and avoidance over time. Ongoing fear of the future does not appear to be a necessary condition for the development of stress-response symptoms. Future studies need to explore the role of distressing emotions in the development and exacerbation of fear of the future among cancer survivors.

Comparison of continuous versus categorical tumor measurement-based metrics to predict overall survival in cancer treatment trials.

PubMed

An, Ming-Wen; Mandrekar, Sumithra J; Branda, Megan E; Hillman, Shauna L; Adjei, Alex A; Pitot, Henry C; Goldberg, Richard M; Sargent, Daniel J

2011-10-15

The categorical definition of response assessed via the Response Evaluation Criteria in Solid Tumors has documented limitations. We sought to identify alternative metrics for tumor response that improve prediction of overall survival. Individual patient data from three North Central Cancer Treatment Group trials (N0026, n = 117; N9741, n = 1,109; and N9841, n = 332) were used. Continuous metrics of tumor size based on longitudinal tumor measurements were considered in addition to a trichotomized response [TriTR: response (complete or partial) vs. stable disease vs. progression). Cox proportional hazards models, adjusted for treatment arm and baseline tumor burden, were used to assess the impact of the metrics on subsequent overall survival, using a landmark analysis approach at 12, 16, and 24 weeks postbaseline. Model discrimination was evaluated by the concordance (c) index. The overall best response rates for the three trials were 26%, 45%, and 25%, respectively. Although nearly all metrics were statistically significantly associated with overall survival at the different landmark time points, the concordance indices (c-index) for the traditional response metrics ranged from 0.59 to 0.65; for the continuous metrics from 0.60 to 0.66; and for the TriTR metrics from 0.64 to 0.69. The c-indices for TriTR at 12 weeks were comparable with those at 16 and 24 weeks. Continuous tumor measurement-based metrics provided no predictive improvement over traditional response-based metrics or TriTR; TriTR had better predictive ability than best TriTR or confirmed response. If confirmed, TriTR represents a promising endpoint for future phase II trials. ©2011 AACR.

Comparison of continuous versus categorical tumor measurement-based metrics to predict overall survival in cancer treatment trials

PubMed Central

An, Ming-Wen; Mandrekar, Sumithra J.; Branda, Megan E.; Hillman, Shauna L.; Adjei, Alex A.; Pitot, Henry; Goldberg, Richard M.; Sargent, Daniel J.

2011-01-01

Purpose The categorical definition of response assessed via the Response Evaluation Criteria in Solid Tumors has documented limitations. We sought to identify alternative metrics for tumor response that improve prediction of overall survival. Experimental Design Individual patient data from three North Central Cancer Treatment Group trials (N0026, n=117; N9741, n=1109; N9841, n=332) were used. Continuous metrics of tumor size based on longitudinal tumor measurements were considered in addition to a trichotomized response (TriTR: Response vs. Stable vs. Progression). Cox proportional hazards models, adjusted for treatment arm and baseline tumor burden, were used to assess the impact of the metrics on subsequent overall survival, using a landmark analysis approach at 12-, 16- and 24-weeks post baseline. Model discrimination was evaluated using the concordance (c) index. Results The overall best response rates for the three trials were 26%, 45%, and 25% respectively. While nearly all metrics were statistically significantly associated with overall survival at the different landmark time points, the c-indices for the traditional response metrics ranged from 0.59-0.65; for the continuous metrics from 0.60-0.66 and for the TriTR metrics from 0.64-0.69. The c-indices for TriTR at 12-weeks were comparable to those at 16- and 24-weeks. Conclusions Continuous tumor-measurement-based metrics provided no predictive improvement over traditional response based metrics or TriTR; TriTR had better predictive ability than best TriTR or confirmed response. If confirmed, TriTR represents a promising endpoint for future Phase II trials. PMID:21880789

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

USGS Publications Warehouse

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

2012-01-01

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

Enteric disease episodes and the risk of acquiring a future sexually transmitted infection: a prediction model in Montreal residents.

PubMed

Caron, Melissa; Allard, Robert; Bédard, Lucie; Latreille, Jérôme; Buckeridge, David L

2016-11-01

The sexual transmission of enteric diseases poses an important public health challenge. We aimed to build a prediction model capable of identifying individuals with a reported enteric disease who could be at risk of acquiring future sexually transmitted infections (STIs). Passive surveillance data on Montreal residents with at least 1 enteric disease report was used to construct the prediction model. Cases were defined as all subjects with at least 1 STI report following their initial enteric disease episode. A final logistic regression prediction model was chosen using forward stepwise selection. The prediction model with the greatest validity included age, sex, residential location, number of STI episodes experienced prior to the first enteric disease episode, type of enteric disease acquired, and an interaction term between age and male sex. This model had an area under the curve of 0.77 and had acceptable calibration. A coordinated public health response to the sexual transmission of enteric diseases requires that a distinction be made between cases of enteric diseases transmitted through sexual activity from those transmitted through contaminated food or water. A prediction model can aid public health officials in identifying individuals who may have a higher risk of sexually acquiring a reportable disease. Once identified, these individuals could receive specialized intervention to prevent future infection. The information produced from a prediction model capable of identifying higher risk individuals can be used to guide efforts in investigating and controlling reported cases of enteric diseases and STIs. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Improving the forecast for biodiversity under climate change.

PubMed

Urban, M C; Bocedi, G; Hendry, A P; Mihoub, J-B; Pe'er, G; Singer, A; Bridle, J R; Crozier, L G; De Meester, L; Godsoe, W; Gonzalez, A; Hellmann, J J; Holt, R D; Huth, A; Johst, K; Krug, C B; Leadley, P W; Palmer, S C F; Pantel, J H; Schmitz, A; Zollner, P A; Travis, J M J

2016-09-09

New biological models are incorporating the realistic processes underlying biological responses to climate change and other human-caused disturbances. However, these more realistic models require detailed information, which is lacking for most species on Earth. Current monitoring efforts mainly document changes in biodiversity, rather than collecting the mechanistic data needed to predict future changes. We describe and prioritize the biological information needed to inform more realistic projections of species' responses to climate change. We also highlight how trait-based approaches and adaptive modeling can leverage sparse data to make broader predictions. We outline a global effort to collect the data necessary to better understand, anticipate, and reduce the damaging effects of climate change on biodiversity. Copyright © 2016, American Association for the Advancement of Science.

Carotenoid-dependent coloration of male American kestrels predicts ability to reduce parasitic infections

NASA Astrophysics Data System (ADS)

Dawson, Russell D.; Bortolotti, Gary R.

2006-12-01

The signaling function of sexually selected traits, such as carotenoid-dependent avian plumage coloration, has received a great deal of recent attention especially with respect to parasitism and immunocompetence. We argue that parasite-mediated models of sexual selection may have an implicit temporal component that many researchers have ignored. For example, previous studies have demonstrated that carotenoid-dependent traits can signal past parasite exposure, current levels of parasitism, or the ability of individuals to manage parasitic infections in the future. We examined repeated measures of carotenoid-dependent skin color and blood parasitism in American kestrels ( Falco sparverius) to distinguish whether coloration might signal current parasitism or the potential to deal with infections in the future. We found no evidence that coloration was related to current levels of parasitism in either sex. However, coloration of males significantly predicted their response to parasitism; males with bright orange coloration during prelaying, when mate choice is occurring, were more likely than dull yellow males to reduce their levels of infection by the time incubation began. Coloration during prelaying may advertise a male’s health later in the breeding season. For kestrels, the ability to predict future health would be highly beneficial given the male’s role in providing food to his mate and offspring. Coloration of females was not a significant predictor of parasitism in the future, and we provide several possible explanations for this result.

Geometry and mass model of ionizing radiation experiments on the LDEF satellite

NASA Technical Reports Server (NTRS)

Colborn, B. L.; Armstrong, T. W.

1992-01-01

Extensive measurements related to ionizing radiation environments and effects were made on the LDEF satellite during its mission lifetime of almost 6 years. These data, together with the opportunity they provide for evaluating predictive models and analysis methods, should allow more accurate assessments of the space radiation environment and related effects for future missions in low Earth orbit. The LDEF radiation dosimetry data is influenced to varying degrees by material shielding effects due to the dosimeter itself, nearby components and experiments, and the spacecraft structure. A geometry and mass model is generated of LDEF, incorporating sufficient detail that it can be applied in determining the influence of material shielding on ionizing radiation measurements and predictions. This model can be used as an aid in data interpretation by unfolding shielding effects from the LDEF radiation dosimeter responses. Use of the LDEF geometry/mass model, in conjunction with predictions and comparisons with LDEF dosimetry data currently underway, will also allow more definitive evaluations of current radiation models for future mission applications.

Lessons from the Ebola Outbreak: Action Items for Emerging Infectious Disease Preparedness and Response.

PubMed

Jacobsen, Kathryn H; Aguirre, A Alonso; Bailey, Charles L; Baranova, Ancha V; Crooks, Andrew T; Croitoru, Arie; Delamater, Paul L; Gupta, Jhumka; Kehn-Hall, Kylene; Narayanan, Aarthi; Pierobon, Mariaelena; Rowan, Katherine E; Schwebach, J Reid; Seshaiyer, Padmanabhan; Sklarew, Dann M; Stefanidis, Anthony; Agouris, Peggy

2016-03-01

As the Ebola outbreak in West Africa wanes, it is time for the international scientific community to reflect on how to improve the detection of and coordinated response to future epidemics. Our interdisciplinary team identified key lessons learned from the Ebola outbreak that can be clustered into three areas: environmental conditions related to early warning systems, host characteristics related to public health, and agent issues that can be addressed through the laboratory sciences. In particular, we need to increase zoonotic surveillance activities, implement more effective ecological health interventions, expand prediction modeling, support medical and public health systems in order to improve local and international responses to epidemics, improve risk communication, better understand the role of social media in outbreak awareness and response, produce better diagnostic tools, create better therapeutic medications, and design better vaccines. This list highlights research priorities and policy actions the global community can take now to be better prepared for future emerging infectious disease outbreaks that threaten global public health and security.

How Parental Reactions Change in Response to Adolescent Suicide Attempt.

PubMed

Greene-Palmer, Farrah N; Wagner, Barry M; Neely, Laura L; Cox, Daniel W; Kochanski, Kristen M; Perera, Kanchana U; Ghahramanlou-Holloway, Marjan

2015-01-01

This study examined parental reactions to adolescents' suicide attempts and the association of reactions with future suicidal self-directed violence. Participants were 81 mothers and 49 fathers of 85 psychiatric inpatient adolescents. Maternal hostility and paternal anger and arguing predicted future suicide attempts. From pre- to post-attempt, mothers reported feeling increased sadness, caring, anxiety, guilt, fear, and being overwhelmed; fathers reported increased sadness, anxiety, and fear. Findings have clinical implications; improving parent-child relationships post-suicide attempt may serve as a protective factor for suicide.

Interactions of timing and prediction error learning.

PubMed

Kirkpatrick, Kimberly

2014-01-01

Timing and prediction error learning have historically been treated as independent processes, but growing evidence has indicated that they are not orthogonal. Timing emerges at the earliest time point when conditioned responses are observed, and temporal variables modulate prediction error learning in both simple conditioning and cue competition paradigms. In addition, prediction errors, through changes in reward magnitude or value alter timing of behavior. Thus, there appears to be a bi-directional interaction between timing and prediction error learning. Modern theories have attempted to integrate the two processes with mixed success. A neurocomputational approach to theory development is espoused, which draws on neurobiological evidence to guide and constrain computational model development. Heuristics for future model development are presented with the goal of sparking new approaches to theory development in the timing and prediction error fields. Copyright © 2013 Elsevier B.V. All rights reserved.

Neural precursors of future liking and affective reciprocity

PubMed Central

Zerubavel, Noam; Hoffman, Mark Anthony; Reich, Adam; Ochsner, Kevin N.; Bearman, Peter

2018-01-01

Why do certain group members end up liking each other more than others? How does affective reciprocity arise in human groups? The prediction of interpersonal sentiment has been a long-standing pursuit in the social sciences. We combined fMRI and longitudinal social network data to test whether newly acquainted group members’ reward-related neural responses to images of one another’s faces predict their future interpersonal sentiment, even many months later. Specifically, we analyze associations between relationship-specific valuation activity and relationship-specific future liking. We found that one’s own future (T2) liking of a particular group member is predicted jointly by actor’s initial (T1) neural valuation of partner and by that partner’s initial (T1) neural valuation of actor. These actor and partner effects exhibited equivalent predictive strength and were robust when statistically controlling for each other, both individuals’ initial liking, and other potential drivers of liking. Behavioral findings indicated that liking was initially unreciprocated at T1 yet became strongly reciprocated by T2. The emergence of affective reciprocity was partly explained by the reciprocal pathways linking dyad members’ T1 neural data both to their own and to each other’s T2 liking outcomes. These findings elucidate interpersonal brain mechanisms that define how we ultimately end up liking particular interaction partners, how group members’ initially idiosyncratic sentiments become reciprocated, and more broadly, how dyads evolve. This study advances a flexible framework for researching the neural foundations of interpersonal sentiments and social relations that—conceptually, methodologically, and statistically—emphasizes group members’ neural interdependence. PMID:29632195

Neural precursors of future liking and affective reciprocity.

PubMed

Zerubavel, Noam; Hoffman, Mark Anthony; Reich, Adam; Ochsner, Kevin N; Bearman, Peter

2018-04-24

Why do certain group members end up liking each other more than others? How does affective reciprocity arise in human groups? The prediction of interpersonal sentiment has been a long-standing pursuit in the social sciences. We combined fMRI and longitudinal social network data to test whether newly acquainted group members' reward-related neural responses to images of one another's faces predict their future interpersonal sentiment, even many months later. Specifically, we analyze associations between relationship-specific valuation activity and relationship-specific future liking. We found that one's own future (T2) liking of a particular group member is predicted jointly by actor's initial (T1) neural valuation of partner and by that partner's initial (T1) neural valuation of actor. These actor and partner effects exhibited equivalent predictive strength and were robust when statistically controlling for each other, both individuals' initial liking, and other potential drivers of liking. Behavioral findings indicated that liking was initially unreciprocated at T1 yet became strongly reciprocated by T2. The emergence of affective reciprocity was partly explained by the reciprocal pathways linking dyad members' T1 neural data both to their own and to each other's T2 liking outcomes. These findings elucidate interpersonal brain mechanisms that define how we ultimately end up liking particular interaction partners, how group members' initially idiosyncratic sentiments become reciprocated, and more broadly, how dyads evolve. This study advances a flexible framework for researching the neural foundations of interpersonal sentiments and social relations that-conceptually, methodologically, and statistically-emphasizes group members' neural interdependence. Copyright © 2018 the Author(s). Published by PNAS.

Stream Discharge and Evapotranspiration Responses to Climate Change and Their Associated Uncertainties in a Large Semi-Arid Basin

NASA Astrophysics Data System (ADS)

Bassam, S.; Ren, J.

2017-12-01

Predicting future water availability in watersheds is very important for proper water resources management, especially in semi-arid regions with scarce water resources. Hydrological models have been considered as powerful tools in predicting future hydrological conditions in watershed systems in the past two decades. Streamflow and evapotranspiration are the two important components in watershed water balance estimation as the former is the most commonly-used indicator of the overall water budget estimation, and the latter is the second biggest component of water budget (biggest outflow from the system). One of the main concerns in watershed scale hydrological modeling is the uncertainties associated with model prediction, which could arise from errors in model parameters and input meteorological data, or errors in model representation of the physics of hydrological processes. Understanding and quantifying these uncertainties are vital to water resources managers for proper decision making based on model predictions. In this study, we evaluated the impacts of different climate change scenarios on the future stream discharge and evapotranspiration, and their associated uncertainties, throughout a large semi-arid basin using a stochastically-calibrated, physically-based, semi-distributed hydrological model. The results of this study could provide valuable insights in applying hydrological models in large scale watersheds, understanding the associated sensitivity and uncertainties in model parameters, and estimating the corresponding impacts on interested hydrological process variables under different climate change scenarios.

Predicting streamflow response to fire-induced landcover change: implications of parameter uncertainty in the MIKE SHE model.

PubMed

McMichael, Christine E; Hope, Allen S

2007-08-01

Fire is a primary agent of landcover transformation in California semi-arid shrubland watersheds, however few studies have examined the impacts of fire and post-fire succession on streamflow dynamics in these basins. While it may seem intuitive that larger fires will have a greater impact on streamflow response than smaller fires in these watersheds, the nature of these relationships has not been determined. The effects of fire size on seasonal and annual streamflow responses were investigated for a medium-sized basin in central California using a modified version of the MIKE SHE model which had been previously calibrated and tested for this watershed using the Generalized Likelihood Uncertainty Estimation methodology. Model simulations were made for two contrasting periods, wet and dry, in order to assess whether fire size effects varied with weather regime. Results indicated that seasonal and annual streamflow response increased nearly linearly with fire size in a given year under both regimes. Annual flow response was generally higher in wetter years for both weather regimes, however a clear trend was confounded by the effect of stand age. These results expand our understanding of the effects of fire size on hydrologic response in chaparral watersheds, but it is important to note that the majority of model predictions were largely indistinguishable from the predictive uncertainty associated with the calibrated model - a key finding that highlights the importance of analyzing hydrologic predictions for altered landcover conditions in the context of model uncertainty. Future work is needed to examine how alternative decisions (e.g., different likelihood measures) may influence GLUE-based MIKE SHE streamflow predictions following different size fires, and how the effect of fire size on streamflow varies with other factors such as fire location.

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.

Plant water potential improves prediction of empirical stomatal models.

PubMed

Anderegg, William R L; Wolf, Adam; Arango-Velez, Adriana; Choat, Brendan; Chmura, Daniel J; Jansen, Steven; Kolb, Thomas; Li, Shan; Meinzer, Frederick; Pita, Pilar; Resco de Dios, Víctor; Sperry, John S; Wolfe, Brett T; Pacala, Stephen

2017-01-01

Climate change is expected to lead to increases in drought frequency and severity, with deleterious effects on many ecosystems. Stomatal responses to changing environmental conditions form the backbone of all ecosystem models, but are based on empirical relationships and are not well-tested during drought conditions. Here, we use a dataset of 34 woody plant species spanning global forest biomes to examine the effect of leaf water potential on stomatal conductance and test the predictive accuracy of three major stomatal models and a recently proposed model. We find that current leaf-level empirical models have consistent biases of over-prediction of stomatal conductance during dry conditions, particularly at low soil water potentials. Furthermore, the recently proposed stomatal conductance model yields increases in predictive capability compared to current models, and with particular improvement during drought conditions. Our results reveal that including stomatal sensitivity to declining water potential and consequent impairment of plant water transport will improve predictions during drought conditions and show that many biomes contain a diversity of plant stomatal strategies that range from risky to conservative stomatal regulation during water stress. Such improvements in stomatal simulation are greatly needed to help unravel and predict the response of ecosystems to future climate extremes.

Hardware-in-the-Loop Simulation of a Distribution System with Air Conditioners under Model Predictive Control: Preprint

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

Sparn, Bethany F; Ruth, Mark F; Krishnamurthy, Dheepak

Many have proposed that responsive load provided by distributed energy resources (DERs) and demand response (DR) are an option to provide flexibility to the grid and especially to distribution feeders. However, because responsive load involves a complex interplay between tariffs and DER and DR technologies, it is challenging to test and evaluate options without negatively impacting customers. This paper describes a hardware-in-the-loop (HIL) simulation system that has been developed to reduce the cost of evaluating the impact of advanced controllers (e.g., model predictive controllers) and technologies (e.g., responsive appliances). The HIL simulation system combines large-scale software simulation with a smallmore » set of representative building equipment hardware. It is used to perform HIL simulation of a distribution feeder and the loads on it under various tariff structures. In the reported HIL simulation, loads include many simulated air conditioners and one physical air conditioner. Independent model predictive controllers manage operations of all air conditioners under a time-of-use tariff. Results from this HIL simulation and a discussion of future development work of the system are presented.« less

Depressive symptoms predict head and neck cancer survival: Examining plausible behavioral and biological pathways.

PubMed

Zimmaro, Lauren A; Sephton, Sandra E; Siwik, Chelsea J; Phillips, Kala M; Rebholz, Whitney N; Kraemer, Helena C; Giese-Davis, Janine; Wilson, Liz; Bumpous, Jeffrey M; Cash, Elizabeth D

2018-03-01

Head and neck cancers are associated with high rates of depression, which may increase the risk for poorer immediate and long-term outcomes. Here it was hypothesized that greater depressive symptoms would predict earlier mortality, and behavioral (treatment interruption) and biological (treatment response) mediators were examined. Patients (n = 134) reported depressive symptomatology at treatment planning. Clinical data were reviewed at the 2-year follow-up. Greater depressive symptoms were associated with significantly shorter survival (hazard ratio, 0.868; 95% confidence interval [CI], 0.819-0.921; P < .001), higher rates of chemoradiation interruption (odds ratio, 0.865; 95% CI, 0.774-0.966; P = .010), and poorer treatment response (odds ratio, 0.879; 95% CI, 0.803-0.963; P = .005). The poorer treatment response partially explained the depression-survival relation. Other known prognostic indicators did not challenge these results. Depressive symptoms at the time of treatment planning predict overall 2-year mortality. Effects are partly influenced by the treatment response. Depression screening and intervention may be beneficial. Future studies should examine parallel biological pathways linking depression to cancer survival, including endocrine disruption and inflammation. Cancer 2018;124:1053-60. © 2018 American Cancer Society. © 2018 American Cancer Society.

Future Exploration and Utilization of Outer Space

NASA Technical Reports Server (NTRS)

Dryden, H. L.

1960-01-01

The assessment of the future of astronautics is the task of a prophet, a profession not recognized as an established branch of science. Prophecy is an art rather than a profession and there are no established methods of procedure. Knowledge of specific developments in progress and past experience give a reasonable basis for extrapolating a few years ahead. For the more distant future, imagination, intuition, and faith are the only tools, and these are inevitably colored by the nature and environment of the prophet. He may be naturally an optimist or a pessimist. The seeker for financial support and the salesman will see the future very differently than the engineer responsible for the success of launching vehicles on difficult missions. Some of the problems of predicting future developments may be appreciated by looking backward in time by 52 years.

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

PubMed

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

2018-03-14

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

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

USGS Publications Warehouse

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

2018-01-01

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

Predictive systems ecology

PubMed Central

Evans, Matthew R.; Bithell, Mike; Cornell, Stephen J.; Dall, Sasha R. X.; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J.; Lewis, Simon L.; Mace, Georgina M.; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K. J.; Petchey, Owen; Smith, Matthew; Travis, Justin M. J.; Benton, Tim G.

2013-01-01

Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive. PMID:24089332

Predictive systems ecology.

PubMed

Evans, Matthew R; Bithell, Mike; Cornell, Stephen J; Dall, Sasha R X; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J; Lewis, Simon L; Mace, Georgina M; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K J; Petchey, Owen; Smith, Matthew; Travis, Justin M J; Benton, Tim G

2013-11-22

Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

(Q)SARs to predict environmental toxicities: current status and future needs.

PubMed

Cronin, Mark T D

2017-03-22

The current state of the art of (Quantitative) Structure-Activity Relationships ((Q)SARs) to predict environmental toxicity is assessed along with recommendations to develop these models further. The acute toxicity of compounds acting by the non-polar narcotic mechanism of action can be well predicted, however other approaches, including read-across, may be required for compounds acting by specific mechanisms of action. The chronic toxicity of compounds to environmental species is more difficult to predict from (Q)SARs, with robust data sets and more mechanistic information required. In addition, the toxicity of mixtures is little addressed by (Q)SAR approaches. Developments in environmental toxicology including Adverse Outcome Pathways (AOPs) and omics responses should be utilised to develop better, more mechanistically relevant, (Q)SAR models.

Implications of genome-wide association studies in cancer therapeutics.

PubMed

Patel, Jai N; McLeod, Howard L; Innocenti, Federico

2013-09-01

Genome wide association studies (GWAS) provide an agnostic approach to identifying potential genetic variants associated with disease susceptibility, prognosis of survival and/or predictive of drug response. Although these techniques are costly and interpretation of study results is challenging, they do allow for a more unbiased interrogation of the entire genome, resulting in the discovery of novel genes and understanding of novel biological associations. This review will focus on the implications of GWAS in cancer therapy, in particular germ-line mutations, including findings from major GWAS which have identified predictive genetic loci for clinical outcome and/or toxicity. Lessons and challenges in cancer GWAS are also discussed, including the need for functional analysis and replication, as well as future perspectives for biological and clinical utility. Given the large heterogeneity in response to cancer therapeutics, novel methods of identifying mechanisms and biology of variable drug response and ultimately treatment individualization will be indispensable. © 2013 The British Pharmacological Society.

Wind loads on flat plate photovoltaic array fields (nonsteady winds)

NASA Technical Reports Server (NTRS)

Miller, R. D.; Zimmerman, D. K.

1981-01-01

Techniques to predict the dynamic response and the structural dynamic loads of flat plate photovoltaic arrays due to wind turbulence were analyzed. Guidelines for use in predicting the turbulent portion of the wind loading on future similar arrays are presented. The dynamic response and the loads dynamic magnification factor of the two array configurations are similar. The magnification factors at a mid chord and outer chord location on the array illustrated and at four points on the chord are shown. The wind tunnel test experimental rms pressure coefficient on which magnification factors are based is shown. It is found that the largest response and dynamic magnification factor occur at a mid chord location on an array and near the trailing edge. A technique employing these magnification factors and the wind tunnel test rms fluctuating pressure coefficients to calculate design pressure loads due to wind turbulence is presented.

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.

Modelling DC responses of 3D complex fracture networks

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

Beskardes, Gungor Didem; Weiss, Chester Joseph

Here, the determination of the geometrical properties of fractures plays a critical role in many engineering problems to assess the current hydrological and mechanical states of geological media and to predict their future states. However, numerical modeling of geoelectrical responses in realistic fractured media has been challenging due to the explosive computational cost imposed by the explicit discretizations of fractures at multiple length scales, which often brings about a tradeoff between computational efficiency and geologic realism. Here, we use the hierarchical finite element method to model electrostatic response of realistically complex 3D conductive fracture networks with minimal computational cost.

Modelling DC responses of 3D complex fracture networks

DOE PAGES

Beskardes, Gungor Didem; Weiss, Chester Joseph

2018-03-01

Here, the determination of the geometrical properties of fractures plays a critical role in many engineering problems to assess the current hydrological and mechanical states of geological media and to predict their future states. However, numerical modeling of geoelectrical responses in realistic fractured media has been challenging due to the explosive computational cost imposed by the explicit discretizations of fractures at multiple length scales, which often brings about a tradeoff between computational efficiency and geologic realism. Here, we use the hierarchical finite element method to model electrostatic response of realistically complex 3D conductive fracture networks with minimal computational cost.

Thermal and hydrologic responses to climate change predict marked alterations in boreal stream invertebrate assemblages.

PubMed

Mustonen, Kaisa-Riikka; Mykrä, Heikki; Marttila, Hannu; Sarremejane, Romain; Veijalainen, Noora; Sippel, Kalle; Muotka, Timo; Hawkins, Charles P

2018-06-01

Air temperature at the northernmost latitudes is predicted to increase steeply and precipitation to become more variable by the end of the 21st century, resulting in altered thermal and hydrological regimes. We applied five climate scenarios to predict the future (2070-2100) benthic macroinvertebrate assemblages at 239 near-pristine sites across Finland (ca. 1200 km latitudinal span). We used a multitaxon distribution model with air temperature and modeled daily flow as predictors. As expected, projected air temperature increased the most in northernmost Finland. Predicted taxonomic richness also increased the most in northern Finland, congruent with the predicted northwards shift of many species' distributions. Compositional changes were predicted to be high even without changes in richness, suggesting that species replacement may be the main mechanism causing climate-induced changes in macroinvertebrate assemblages. Northern streams were predicted to lose much of the seasonality of their flow regimes, causing potentially marked changes in stream benthic assemblages. Sites with the highest loss of seasonality were predicted to support future assemblages that deviate most in compositional similarity from the present-day assemblages. Macroinvertebrate assemblages were also predicted to change more in headwaters than in larger streams, as headwaters were particularly sensitive to changes in flow patterns. Our results emphasize the importance of focusing protection and mitigation on headwater streams with high-flow seasonality because of their vulnerability to climate change. © 2018 John Wiley & Sons Ltd.

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.

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

The BUMP model of response planning: intermittent predictive control accounts for 10 Hz physiological tremor.

PubMed

Bye, Robin T; Neilson, Peter D

2010-10-01

Physiological tremor during movement is characterized by ∼10 Hz oscillation observed both in the electromyogram activity and in the velocity profile. We propose that this particular rhythm occurs as the direct consequence of a movement response planning system that acts as an intermittent predictive controller operating at discrete intervals of ∼100 ms. The BUMP model of response planning describes such a system. It forms the kernel of Adaptive Model Theory which defines, in computational terms, a basic unit of motor production or BUMP. Each BUMP consists of three processes: (1) analyzing sensory information, (2) planning a desired optimal response, and (3) execution of that response. These processes operate in parallel across successive sequential BUMPs. The response planning process requires a discrete-time interval in which to generate a minimum acceleration trajectory to connect the actual response with the predicted future state of the target and compensate for executional error. We have shown previously that a response planning time of 100 ms accounts for the intermittency observed experimentally in visual tracking studies and for the psychological refractory period observed in double stimulation reaction time studies. We have also shown that simulations of aimed movement, using this same planning interval, reproduce experimentally observed speed-accuracy tradeoffs and movement velocity profiles. Here we show, by means of a simulation study of constant velocity tracking movements, that employing a 100 ms planning interval closely reproduces the measurement discontinuities and power spectra of electromyograms, joint-angles, and angular velocities of physiological tremor reported experimentally. We conclude that intermittent predictive control through sequential operation of BUMPs is a fundamental mechanism of 10 Hz physiological tremor in movement. Copyright © 2010 Elsevier B.V. All rights reserved.

A role for recency of response conflict in producing the bivalency effect.

PubMed

Grundy, John G; Shedden, Judith M

2014-09-01

The bivalency effect is a block-wise response slowing that is observed during task-switching when rare stimuli that cue two tasks (bivalent stimuli) are encountered. This adjustment in response style affects all trials that follow bivalent stimuli, including those trials that do not share any features with bivalent stimuli. However, the specific stimulus and response properties that trigger the bivalency effect are not well understood. In typical bivalency effect experiments, bivalent stimuli can be congruent or incongruent with respect to the response afforded by the irrelevant stimulus feature, and this distinction has never been examined. In the present study, we show that cognitive load defined by the response incongruence on bivalent trials plays a critical role in producing the subsequent response slowing observed in the bivalency effect, as well as maintaining the magnitude of the bivalency effect across practice. We propose that the bivalency effect reflects a process involved in predicting future cognitive load based on recent cognitive load experience. This is in line with a recent proposal for a role of the ACC in monitoring ongoing changes in the environment to optimize future performance (Sheth et al., in Nature 488:218-221, 2012).

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...

Sequencing the fungal tree of life

Treesearch

F. Martin; D. Cullen; D. Hibbett; A. Pisabarro; J.W. Spatafora; S.E. Baker; I.V. Grigoriev

2011-01-01

Terrestrial ecosystems host a complex array of interacting communities, with thousands of species of animals, plants, fungi and bacteria. In soils, this complex web of life is responsible for the cycling of carbon (C), for water and nutrients, for soil quality and for plant nutrition and health. To predict future changes of these threatened ecosystems and to fully...

A Generic Service-Oriented Cost Model for Student Admissions Registration

ERIC Educational Resources Information Center

Pena, Philip Edward

2017-01-01

State support of community colleges has been reduced in recent years and is not expected to recover to previous levels, even though costs continue to rise. While many colleges have increased tuition in response to this situation, students cannot afford endless increases in tuition. While predicting the future is difficult, it is likely that…

Evaluating the sources of potential migrant species: implications under climate change

Treesearch

Ines Ibanez; James S. Clark; Michael C. Dietze

2008-01-01

As changes in climate become more apparent, ecologists face the challenge of predicting species responses to the new conditions. Most forecasts are based on climate envelopes (CE), correlative approaches that project future distributions on the basis of the current climate often assuming some dispersal lag. One major caveat with this approach is that it ignores the...

Estimating potential habitat for 134 eastern US tree species under six climate scenarios

Treesearch

Louis R. Iverson; Anantha M. Prasad; Stephen N. Matthews; Matthew Peters

2008-01-01

We modeled and mapped, using the predictive data mining tool Random Forests, 134 tree species from the eastern United States for potential response to several scenarios of climate change. Each species was modeled individually to show current and potential future habitats according to two emission scenarios (high emissions on current trajectory and reasonable...

Collaborative Research: Process-resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate

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

Cai, Ming; Deng, Yi

2015-02-06

El Niño-Southern Oscillation (ENSO) and Annular Modes (AMs) represent respectively the most important modes of low frequency variability in the tropical and extratropical circulations. The future projection of the ENSO and AM variability, however, remains highly uncertain with the state-of-the-art coupled general circulation models. A comprehensive understanding of the factors responsible for the inter-model discrepancies in projecting future changes in the ENSO and AM variability, in terms of multiple feedback processes involved, has yet to be achieved. The proposed research aims to identify sources of such uncertainty and establish a set of process-resolving quantitative evaluations of the existing predictions ofmore » the future ENSO and AM variability. The proposed process-resolving evaluations are based on a feedback analysis method formulated in Lu and Cai (2009), which is capable of partitioning 3D temperature anomalies/perturbations into components linked to 1) radiation-related thermodynamic processes such as cloud and water vapor feedbacks, 2) local dynamical processes including convection and turbulent/diffusive energy transfer and 3) non-local dynamical processes such as the horizontal energy transport in the oceans and atmosphere. Taking advantage of the high-resolution, multi-model ensemble products from the Coupled Model Intercomparison Project Phase 5 (CMIP5) soon to be available at the Lawrence Livermore National Lab, we will conduct a process-resolving decomposition of the global three-dimensional (3D) temperature (including SST) response to the ENSO and AM variability in the preindustrial, historical and future climate simulated by these models. Specific research tasks include 1) identifying the model-observation discrepancies in the global temperature response to ENSO and AM variability and attributing such discrepancies to specific feedback processes, 2) delineating the influence of anthropogenic radiative forcing on the key feedback processes operating on ENSO and AM variability and quantifying their relative contributions to the changes in the temperature anomalies associated with different phases of ENSO and AMs, and 3) investigating the linkages between model feedback processes that lead to inter-model differences in time-mean temperature projection and model feedback processes that cause inter-model differences in the simulated ENSO and AM temperature response. Through a thorough model-observation and inter-model comparison of the multiple energetic processes associated with ENSO and AM variability, the proposed research serves to identify key uncertainties in model representation of ENSO and AM variability, and investigate how the model uncertainty in predicting time-mean response is related to the uncertainty in predicting response of the low-frequency modes. The proposal is thus a direct response to the first topical area of the solicitation: Interaction of Climate Change and Low Frequency Modes of Natural Climate Variability. It ultimately supports the accomplishment of the BER climate science activity Long Term Measure (LTM): "Deliver improved scientific data and models about the potential response of the Earth's climate and terrestrial biosphere to increased greenhouse gas levels for policy makers to determine safe levels of greenhouse gases in the atmosphere."« less

Predicted persistence and response times of linear and cyclic volatile methylsiloxanes in global and local environments.

PubMed

Kim, Jaeshin; Mackay, Donald; Whelan, Michael John

2018-03-01

We investigated the response times of eight volatile methylsiloxanes (VMSs) in environmental systems at different scales from local to global, with a particular focus on overall loss rates after cessation of emissions. In part, this is driven by proposals to restrict the use of some of these compounds in certain products in Europe. The GloboPOP model estimated low absolute Arctic Contamination Potentials for all VMSs and rapid response times in all media except sediment. VMSs are predicted to be distributed predominantly in air where they react with OH radicals, leading to short response times. After cessation of emissions VMSs concentrations in the environment are expected to decrease rapidly from current levels. Response times in specific water and sediment systems were evaluated using a dynamic QWASI model. Response times were sensitive to both physico-chemical properties and environmental characteristics. Degradation was predicted to play the most important role in determining response times in water and sediment. In the case of the lowest molecular weight VMSs such as L2 and D3, response times were essentially independent of environmental characteristics due to fast hydrolysis in water and sediment. However, response times for the other VMSs are system-specific. They are relatively short in shallow water bodies but increase with depth due to the diminishing role of volatilization on concentration change as volume to surface area ratio increases. In sediment, degradation and resuspension rates also contribute most to the response times. The estimated response times for local environments are useful for planning future monitoring programs. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Bayesian network to predict coastal vulnerability to sea level rise

USGS Publications Warehouse

Gutierrez, B.T.; Plant, N.G.; Thieler, E.R.

2011-01-01

Sea level rise during the 21st century will have a wide range of effects on coastal environments, human development, and infrastructure in coastal areas. The broad range of complex factors influencing coastal systems contributes to large uncertainties in predicting long-term sea level rise impacts. Here we explore and demonstrate the capabilities of a Bayesian network (BN) to predict long-term shoreline change associated with sea level rise and make quantitative assessments of prediction uncertainty. A BN is used to define relationships between driving forces, geologic constraints, and coastal response for the U.S. Atlantic coast that include observations of local rates of relative sea level rise, wave height, tide range, geomorphic classification, coastal slope, and shoreline change rate. The BN is used to make probabilistic predictions of shoreline retreat in response to different future sea level rise rates. Results demonstrate that the probability of shoreline retreat increases with higher rates of sea level rise. Where more specific information is included, the probability of shoreline change increases in a number of cases, indicating more confident predictions. A hindcast evaluation of the BN indicates that the network correctly predicts 71% of the cases. Evaluation of the results using Brier skill and log likelihood ratio scores indicates that the network provides shoreline change predictions that are better than the prior probability. Shoreline change outcomes indicating stability (-1 1 m/yr) was not well predicted. We find that BNs can assimilate important factors contributing to coastal change in response to sea level rise and can make quantitative, probabilistic predictions that can be applied to coastal management decisions. Copyright ?? 2011 by the American Geophysical Union.

Visualization and classification of physiological failure modes in ensemble hemorrhage simulation

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

Continental-Scale Estimates of Runoff Using Future Climate ...

EPA Pesticide Factsheets

Recent runoff events have had serious repercussions to both natural ecosystems and human infrastructure. Understanding how shifts in storm event intensities are expected to change runoff responses are valuable for local, regional, and landscape planning. To address this challenge, relative changes in runoff using predicted future climate conditions were estimated over different biophysical areas for the CONterminous U.S. (CONUS). Runoff was estimated using the Curve Number (CN) developed by the USDA Soil Conservation Service (USDA, 1986). A seamless gridded dataset representing a CN for existing land use/land cover (LULC) across the CONUS was used along with two different storm event grids created specifically for this effort. The two storm event grids represent a 2- and a 100-year, 24-hour storm event under current climate conditions. The storm event grids were generated using a compilation of county-scale Texas USGS Intensity-Duration-Frequency (IDF) data (provided by William Asquith, USGS, Lubbock, Texas), and NOAA Atlas-2 and NOAA Atlas-14 gridded data sets. Future CN runoff was predicted using extreme storm events grids created using a method based on Kao and Ganguly (2011) where precipitation extremes reflect changes in saturated water vapor pressure of the atmosphere in response to temperature changes. The Clausius-Clapeyron relationship establishes that the total water vapor mass of fully saturated air increases with increasing temperature, leading to

Predicting Plant Diversity Patterns in Madagascar: Understanding the Effects of Climate and Land Cover Change in a Biodiversity Hotspot

PubMed Central

Brown, Kerry A.; Parks, Katherine E.; Bethell, Colin A.; Johnson, Steig E.; Mulligan, Mark

2015-01-01

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar’s plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future. PMID:25856241

Predicting plant diversity patterns in Madagascar: understanding the effects of climate and land cover change in a biodiversity hotspot.

PubMed

Brown, Kerry A; Parks, Katherine E; Bethell, Colin A; Johnson, Steig E; Mulligan, Mark

2015-01-01

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar's plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.

Surprise responses in the human brain demonstrate statistical learning under high concurrent cognitive demand

NASA Astrophysics Data System (ADS)

Garrido, Marta Isabel; Teng, Chee Leong James; Taylor, Jeremy Alexander; Rowe, Elise Genevieve; Mattingley, Jason Brett

2016-06-01

The ability to learn about regularities in the environment and to make predictions about future events is fundamental for adaptive behaviour. We have previously shown that people can implicitly encode statistical regularities and detect violations therein, as reflected in neuronal responses to unpredictable events that carry a unique prediction error signature. In the real world, however, learning about regularities will often occur in the context of competing cognitive demands. Here we asked whether learning of statistical regularities is modulated by concurrent cognitive load. We compared electroencephalographic metrics associated with responses to pure-tone sounds with frequencies sampled from narrow or wide Gaussian distributions. We showed that outliers evoked a larger response than those in the centre of the stimulus distribution (i.e., an effect of surprise) and that this difference was greater for physically identical outliers in the narrow than in the broad distribution. These results demonstrate an early neurophysiological marker of the brain's ability to implicitly encode complex statistical structure in the environment. Moreover, we manipulated concurrent cognitive load by having participants perform a visual working memory task while listening to these streams of sounds. We again observed greater prediction error responses in the narrower distribution under both low and high cognitive load. Furthermore, there was no reliable reduction in prediction error magnitude under high-relative to low-cognitive load. Our findings suggest that statistical learning is not a capacity limited process, and that it proceeds automatically even when cognitive resources are taxed by concurrent demands.

The impact of warming on greenhouse gas fluxes: an experimental comparison which reveals the varied response of ecosystems to climate change.

NASA Astrophysics Data System (ADS)

Stockdale, James; Ineson, Philip

2016-04-01

Modelled predictions of the response of terrestrial systems to climate change are highly variable, yet the response of net ecosystem exchange (NEE) is a vital ecosystem behaviour to understand due to its inherent feedback to the carbon cycle. The establishment and subsequent monitoring of replicated experimental manipulations are a direct method to reveal these responses, yet are difficult to achieve as they typically resource-heavy and labour intensive. We actively manipulated the temperature at three agricultural grasslands in southern England and deployed novel 'SkyLine' systems, recently developed at the University of York, to continuously monitor GHG fluxes. Each 'SkyLine' is a low-cost and fully autonomous technology yet produces fluxes at a near-continuous temporal frequency and across a wide spatial area. The results produced by 'SkyLine' enable the detail response of each system to increased temperature over diurnal and seasonal timescales. Unexpected differences in NEE are shown between superficially similar ecosystems which, upon investigation, suggest that interactions between a variety of environmental variables are key and that knowledge of pre-existing environmental conditions help to predict a systems response to future climate. For example, the prevailing hydrological conditions at each site appear to affect its response to changing temperature. The high-frequency data shown here, combined with the fully-replicated experimental design reveal complex interactions which must be understood to improve predictions of ecosystem response to a changing climate.

Testing for local adaptation and evolutionary potential along altitudinal gradients in rainforest Drosophila: beyond laboratory estimates.

PubMed

O'Brien, Eleanor K; Higgie, Megan; Reynolds, Alan; Hoffmann, Ary A; Bridle, Jon R

2017-05-01

Predicting how species will respond to the rapid climatic changes predicted this century is an urgent task. Species distribution models (SDMs) use the current relationship between environmental variation and species' abundances to predict the effect of future environmental change on their distributions. However, two common assumptions of SDMs are likely to be violated in many cases: (i) that the relationship of environment with abundance or fitness is constant throughout a species' range and will remain so in future and (ii) that abiotic factors (e.g. temperature, humidity) determine species' distributions. We test these assumptions by relating field abundance of the rainforest fruit fly Drosophila birchii to ecological change across gradients that include its low and high altitudinal limits. We then test how such ecological variation affects the fitness of 35 D. birchii families transplanted in 591 cages to sites along two altitudinal gradients, to determine whether genetic variation in fitness responses could facilitate future adaptation to environmental change. Overall, field abundance was highest at cooler, high-altitude sites, and declined towards warmer, low-altitude sites. By contrast, cage fitness (productivity) increased towards warmer, lower-altitude sites, suggesting that biotic interactions (absent from cages) drive ecological limits at warmer margins. In addition, the relationship between environmental variation and abundance varied significantly among gradients, indicating divergence in ecological niche across the species' range. However, there was no evidence for local adaptation within gradients, despite greater productivity of high-altitude than low-altitude populations when families were reared under laboratory conditions. Families also responded similarly to transplantation along gradients, providing no evidence for fitness trade-offs that would favour local adaptation. These findings highlight the importance of (i) measuring genetic variation in key traits under ecologically relevant conditions, and (ii) considering the effect of biotic interactions when predicting species' responses to environmental change. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

An Expert System For Multispectral Threat Assessment And Response

NASA Astrophysics Data System (ADS)

Steinberg, Alan N.

1987-05-01

A concept has been defined for an automatic system to manage the self-defense of a combat aircraft. Distinctive new features of this concept include: a. the flexible prioritization of tasks and coordinated use of sensor, countermeasures, flight systems and weapons assets by means of an automated planning function; b. the integration of state-of-the-art data fusion algorithms with event prediction processing; c. the use of advanced Artificial Intelligence tools to emulate the decision processes of tactical EW experts. Threat Assessment functions (a) estimate threat identity, lethality and intent on the basis of multi-spectral sensor data, and (b) predict the time to critical events in threat engagements (e.g., target acquisition, tracking, weapon launch, impact). Response Management functions (a) select candidate responses to reported threat situations; (b) estimate the effects of candidate actions on survival; and (c) coordinate the assignment of sensors, weapons and countermeasures with the flight plan. The system employs Finite State Models to represent current engagements and to predict subsequent events. Each state in a model is associated with a set of observable features, allowing interpretation of sensor data and adaptive use of sensor assets. Defined conditions on state transitions allow prediction of times to critical future states and are used in planning self-defensive responses, which are designed either to impede a particular state transition or to force a transition to a lower threat state.

Dosimetric impact of geometric errors due to respiratory motion prediction on dynamic multileaf collimator-based four-dimensional radiation delivery

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

Vedam, S.; Docef, A.; Fix, M.

2005-06-15

The synchronization of dynamic multileaf collimator (DMLC) response with respiratory motion is critical to ensure the accuracy of DMLC-based four dimensional (4D) radiation delivery. In practice, however, a finite time delay (response time) between the acquisition of tumor position and multileaf collimator response necessitates predictive models of respiratory tumor motion to synchronize radiation delivery. Predicting a complex process such as respiratory motion introduces geometric errors, which have been reported in several publications. However, the dosimetric effect of such errors on 4D radiation delivery has not yet been investigated. Thus, our aim in this work was to quantify the dosimetric effectsmore » of geometric error due to prediction under several different conditions. Conformal and intensity modulated radiation therapy (IMRT) plans for a lung patient were generated for anterior-posterior/posterior-anterior (AP/PA) beam arrangements at 6 and 18 MV energies to provide planned dose distributions. Respiratory motion data was obtained from 60 diaphragm-motion fluoroscopy recordings from five patients. A linear adaptive filter was employed to predict the tumor position. The geometric error of prediction was defined as the absolute difference between predicted and actual positions at each diaphragm position. Distributions of geometric error of prediction were obtained for all of the respiratory motion data. Planned dose distributions were then convolved with distributions for the geometric error of prediction to obtain convolved dose distributions. The dosimetric effect of such geometric errors was determined as a function of several variables: response time (0-0.6 s), beam energy (6/18 MV), treatment delivery (3D/4D), treatment type (conformal/IMRT), beam direction (AP/PA), and breathing training type (free breathing/audio instruction/visual feedback). Dose difference and distance-to-agreement analysis was employed to quantify results. Based on our data, the dosimetric impact of prediction (a) increased with response time, (b) was larger for 3D radiation therapy as compared with 4D radiation therapy, (c) was relatively insensitive to change in beam energy and beam direction, (d) was greater for IMRT distributions as compared with conformal distributions, (e) was smaller than the dosimetric impact of latency, and (f) was greatest for respiration motion with audio instructions, followed by visual feedback and free breathing. Geometric errors of prediction that occur during 4D radiation delivery introduce dosimetric errors that are dependent on several factors, such as response time, treatment-delivery type, and beam energy. Even for relatively small response times of 0.6 s into the future, dosimetric errors due to prediction could approach delivery errors when respiratory motion is not accounted for at all. To reduce the dosimetric impact, better predictive models and/or shorter response times are required.« less

Assessing the impact of future climate extremes on the US corn and soybean production

NASA Astrophysics Data System (ADS)

Jin, Z.

2015-12-01

Future climate changes will place big challenges to the US agricultural system, among which increasing heat stress and precipitation variability were the two major concerns. Reliable prediction of crop productions in response to the increasingly frequent and severe extreme climate is a prerequisite for developing adaptive strategies on agricultural risk management. However, the progress has been slow on quantifying the uncertainty of computational predictions at high spatial resolutions. Here we assessed the risks of future climate extremes on the US corn and soybean production using the Agricultural Production System sIMulator (APSIM) model under different climate scenarios. To quantify the uncertainty due to conceptual representations of heat, drought and flooding stress in crop models, we proposed a new strategy of algorithm ensemble in which different methods for simulating crop responses to those extreme climatic events were incorporated into the APSIM. This strategy allowed us to isolate irrelevant structure differences among existing crop models but only focus on the process of interest. Future climate inputs were derived from high-spatial-resolution (12km × 12km) Weather Research and Forecasting (WRF) simulations under Representative Concentration Pathways 4.5 (RCP 4.5) and 8.5 (RCP 8.5). Based on crop model simulations, we analyzed the magnitude and frequency of heat, drought and flooding stress for the 21st century. We also evaluated the water use efficiency and water deficit on regional scales if farmers were to boost their yield by applying more fertilizers. Finally we proposed spatially explicit adaptation strategies of irrigation and fertilizing for different management zones.

Biodiversity in marine invertebrate responses to acute warming revealed by a comparative multi-omics approach.

PubMed

Clark, Melody S; Sommer, Ulf; Sihra, Jaspreet K; Thorne, Michael A S; Morley, Simon A; King, Michelle; Viant, Mark R; Peck, Lloyd S

2017-01-01

Understanding species' responses to environmental change underpins our abilities to make predictions on future biodiversity under any range of scenarios. In spite of the huge biodiversity in most ecosystems, a model species approach is often taken in environmental studies. To date, we still do not know how many species we need to study to input into models and inform on ecosystem-level responses to change. In this study, we tested current paradigms on factors setting thermal limits by investigating the acute warming response of six Antarctic marine invertebrates: a crustacean Paraceradocus miersi, a brachiopod Liothyrella uva, two bivalve molluscs, Laternula elliptica, Aequiyoldia eightsii, a gastropod mollusc Marseniopsis mollis and an echinoderm Cucumaria georgiana. Each species was warmed at the rate of 1 °C h -1 and taken to the same physiological end point (just prior to heat coma). Their molecular responses were evaluated using complementary metabolomics and transcriptomics approaches with the aim of discovering the underlying mechanisms of their resilience or sensitivity to warming. The responses were species-specific; only two showed accumulation of anaerobic end products and three exhibited the classical heat shock response with expression of HSP70 transcripts. These diverse cellular measures did not directly correlate with resilience to heat stress and suggested that each species may have a different critical point of failure. Thus, one unifying molecular mechanism underpinning response to warming could not be assigned, and no overarching paradigm was supported. This biodiversity in response makes future ecosystems predictions extremely challenging, as we clearly need to develop a macrophysiology-type approach to cellular evaluations of the environmental stress response, studying a range of well-rationalized members from different community levels and of different phylogenetic origins rather than extrapolating from one or two arbitrary model species. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Current versus future reproduction and longevity: a re-evaluation of predictions and mechanisms.

PubMed

Zhang, Yufeng; Hood, Wendy R

2016-10-15

Oxidative damage is predicted to be a mediator of trade-offs between current reproduction and future reproduction or survival, but most studies fail to support such predictions. We suggest that two factors underlie the equivocal nature of these findings: (1) investigators typically assume a negative linear relationship between current reproduction and future reproduction or survival, even though this is not consistently shown by empirical studies; and (2) studies often fail to target mechanisms that could link interactions between sequential life-history events. Here, we review common patterns of reproduction, focusing on the relationships between reproductive performance, survival and parity in females. Observations in a range of species show that performance between sequential reproductive events can decline, remain consistent or increase. We describe likely bioenergetic consequences of reproduction that could underlie these changes in fitness, including mechanisms that could be responsible for negative effects being ephemeral, persistent or delayed. Finally, we make recommendations for designing future studies. We encourage investigators to carefully consider additional or alternative measures of bioenergetic function in studies of life-history trade-offs. Such measures include reactive oxygen species production, oxidative repair, mitochondrial biogenesis, cell proliferation, mitochondrial DNA mutation and replication error and, importantly, a measure of the respiratory function to determine whether measured differences in bioenergetic state are associated with a change in the energetic capacity of tissues that could feasibly affect future reproduction or lifespan. More careful consideration of the life-history context and bioenergetic variables will improve our understanding of the mechanisms that underlie the life-history patterns of animals. © 2016. Published by The Company of Biologists Ltd.

Current versus future reproduction and longevity: a re-evaluation of predictions and mechanisms

PubMed Central

Zhang, Yufeng

2016-01-01

ABSTRACT Oxidative damage is predicted to be a mediator of trade-offs between current reproduction and future reproduction or survival, but most studies fail to support such predictions. We suggest that two factors underlie the equivocal nature of these findings: (1) investigators typically assume a negative linear relationship between current reproduction and future reproduction or survival, even though this is not consistently shown by empirical studies; and (2) studies often fail to target mechanisms that could link interactions between sequential life-history events. Here, we review common patterns of reproduction, focusing on the relationships between reproductive performance, survival and parity in females. Observations in a range of species show that performance between sequential reproductive events can decline, remain consistent or increase. We describe likely bioenergetic consequences of reproduction that could underlie these changes in fitness, including mechanisms that could be responsible for negative effects being ephemeral, persistent or delayed. Finally, we make recommendations for designing future studies. We encourage investigators to carefully consider additional or alternative measures of bioenergetic function in studies of life-history trade-offs. Such measures include reactive oxygen species production, oxidative repair, mitochondrial biogenesis, cell proliferation, mitochondrial DNA mutation and replication error and, importantly, a measure of the respiratory function to determine whether measured differences in bioenergetic state are associated with a change in the energetic capacity of tissues that could feasibly affect future reproduction or lifespan. More careful consideration of the life-history context and bioenergetic variables will improve our understanding of the mechanisms that underlie the life-history patterns of animals. PMID:27802148

Implications of next generation attenuation ground motion prediction equations for site coefficients used in earthquake resistant design

USGS Publications Warehouse

Borcherdt, Roger D.

2014-01-01

Proposals are developed to update Tables 11.4-1 and 11.4-2 of Minimum Design Loads for Buildings and Other Structures published as American Society of Civil Engineers Structural Engineering Institute standard 7-10 (ASCE/SEI 7–10). The updates are mean next generation attenuation (NGA) site coefficients inferred directly from the four NGA ground motion prediction equations used to derive the maximum considered earthquake response maps adopted in ASCE/SEI 7–10. Proposals include the recommendation to use straight-line interpolation to infer site coefficients at intermediate values of (average shear velocity to 30-m depth). The NGA coefficients are shown to agree well with adopted site coefficients at low levels of input motion (0.1 g) and those observed from the Loma Prieta earthquake. For higher levels of input motion, the majority of the adopted values are within the 95% epistemic-uncertainty limits implied by the NGA estimates with the exceptions being the mid-period site coefficient, Fv, for site class D and the short-period coefficient, Fa, for site class C, both of which are slightly less than the corresponding 95% limit. The NGA data base shows that the median value  of 913 m/s for site class B is more typical than 760 m/s as a value to characterize firm to hard rock sites as the uniform ground condition for future maximum considered earthquake response ground motion estimates. Future updates of NGA ground motion prediction equations can be incorporated easily into future adjustments of adopted site coefficients using procedures presented herein. 

Facilitation among plants in alpine environments in the face of climate change.

PubMed

Anthelme, Fabien; Cavieres, Lohengrin A; Dangles, Olivier

2014-01-01

While there is a large consensus that plant-plant interactions are a crucial component of the response of plant communities to the effects of climate change, available data remain scarce, particularly in alpine systems. This represents an important obstacle to making consistent predictions about the future of plant communities. Here, we review current knowledge on the effects of climate change on facilitation among alpine plant communities and propose directions for future research. In established alpine communities, while warming seemingly generates a net facilitation release, earlier snowmelt may increase facilitation. Some nurse plants are able to buffer microenvironmental changes in the long term and may ensure the persistence of other alpine plants through local migration events. For communities migrating to higher elevations, facilitation should play an important role in their reorganization because of the harsher environmental conditions. In particular, the absence of efficient nurse plants might slow down upward migration, possibly generating chains of extinction. Facilitation-climate change relationships are expected to shift along latitudinal gradients because (1) the magnitude of warming is predicted to vary along these gradients, and (2) alpine environments are significantly different at low vs. high latitudes. Data on these expected patterns are preliminary and thus need to be tested with further studies on facilitation among plants in alpine environments that have thus far not been considered. From a methodological standpoint, future studies will benefit from the spatial representation of the microclimatic environment of plants to predict their response to climate change. Moreover, the acquisition of long-term data on the dynamics of plant-plant interactions, either through permanent plots or chronosequences of glacial recession, may represent powerful approaches to clarify the relationship between plant interactions and climate change.

Facilitation among plants in alpine environments in the face of climate change

PubMed Central

Anthelme, Fabien; Cavieres, Lohengrin A.; Dangles, Olivier

2014-01-01

While there is a large consensus that plant–plant interactions are a crucial component of the response of plant communities to the effects of climate change, available data remain scarce, particularly in alpine systems. This represents an important obstacle to making consistent predictions about the future of plant communities. Here, we review current knowledge on the effects of climate change on facilitation among alpine plant communities and propose directions for future research. In established alpine communities, while warming seemingly generates a net facilitation release, earlier snowmelt may increase facilitation. Some nurse plants are able to buffer microenvironmental changes in the long term and may ensure the persistence of other alpine plants through local migration events. For communities migrating to higher elevations, facilitation should play an important role in their reorganization because of the harsher environmental conditions. In particular, the absence of efficient nurse plants might slow down upward migration, possibly generating chains of extinction. Facilitation–climate change relationships are expected to shift along latitudinal gradients because (1) the magnitude of warming is predicted to vary along these gradients, and (2) alpine environments are significantly different at low vs. high latitudes. Data on these expected patterns are preliminary and thus need to be tested with further studies on facilitation among plants in alpine environments that have thus far not been considered. From a methodological standpoint, future studies will benefit from the spatial representation of the microclimatic environment of plants to predict their response to climate change. Moreover, the acquisition of long-term data on the dynamics of plant–plant interactions, either through permanent plots or chronosequences of glacial recession, may represent powerful approaches to clarify the relationship between plant interactions and climate change. PMID:25161660

The development of future-oriented control: an electrophysiological investigation.

PubMed

Waxer, Matthew; Morton, J Bruce

2011-06-01

Cognitive control, or the ability to focus attention and select task-appropriate responses, is not static but can be dynamically adjusted in the face of changing environmental circumstances. Several models suggest a role for conflict-monitoring in triggering these adjustments, whereby instances of response uncertainty are detected by the anterior cingulate cortex and strengthen attention-guiding rules actively maintained by lateral prefrontal cortex. Given the continued development of active maintenance mechanisms into adolescence, these models predict that the capacity to dynamically modulate control should be protracted in its development. The present study tested this prediction by examining age-related differences in behavioral and electrophysiological adaptations to prior conflict. Children, adolescents, and adults were administered the Dimensional Change Card Sort (DCCS; Zelazo, 2006) - a developmentally-appropriate task modified so that response conflict varied from trial to trial - as cortical activity was measured by means of event-related potentials (ERPs). Although all groups showed a robust conflict effect, there were pronounced age-related differences in behavioral and electrophysiological adaptations to prior conflict. First, responses to incongruent trials were faster following incongruent trials than following congruent trials, but only for adults and adolescents. Second, ERP components that indexed response conflict, and the cortical source of these components, were modulated by preceding conflict for adults and adolescents, but not children. Taken together, the findings suggest that adults and adolescents take advantage of prior conflict to prepare for the future, whereas children respond to cognitive challenges as they occur. Theoretical implications are discussed. Copyright © 2011 Elsevier Inc. All rights reserved.

Predicting Health Resilience in Pediatric Type 1 Diabetes: A Test of the Resilience Model Framework

PubMed Central

Huang, Bin; Pendley, Jennifer Shroff; Delamater, Alan; Dolan, Lawrence; Reeves, Grafton; Drotar, Dennis

2015-01-01

Objectives This research examined whether individual and family-level factors during the transition from late childhood to early adolescence protected individuals from an increased risk of poor glycemic control across time, which is a predictor of future diabetes-related complications (i.e., health resilience). Methods This longitudinal, multisite study included 239 patients with type 1 diabetes and their caregivers. Glycemic control was based on hemoglobin A1c. Individual and family-level factors included: demographic variables, youth behavioral regulation, adherence (frequency of blood glucose monitoring), diabetes self-management, level of parental support for diabetes autonomy, level of youth mastery and responsibility for diabetes management, and diabetes-related family conflict. Results Longitudinal mixed-effects logistic regression indicated that testing blood glucose more frequently, better self-management, and less diabetes-related family conflict were indicators of health resilience. Conclusions Multiple individual and family-level factors predicted risk for future health complications. Future research should develop interventions targeting specific individual and family-level factors to sustain glycemic control within recommended targets, which reduces the risk of developing future health complications during the transition to adolescence and adulthood. PMID:26152400

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

NASA Astrophysics Data System (ADS)

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

2004-05-01

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

Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing

PubMed Central

Schoppe, Oliver; King, Andrew J.; Schnupp, Jan W.H.; Harper, Nicol S.

2016-01-01

Adaptation to stimulus statistics, such as the mean level and contrast of recently heard sounds, has been demonstrated at various levels of the auditory pathway. It allows the nervous system to operate over the wide range of intensities and contrasts found in the natural world. Yet current standard models of the response properties of auditory neurons do not incorporate such adaptation. Here we present a model of neural responses in the ferret auditory cortex (the IC Adaptation model), which takes into account adaptation to mean sound level at a lower level of processing: the inferior colliculus (IC). The model performs high-pass filtering with frequency-dependent time constants on the sound spectrogram, followed by half-wave rectification, and passes the output to a standard linear–nonlinear (LN) model. We find that the IC Adaptation model consistently predicts cortical responses better than the standard LN model for a range of synthetic and natural stimuli. The IC Adaptation model introduces no extra free parameters, so it improves predictions without sacrificing parsimony. Furthermore, the time constants of adaptation in the IC appear to be matched to the statistics of natural sounds, suggesting that neurons in the auditory midbrain predict the mean level of future sounds and adapt their responses appropriately. SIGNIFICANCE STATEMENT An ability to accurately predict how sensory neurons respond to novel stimuli is critical if we are to fully characterize their response properties. Attempts to model these responses have had a distinguished history, but it has proven difficult to improve their predictive power significantly beyond that of simple, mostly linear receptive field models. Here we show that auditory cortex receptive field models benefit from a nonlinear preprocessing stage that replicates known adaptation properties of the auditory midbrain. This improves their predictive power across a wide range of stimuli but keeps model complexity low as it introduces no new free parameters. Incorporating the adaptive coding properties of neurons will likely improve receptive field models in other sensory modalities too. PMID:26758822

Characterizing the Response of Composite Panels to a Pyroshock Induced Environment Using Design of Experiments Methodology

NASA Technical Reports Server (NTRS)

Parsons, David S.; Ordway, David; Johnson, Kenneth

2013-01-01

This experimental study seeks to quantify the impact various composite parameters have on the structural response of a composite structure in a pyroshock environment. The prediction of an aerospace structure's response to pyroshock induced loading is largely dependent on empirical databases created from collections of development and flight test data. While there is significant structural response data due to pyroshock induced loading for metallic structures, there is much less data available for composite structures. One challenge of developing a composite pyroshock response database as well as empirical prediction methods for composite structures is the large number of parameters associated with composite materials. This experimental study uses data from a test series planned using design of experiments (DOE) methods. Statistical analysis methods are then used to identify which composite material parameters most greatly influence a flat composite panel's structural response to pyroshock induced loading. The parameters considered are panel thickness, type of ply, ply orientation, and pyroshock level induced into the panel. The results of this test will aid in future large scale testing by eliminating insignificant parameters as well as aid in the development of empirical scaling methods for composite structures' response to pyroshock induced loading.

Characterizing the Response of Composite Panels to a Pyroshock Induced Environment using Design of Experiments Methodology

NASA Technical Reports Server (NTRS)

Parsons, David S.; Ordway, David O.; Johnson, Kenneth L.

2013-01-01

This experimental study seeks to quantify the impact various composite parameters have on the structural response of a composite structure in a pyroshock environment. The prediction of an aerospace structure's response to pyroshock induced loading is largely dependent on empirical databases created from collections of development and flight test data. While there is significant structural response data due to pyroshock induced loading for metallic structures, there is much less data available for composite structures. One challenge of developing a composite pyroshock response database as well as empirical prediction methods for composite structures is the large number of parameters associated with composite materials. This experimental study uses data from a test series planned using design of experiments (DOE) methods. Statistical analysis methods are then used to identify which composite material parameters most greatly influence a flat composite panel's structural response to pyroshock induced loading. The parameters considered are panel thickness, type of ply, ply orientation, and pyroshock level induced into the panel. The results of this test will aid in future large scale testing by eliminating insignificant parameters as well as aid in the development of empirical scaling methods for composite structures' response to pyroshock induced loading.

Older parents are less responsive to a stressor in a long-lived seabird: a mechanism for increased reproductive performance with age?

PubMed

Heidinger, Britt J; Nisbet, Ian C T; Ketterson, Ellen D

2006-09-07

In many taxa, reproductive performance increases throughout the lifespan and this may occur in part because older adults invest more in reproduction. The mechanisms that facilitate an increase in reproductive performance with age, however, are poorly understood. In response to stressors, vertebrates release glucocorticoids, which enhance survival but concurrently shift investment away from reproduction. Consequently, when the value of current reproduction is high relative to the value of future reproduction and survival, as it is in older adults, life history theory predicts that the stress response should be suppressed. In this study, we tested the hypothesis that older parents would respond less strongly to a stressor in a natural, breeding population of common terns (Sterna hirundo). Common terns are long-lived seabirds and reproductive performance is known to increase throughout the lifespan of this species. As predicted, the maximum level of glucocorticoids released in response to handling stress decreased significantly with age. We suggest that suppression of the stress response may be an important physiological mechanism that facilitates an increase in reproductive performance with age.

Projected effects of Climate-change-induced flow alterations on stream macroinvertebrate abundances.

PubMed

Kakouei, Karan; Kiesel, Jens; Domisch, Sami; Irving, Katie S; Jähnig, Sonja C; Kail, Jochem

2018-03-01

Global change has the potential to affect river flow conditions which are fundamental determinants of physical habitats. Predictions of the effects of flow alterations on aquatic biota have mostly been assessed based on species ecological traits (e.g., current preferences), which are difficult to link to quantitative discharge data. Alternatively, we used empirically derived predictive relationships for species' response to flow to assess the effect of flow alterations due to climate change in two contrasting central European river catchments. Predictive relationships were set up for 294 individual species based on (1) abundance data from 223 sampling sites in the Kinzig lower-mountainous catchment and 67 sites in the Treene lowland catchment, and (2) flow conditions at these sites described by five flow metrics quantifying the duration, frequency, magnitude, timing and rate of flow events using present-day gauging data. Species' abundances were predicted for three periods: (1) baseline (1998-2017), (2) horizon 2050 (2046-2065) and (3) horizon 2090 (2080-2099) based on these empirical relationships and using high-resolution modeled discharge data for the present and future climate conditions. We compared the differences in predicted abundances among periods for individual species at each site, where the percent change served as a proxy to assess the potential species responses to flow alterations. Climate change was predicted to most strongly affect the low-flow conditions, leading to decreased abundances of species up to -42%. Finally combining the response of all species over all metrics indicated increasing overall species assemblage responses in 98% of the studied river reaches in both projected horizons and were significantly larger in the lower-mountainous Kinzig compared to the lowland Treene catchment. Such quantitative analyses of freshwater taxa responses to flow alterations provide valuable tools for predicting potential climate-change impacts on species abundances and can be applied to any stressor, species, or region.

On-Line, Self-Learning, Predictive Tool for Determining Payload Thermal Response

NASA Technical Reports Server (NTRS)

Jen, Chian-Li; Tilwick, Leon

2000-01-01

This paper will present the results of a joint ManTech / Goddard R&D effort, currently under way, to develop and test a computer based, on-line, predictive simulation model for use by facility operators to predict the thermal response of a payload during thermal vacuum testing. Thermal response was identified as an area that could benefit from the algorithms developed by Dr. Jeri for complex computer simulations. Most thermal vacuum test setups are unique since no two payloads have the same thermal properties. This requires that the operators depend on their past experiences to conduct the test which requires time for them to learn how the payload responds while at the same time limiting any risk of exceeding hot or cold temperature limits. The predictive tool being developed is intended to be used with the new Thermal Vacuum Data System (TVDS) developed at Goddard for the Thermal Vacuum Test Operations group. This model can learn the thermal response of the payload by reading a few data points from the TVDS, accepting the payload's current temperature as the initial condition for prediction. The model can then be used as a predictive tool to estimate the future payload temperatures according to a predetermined shroud temperature profile. If the error of prediction is too big, the model can be asked to re-learn the new situation on-line in real-time and give a new prediction. Based on some preliminary tests, we feel this predictive model can forecast the payload temperature of the entire test cycle within 5 degrees Celsius after it has learned 3 times during the beginning of the test. The tool will allow the operator to play "what-if' experiments to decide what is his best shroud temperature set-point control strategy. This tool will save money by minimizing guess work and optimizing transitions as well as making the testing process safer and easier to conduct.

Climate change and the distribution and conservation of the world's highest elevation woodlands in the South American Altiplano

NASA Astrophysics Data System (ADS)

Cuyckens, G. A. E.; Christie, D. A.; Domic, A. I.; Malizia, L. R.; Renison, D.

2016-02-01

Climate change is becoming an increasing threat to biodiversity. Consequently, methods for delineation, establishment and management of protected areas must consider the species' future distribution in response to future climate conditions. Biodiversity in high altitude semiarid regions may be particularly threatened by future climate change. In this study we assess the main environmental variables that best explain present day presence of the world's highest elevation woodlands in the South American Altiplano, and model how climate change may affect the future distribution of this unique ecosystem under different climate change scenarios. These woodlands are dominated by Polylepis tarapacana (Rosaceae), a species that forms unique biological communities with important conservation value. Our results indicate that five environmental variables are responsible for 91% and 90.3% of the present and future P. tarapacana distribution models respectively, and suggest that at the end of the 21st century, there will be a significant reduction (56%) in the potential habitat for this species due to more arid conditions. Since it is predicted that P. tarapacana's potential distribution will be severely reduced in the future, we propose a new network of national protected areas across this species distribution range in order to insure the future conservation of this unique ecosystem. Based on an extensive literature review we identify research topics and recommendations for on-ground conservation and management of P. tarapacana woodlands.

Stability and change: Stress responses and the shaping of behavioral phenotypes over the life span.

PubMed

Hennessy, Michael B; Kaiser, Sylvia; Tiedtke, Tobias; Sachser, Norbert

2015-01-01

In mammals, maternal signals conveyed via influences on hypothalamic-pituitary-adrenal (HPA) activity may shape behavior of the young to be better adapted for prevailing environmental conditions. However, the mother's influence extends beyond classic stress response systems. In guinea pigs, several hours (h) of separation from the mother activates not only the HPA axis, but also the innate immune system, which effects immediate behavioral change, as well as modifies behavioral responsiveness in the future. Moreover, the presence of the mother potently suppresses the behavioral consequences of this innate immune activation. These findings raise the possibility that long-term adaptive behavioral change can be mediated by the mother's influence on immune-related activity of her pups. Furthermore, the impact of social partners on physiological stress responses and their behavioral outcomes are not limited to the infantile period. A particularly crucial period for social development in male guinea pigs is that surrounding the attainment of sexual maturation. At this time, social interactions with adults can dramatically affect circulating cortisol concentrations and social behavior in ways that appear to prepare the male to best cope in its likely future social environment. Despite such multiple social influences on the behavior of guinea pigs at different ages, inter-individual differences in the magnitude of the cortisol response remain surprisingly stable over most of the life span. Together, it appears that throughout the life span, physiological stress responses may be regulated by social stimuli. These influences are hypothesized to adjust behavior for predicted environmental conditions. In addition, stable individual differences might provide a means of facilitating adaptation to less predictable conditions.

Prediction and perception of hazards in professional drivers: Does hazard perception skill differ between safe and less-safe fire-appliance drivers?

PubMed

Crundall, David; Kroll, Victoria

2018-05-18

Can hazard perception testing be useful for the emergency services? Previous research has found emergency response drivers' (ERDs) to perform better than controls, however these studies used clips of normal driving. In contrast, the current study filmed footage from a fire-appliance on blue-light training runs through Nottinghamshire, and endeavoured to discriminate between different groups of EDRs based on experience and collision risk. Thirty clips were selected to create two variants of the hazard perception test: a traditional push-button test requiring speeded-responses to hazards, and a prediction test that occludes at hazard onset and provides four possible outcomes for participants to choose between. Three groups of fire-appliance drivers (novices, low-risk experienced and high-risk experienced), and age-matched controls undertook both tests. The hazard perception test only discriminated between controls and all FA drivers, whereas the hazard prediction test was more sensitive, discriminating between high and low-risk experienced fire appliance drivers. Eye movement analyses suggest that the low-risk drivers were better at prioritising the hazardous precursors, leading to better predictive accuracy. These results pave the way for future assessment and training tools to supplement emergency response driver training, while supporting the growing literature that identifies hazard prediction as a more robust measure of driver safety than traditional hazard perception tests. Copyright © 2018 Elsevier Ltd. All rights reserved.

Implementation and extension of the impulse transfer function method for future application to the space shuttle project. Volume 2: Program description and user's guide

NASA Technical Reports Server (NTRS)

Patterson, G.

1973-01-01

The data processing procedures and the computer programs were developed to predict structural responses using the Impulse Transfer Function (ITF) method. There are three major steps in the process: (1) analog-to-digital (A-D) conversion of the test data to produce Phase I digital tapes (2) processing of the Phase I digital tapes to extract ITF's and storing them in a permanent data bank, and (3) predicting structural responses to a set of applied loads. The analog to digital conversion is performed by a standard package which will be described later in terms of the contents of the resulting Phase I digital tape. Two separate computer programs have been developed to perform the digital processing.

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

PubMed

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

2005-09-01

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

Pareidolias in REM Sleep Behavior Disorder: A Possible Predictive Marker of Lewy Body Diseases?

PubMed

Sasai-Sakuma, Taeko; Nishio, Yoshiyuki; Yokoi, Kayoko; Mori, Etsuro; Inoue, Yuichi

2017-02-01

To investigate conditions and clinical significance of pareidolias in patients with idiopathic rapid eyemovent (REM) sleep behavior disorder (iRBD). This cross-sectional study examined 202 patients with iRBD (66.8 ± 8.0 yr, 58 female) and 46 healthy control subjects (64.7 ± 5.8 years, 14 females). They underwent the Pareidolia test, a newly developed instrument for evoking pareidolias, video polysomnography, olfactory tests, and Addenbrooke's cognitive examination-revised. Results show that 53.5% of iRBD patients exhibited one or more pareidolic responses: The rate was higher than control subjects showed (21.7%). The pictures evoking pareidolic responses were more numerous for iRBD patients than for control subjects (1.2 ± 1.8 vs. 0.4 ± 0.8, p < .001). Subgroup analyses revealed that iRBD patients with pareidolic responses had higher amounts of REM sleep without atonia (RWA), with lower sleep efficiency, lower cognitive function, and older age than subjects without pareidolic responses. Results of multivariate analyses show the number of pareidolic responses as a factor associated with decreased cognitive function in iRBD patients with better predictive accuracy. Morbidity length and severity of iRBD, olfactory function, and the amount of RWA were not factors associated with better predictive accuracy. Half or more of the iRBD patients showed pareidolic responses. The responses were proven to be associated more intimately with their cognitive decline than clinical or physiological variables related to RBD. Pareidolias in iRBD are useful as a predictive marker of future development of Lewy body diseases. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Learning predictive statistics from temporal sequences: Dynamics and strategies

PubMed Central

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E.; Kourtzi, Zoe

2017-01-01

Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics—that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments. PMID:28973111

Learning predictive statistics from temporal sequences: Dynamics and strategies.

PubMed

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

2017-10-01

Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics-that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments.

Deciduous forest responses to temperature, precipitation, and drought imply complex climate change impacts.

PubMed

Xie, Yingying; Wang, Xiaojing; Silander, John A

2015-11-03

Changes in spring and autumn phenology of temperate plants in recent decades have become iconic bio-indicators of rapid climate change. These changes have substantial ecological and economic impacts. However, autumn phenology remains surprisingly little studied. Although the effects of unfavorable environmental conditions (e.g., frost, heat, wetness, and drought) on autumn phenology have been observed for over 60 y, how these factors interact to influence autumn phenological events remain poorly understood. Using remotely sensed phenology data from 2001 to 2012, this study identified and quantified significant effects of a suite of environmental factors on the timing of fall dormancy of deciduous forest communities in New England, United States. Cold, frost, and wet conditions, and high heat-stress tended to induce earlier dormancy of deciduous forests, whereas moderate heat- and drought-stress delayed dormancy. Deciduous forests in two eco-regions showed contrasting, nonlinear responses to variation in these explanatory factors. Based on future climate projection over two periods (2041-2050 and 2090-2099), later dormancy dates were predicted in northern areas. However, in coastal areas earlier dormancy dates were predicted. Our models suggest that besides warming in climate change, changes in frost and moisture conditions as well as extreme weather events (e.g., drought- and heat-stress, and flooding), should also be considered in future predictions of autumn phenology in temperate deciduous forests. This study improves our understanding of how multiple environmental variables interact to affect autumn phenology in temperate deciduous forest ecosystems, and points the way to building more mechanistic and predictive models.

Introduction to the special issue on the 2004 Parkfield earthquake and the Parkfield earthquake prediction experiment

USGS Publications Warehouse

Harris, R.A.; Arrowsmith, J.R.

2006-01-01

The 28 September 2004 M 6.0 Parkfield earthquake, a long-anticipated event on the San Andreas fault, is the world's best recorded earthquake to date, with state-of-the-art data obtained from geologic, geodetic, seismic, magnetic, and electrical field networks. This has allowed the preearthquake and postearthquake states of the San Andreas fault in this region to be analyzed in detail. Analyses of these data provide views into the San Andreas fault that show a complex geologic history, fault geometry, rheology, and response of the nearby region to the earthquake-induced ground movement. Although aspects of San Andreas fault zone behavior in the Parkfield region can be modeled simply over geological time frames, the Parkfield Earthquake Prediction Experiment and the 2004 Parkfield earthquake indicate that predicting the fine details of future earthquakes is still a challenge. Instead of a deterministic approach, forecasting future damaging behavior, such as that caused by strong ground motions, will likely continue to require probabilistic methods. However, the Parkfield Earthquake Prediction Experiment and the 2004 Parkfield earthquake have provided ample data to understand most of what did occur in 2004, culminating in significant scientific advances.

Prediction of mesothelioma and lung cancer in a cohort of asbestos exposed workers.

PubMed

Gasparrini, Antonio; Pizzo, Anna Maria; Gorini, Giuseppe; Seniori Costantini, Adele; Silvestri, Stefano; Ciapini, Cesare; Innocenti, Andrea; Berry, Geoffrey

2008-01-01

Several papers have reported state-wide projections of mesothelioma deaths, but few have computed these predictions in selected exposed groups. To predict the future deaths attributable to asbestos in a cohort of railway rolling stock workers. The future mortality of the 1,146 living workers has been computed in term of individual probability of dying for three different risks: baseline mortality, lung cancer excess, mesothelioma mortality. Lung cancer mortality attributable to asbestos was calculated assuming the excess risk as stable or with a decrease after a period of time since first exposure. Mesothelioma mortality was based on cumulative exposure and time since first exposure, with the inclusion of a term for clearance of asbestos fibres from the lung. The most likely range of the number of deaths attributable to asbestos in the period 2005-2050 was 15-30 for excess of lung cancer, and 23-35 for mesothelioma. This study provides predictions of asbestos-related mortality even in a selected cohort of exposed subjects, using previous knowledge about exposure-response relationship. The inclusion of individual information in the projection model helps reduce misclassification and improves the results. The method could be extended in other selected cohorts.

Relationship between BOLD amplitude and pattern classification of orientation-selective activity in the human visual cortex.

PubMed

Tong, Frank; Harrison, Stephenie A; Dewey, John A; Kamitani, Yukiyasu

2012-11-15

Orientation-selective responses can be decoded from fMRI activity patterns in the human visual cortex, using multivariate pattern analysis (MVPA). To what extent do these feature-selective activity patterns depend on the strength and quality of the sensory input, and might the reliability of these activity patterns be predicted by the gross amplitude of the stimulus-driven BOLD response? Observers viewed oriented gratings that varied in luminance contrast (4, 20 or 100%) or spatial frequency (0.25, 1.0 or 4.0 cpd). As predicted, activity patterns in early visual areas led to better discrimination of orientations presented at high than low contrast, with greater effects of contrast found in area V1 than in V3. A second experiment revealed generally better decoding of orientations at low or moderate as compared to high spatial frequencies. Interestingly however, V1 exhibited a relative advantage at discriminating high spatial frequency orientations, consistent with the finer scale of representation in the primary visual cortex. In both experiments, the reliability of these orientation-selective activity patterns was well predicted by the average BOLD amplitude in each region of interest, as indicated by correlation analyses, as well as decoding applied to a simple model of voxel responses to simulated orientation columns. Moreover, individual differences in decoding accuracy could be predicted by the signal-to-noise ratio of an individual's BOLD response. Our results indicate that decoding accuracy can be well predicted by incorporating the amplitude of the BOLD response into simple simulation models of cortical selectivity; such models could prove useful in future applications of fMRI pattern classification. Copyright © 2012 Elsevier Inc. All rights reserved.

Relationship between BOLD amplitude and pattern classification of orientation-selective activity in the human visual cortex

PubMed Central

Tong, Frank; Harrison, Stephenie A.; Dewey, John A.; Kamitani, Yukiyasu

2012-01-01

Orientation-selective responses can be decoded from fMRI activity patterns in the human visual cortex, using multivariate pattern analysis (MVPA). To what extent do these feature-selective activity patterns depend on the strength and quality of the sensory input, and might the reliability of these activity patterns be predicted by the gross amplitude of the stimulus-driven BOLD response? Observers viewed oriented gratings that varied in luminance contrast (4, 20 or 100%) or spatial frequency (0.25, 1.0 or 4.0 cpd). As predicted, activity patterns in early visual areas led to better discrimination of orientations presented at high than low contrast, with greater effects of contrast found in area V1 than in V3. A second experiment revealed generally better decoding of orientations at low or moderate as compared to high spatial frequencies. Interestingly however, V1 exhibited a relative advantage at discriminating high spatial frequency orientations, consistent with the finer scale of representation in the primary visual cortex. In both experiments, the reliability of these orientation-selective activity patterns was well predicted by the average BOLD amplitude in each region of interest, as indicated by correlation analyses, as well as decoding applied to a simple model of voxel responses to simulated orientation columns. Moreover, individual differences in decoding accuracy could be predicted by the signal-to-noise ratio of an individual's BOLD response. Our results indicate that decoding accuracy can be well predicted by incorporating the amplitude of the BOLD response into simple simulation models of cortical selectivity; such models could prove useful in future applications of fMRI pattern classification. PMID:22917989

Acute stress responses: A review and synthesis of ASD, ASR, and CSR.

PubMed

Isserlin, Leanna; Zerach, Gadi; Solomon, Zahava

2008-10-01

Toward the development of a unifying diagnosis for acute stress responses this article attempts to find a place for combat stress reaction (CSR) within the spectrum of other defined acute stress responses. This article critically compares the diagnostic criteria of acute stress disorder (ASD), acute stress reaction (ASR), and CSR. Prospective studies concerning the predictive value of ASD, ASR, and CSR are reviewed. Questions, recommendations, and implications for clinical practice are raised concerning the completeness of the current acute stress response diagnoses, the heterogeneity of different stressors, the scope of expected outcomes, and the importance of decline in function as an indicator of future psychological, psychiatric, and somatic distress. PsycINFO Database Record 2009 APA.

Neural Response to Reward as a Predictor of Rise in Depressive Symptoms in Adolescence

PubMed Central

Morgan, Judith K.; Olino, Thomas M.; McMakin, Dana L.; Ryan, Neal D.; Forbes, Erika E.

2012-01-01

Adolescence is a developmental period characterized by significant increases in the onset of depression, but also by increases in depressive symptoms, even among psychiatrically healthy youth. Disrupted reward function has been postulated as a critical factor in the development of depression, but it is still unclear which adolescents are particularly at risk for rising depressive symptoms. We provide a conceptual stance on gender, pubertal development, and reward type as potential moderators of the association between neural response to reward and rises in depressive symptoms. In addition, we describe preliminary findings that support claims of this conceptual stance. We propose that (1) status-related rewards may be particularly salient for eliciting neural response relevant to depressive symptoms in boys, whereas social rewards may be more salient for eliciting neural response relevant to depressive symptoms in girls and (2) the pattern of reduced striatal response and enhanced medial prefrontal response to reward may be particularly predictive of depressive symptoms in pubertal adolescents. We found that greater vmPFC activation when winning rewards predicted greater increases in depressive symptoms over two years, for boys only, and less striatal activation when anticipating rewards predicted greater increases in depressive symptoms over two years, for adolescents in mid to late pubertal stages but not those in pre to early puberty. We also propose directions for future studies, including the investigation of social vs. monetary reward directly and the longitudinal assessment of parallel changes in pubertal development, neural response to reward, and depressive symptoms. PMID:22521464

The fate of threatened coastal dune habitats in Italy under climate change scenarios.

PubMed

Prisco, Irene; Carboni, Marta; Acosta, Alicia T R

2013-01-01

Coastal dunes worldwide harbor threatened habitats characterized by high diversity in terms of plant communities. In Italy, recent assessments have highlighted the insufficient state of conservation of these habitats as defined by the EU Habitats Directive. The effects of predicted climate change could have dramatic consequences for coastal environments in the near future. An assessment of the efficacy of protection measures under climate change is thus a priority. Here, we have developed environmental envelope models for the most widespread dune habitats in Italy, following two complementary approaches: an "indirect" plant-species-based one and a simple "direct" one. We analyzed how habitats distribution will be altered under the effects of two climate change scenarios and evaluated if the current Italian network of protected areas will be effective in the future after distribution shifts. While modeling dune habitats with the "direct" approach was unsatisfactory, "indirect" models had a good predictive performance, highlighting the importance of using species' responses to climate change for modeling these habitats. The results showed that habitats closer to the sea may even increase their geographical distribution in the near future. The transition dune habitat is projected to remain stable, although mobile and fixed dune habitats are projected to lose most of their actual geographical distribution, the latter being more sensitive to climate change effects. Gap analysis highlighted that the habitats' distribution is currently adequately covered by protected areas, achieving the conservation target. However, according to predictions, protection level for mobile and fixed dune habitats is predicted to drop drastically under the climate change scenarios which we examined. Our results provide useful insights for setting management priorities and better addressing conservation efforts to preserve these threatened habitats in future.

The Fate of Threatened Coastal Dune Habitats in Italy under Climate Change Scenarios

PubMed Central

Prisco, Irene; Carboni, Marta; Acosta, Alicia T. R.

2013-01-01

Coastal dunes worldwide harbor threatened habitats characterized by high diversity in terms of plant communities. In Italy, recent assessments have highlighted the insufficient state of conservation of these habitats as defined by the EU Habitats Directive. The effects of predicted climate change could have dramatic consequences for coastal environments in the near future. An assessment of the efficacy of protection measures under climate change is thus a priority. Here, we have developed environmental envelope models for the most widespread dune habitats in Italy, following two complementary approaches: an “indirect” plant-species-based one and a simple “direct” one. We analyzed how habitats distribution will be altered under the effects of two climate change scenarios and evaluated if the current Italian network of protected areas will be effective in the future after distribution shifts. While modeling dune habitats with the “direct” approach was unsatisfactory, “indirect” models had a good predictive performance, highlighting the importance of using species’ responses to climate change for modeling these habitats. The results showed that habitats closer to the sea may even increase their geographical distribution in the near future. The transition dune habitat is projected to remain stable, although mobile and fixed dune habitats are projected to lose most of their actual geographical distribution, the latter being more sensitive to climate change effects. Gap analysis highlighted that the habitats’ distribution is currently adequately covered by protected areas, achieving the conservation target. However, according to predictions, protection level for mobile and fixed dune habitats is predicted to drop drastically under the climate change scenarios which we examined. Our results provide useful insights for setting management priorities and better addressing conservation efforts to preserve these threatened habitats in future. PMID:23874787

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...

Indiana bat summer maternity distribution: effects of current and future climates

Treesearch

Susan C. Loeb; Eric A. Winters

2013-01-01

Temperate zone bats may be more sensitive to climate change than other groups of mammals because many aspects of their ecology are closely linked to temperature. However, few studies have tried to predict the responses of bats to climate change. The Indiana bat (Myotis sodalis) is a federally listed endangered species that is found in the eastern...

The Effect of Executive Function on Science Achievement among Normally Developing 10-Year Olds

ERIC Educational Resources Information Center

Lederman, Sheri G.

2012-01-01

Executive function (EF) is an umbrella term used to identify a set of discrete but interrelated cognitive abilities that enable individuals to engage in goal-directed, future-oriented action in response to a novel context. Developmental studies indicate that EF is predictive of reading and math achievement in middle childhood. The purpose of this…

Importance of succession, harvest, and climate change in determining future composition in US Central Hardwood Forests

Treesearch

Wen J. Wang; Hong S. He; Frank R. Thompson; Jacob S. Fraser; Brice B. Hanberry; William D. Dijak

2015-01-01

Most temperate forests in U.S. are recovering from heavy exploitation and are in intermediate successional stages where partial tree harvest is the primary disturbance. Changes in regional forest composition in response to climate change are often predicted for plant functional types using biophysical process models. These models usually simplify the simulation of...

Avian community responses to post-fire forest structure: implications for fire management in mixed conifer forests

Treesearch

Angela White; Patricia Manley; Gina Tarbill; T. W. Richardson; R. E. Russell; H. D. Safford; S. Z. Dobrowski

2016-01-01

Fire is a natural process and the dominant disturbance shaping plant and animal communities in many coniferous forests of the western US. Given that fire size and severity are predicted to increase in the future, it has become increasingly important to understand how wildlife responds to fire and post-fire management. The Angora Fire...

Do Magnetic Fields Drive High-Energy Explosive Transients?

NASA Astrophysics Data System (ADS)

Mundell, Carole

2017-10-01

I will review the current state-of-the-art in real-time, rapid response optical imaging and polarimetric followup of transient sources such as Gamma Ray Bursts. I will interpret current results within the context of the external shock model and present predictions for future mm- and cm-wave radio observatories. Recent observational results from new radio pilot studies will also be presented.

A Comparison of Methods to Screen Middle School Students for Reading and Math Difficulties

ERIC Educational Resources Information Center

Nelson, Peter M.; Van Norman, Ethan R.; Lackner, Stacey K.

2016-01-01

The current study explored multiple ways in which middle schools can use and integrate data sources to predict proficiency on future high-stakes state achievement tests. The diagnostic accuracy of (a) prior achievement data, (b) teacher rating scale scores, (c) a composite score combining state test scores and rating scale responses, and (d) two…

Threshold responses to soil moisture deficit by trees and soil in tropical rain forests: insights from field experiments

Treesearch

Patrick Meir; Tana Wood; David R. Galbraith; Paulo M. Brando; Antonio C.I. Da Costa; Lucy Rowland; Leandro V. Ferreira

2015-01-01

Many tropical rain forest regions are at risk of increased future drought. The net effects of drought on forest ecosystem functioning will be substantial if important ecological thresholds are passed. However, understanding and predicting these effects is challenging using observational studies alone. Field-based rainfall exclusion (canopy throughfall exclusion; TFE)...

Attitudinal Responses to Changes in Noise Exposure in Residential Communities

NASA Technical Reports Server (NTRS)

Horonjeff, Richard D.; Robert, William E.

1997-01-01

The purpose of this study is (1) to investigate the current body of knowledge encompassing two related topics: (a) to what extent can we reliably predict the change in people's attitudes in response to an abrupt change in noise exposure, and (b) after the change, is there a decay in the abrupt-change effect whereby people's attitudes slowly shift from their initial reaction to a steady-state value? and (2) to provide recommendations for any future work that may be needed. The literature search located 23 studies relating to one or both of the above topics. These prior studies shed considerable light on the current ability to predict initial reaction and decay effects. The literature makes one point very clear: Great care in both experimental design and data analysis is necessary to produce credible, convincing findings, both in the reanalysis of existing data and for planning future data acquisition and analysis studies. New airport studies must be designed to minimize nuisance variables and avoid past design features that may have introduced sufficient unexplained variance to mask sought after effects. Additionally, the study must be designed to tie in with previous investigations by incorporating similar survey questions and techniques.

General circulation model response to production-limited fossil fuel emission estimates.

NASA Astrophysics Data System (ADS)

Bowman, K. W.; Rutledge, D.; Miller, C.

2008-12-01

The differences in emissions scenarios used to drive IPCC climate projections are the largest sources of uncertainty in future temperature predictions. These estimates are critically dependent on oil, gas, and coal production where the extremal variations in fossil fuel production used in these scenarios is roughly 10:1 after 2100. The development of emission scenarios based on production-limited fossil fuel estimates, i.e., total fossil fuel reserves can be reliably predicted from cumulative production, offers the opportunity to significantly reduce this uncertainty. We present preliminary results of the response of the NASA GISS atmospheric general circulation model to input forcings constrained by production-limited cumulative future fossil-fuel CO2 emissions estimates that reach roughly 500 GtC by 2100, which is significantly lower than any of the IPCC emission scenarios. For climate projections performed from 1958 through 2400 and a climate sensitivity of 5C/2xCO2, the change in globally averaged annual mean temperature relative to fixed CO2 does not exceed 3C with most changes occurring at high latitudes. We find that from 2100-2400 other input forcings such as increased in N2O play an important role in maintaining increase surface temperatures.

Measuring service quality and its relationship to future consumer behavior.

PubMed

Headley, D E; Miller, S J

1993-01-01

The authors adapt the SERVQUAL scale for medical care services and examine it for reliability, dimensionality, and validity in a primary care clinic setting. In addition, they explore the possibility of a link between perceived service quality--and its various dimensions--and a patient's future intent to complain, compliment, repeat purchase, and switch providers. Findings from 159 matched-pair responses indicate that the SERVQUAL scale can be adapted reliably to a clinic setting and that the dimensions of reliability, dependability, and empathy are most predictive of a patient's intent to complain, compliment, repeat purchase, and switch providers.

Evidence base and future research directions in the management of low back pain.

PubMed

Abbott, Allan

2016-03-18

Low back pain (LBP) is a prevalent and costly condition. Awareness of valid and reliable patient history taking, physical examination and clinical testing is important for diagnostic accuracy. Stratified care which targets treatment to patient subgroups based on key characteristics is reliant upon accurate diagnostics. Models of stratified care that can potentially improve treatment effects include prognostic risk profiling for persistent LBP, likely response to specific treatment based on clinical prediction models or suspected underlying causal mechanisms. The focus of this editorial is to highlight current research status and future directions for LBP diagnostics and stratified care.

Microbial models with data-driven parameters predict stronger soil carbon responses to climate change.

PubMed

Hararuk, Oleksandra; Smith, Matthew J; Luo, Yiqi

2015-06-01

Long-term carbon (C) cycle feedbacks to climate depend on the future dynamics of soil organic carbon (SOC). Current models show low predictive accuracy at simulating contemporary SOC pools, which can be improved through parameter estimation. However, major uncertainty remains in global soil responses to climate change, particularly uncertainty in how the activity of soil microbial communities will respond. To date, the role of microbes in SOC dynamics has been implicitly described by decay rate constants in most conventional global carbon cycle models. Explicitly including microbial biomass dynamics into C cycle model formulations has shown potential to improve model predictive performance when assessed against global SOC databases. This study aimed to data-constrained parameters of two soil microbial models, evaluate the improvements in performance of those calibrated models in predicting contemporary carbon stocks, and compare the SOC responses to climate change and their uncertainties between microbial and conventional models. Microbial models with calibrated parameters explained 51% of variability in the observed total SOC, whereas a calibrated conventional model explained 41%. The microbial models, when forced with climate and soil carbon input predictions from the 5th Coupled Model Intercomparison Project (CMIP5), produced stronger soil C responses to 95 years of climate change than any of the 11 CMIP5 models. The calibrated microbial models predicted between 8% (2-pool model) and 11% (4-pool model) soil C losses compared with CMIP5 model projections which ranged from a 7% loss to a 22.6% gain. Lastly, we observed unrealistic oscillatory SOC dynamics in the 2-pool microbial model. The 4-pool model also produced oscillations, but they were less prominent and could be avoided, depending on the parameter values. © 2014 John Wiley & Sons Ltd.

Prediction of lithium response in first-episode mania using the LITHium Intelligent Agent (LITHIA): Pilot data and proof-of-concept.

PubMed

Fleck, David E; Ernest, Nicholas; Adler, Caleb M; Cohen, Kelly; Eliassen, James C; Norris, Matthew; Komoroski, Richard A; Chu, Wen-Jang; Welge, Jeffrey A; Blom, Thomas J; DelBello, Melissa P; Strakowski, Stephen M

2017-06-01

Individualized treatment for bipolar disorder based on neuroimaging treatment targets remains elusive. To address this shortcoming, we developed a linguistic machine learning system based on a cascading genetic fuzzy tree (GFT) design called the LITHium Intelligent Agent (LITHIA). Using multiple objectively defined functional magnetic resonance imaging (fMRI) and proton magnetic resonance spectroscopy ( 1 H-MRS) inputs, we tested whether LITHIA could accurately predict the lithium response in participants with first-episode bipolar mania. We identified 20 subjects with first-episode bipolar mania who received an adequate trial of lithium over 8 weeks and both fMRI and 1 H-MRS scans at baseline pre-treatment. We trained LITHIA using 18 1 H-MRS and 90 fMRI inputs over four training runs to classify treatment response and predict symptom reductions. Each training run contained a randomly selected 80% of the total sample and was followed by a 20% validation run. Over a different randomly selected distribution of the sample, we then compared LITHIA to eight common classification methods. LITHIA demonstrated nearly perfect classification accuracy and was able to predict post-treatment symptom reductions at 8 weeks with at least 88% accuracy in training and 80% accuracy in validation. Moreover, LITHIA exceeded the predictive capacity of the eight comparator methods and showed little tendency towards overfitting. The results provided proof-of-concept that a novel GFT is capable of providing control to a multidimensional bioinformatics problem-namely, prediction of the lithium response-in a pilot data set. Future work on this, and similar machine learning systems, could help assign psychiatric treatments more efficiently, thereby optimizing outcomes and limiting unnecessary treatment. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Micro-RNAs as Potential Predictors of Response to Breast Cancer Systemic Therapy: Future Clinical Implications

PubMed Central

Campos-Parra, Alma D.; Cuamani Mitznahuatl, Gerardo; Pedroza-Torres, Abraham; Vázquez Romo, Rafael; Porras Reyes, Fany Iris; López-Urrutia, Eduardo; Pérez-Plasencia, Carlos

2017-01-01

Despite advances in diagnosis and new treatments such as targeted therapies, breast cancer (BC) is still the most prevalent tumor in women worldwide and the leading cause of death. The principal obstacle for successful BC treatment is the acquired or de novo resistance of the tumors to the systemic therapy (chemotherapy, endocrine, and targeted therapies) that patients receive. In the era of personalized treatment, several studies have focused on the search for biomarkers capable of predicting the response to this therapy; microRNAs (miRNAs) stand out among these markers due to their broad spectrum or potential clinical applications. miRNAs are conserved small non-coding RNAs that act as negative regulators of gene expression playing an important role in several cellular processes, such as cell proliferation, autophagy, genomic stability, and apoptosis. We reviewed recent data that describe the role of miRNAs as potential predictors of response to systemic treatments in BC. Furthermore, upon analyzing the collected published information, we noticed that the overexpression of miR-155, miR-222, miR-125b, and miR-21 predicts the resistance to the most common systemic treatments; nonetheless, the function of these particular miRNAs must be carefully studied and further analyses are still necessary to increase knowledge about their role and future potential clinical uses in BC. PMID:28574440

Micro-RNAs as Potential Predictors of Response to Breast Cancer Systemic Therapy: Future Clinical Implications.

PubMed

Campos-Parra, Alma D; Mitznahuatl, Gerardo Cuamani; Pedroza-Torres, Abraham; Romo, Rafael Vázquez; Reyes, Fany Iris Porras; López-Urrutia, Eduardo; Pérez-Plasencia, Carlos

2017-06-02

Despite advances in diagnosis and new treatments such as targeted therapies, breast cancer (BC) is still the most prevalent tumor in women worldwide and the leading cause of death. The principal obstacle for successful BC treatment is the acquired or de novo resistance of the tumors to the systemic therapy (chemotherapy, endocrine, and targeted therapies) that patients receive. In the era of personalized treatment, several studies have focused on the search for biomarkers capable of predicting the response to this therapy; microRNAs (miRNAs) stand out among these markers due to their broad spectrum or potential clinical applications. miRNAs are conserved small non-coding RNAs that act as negative regulators of gene expression playing an important role in several cellular processes, such as cell proliferation, autophagy, genomic stability, and apoptosis. We reviewed recent data that describe the role of miRNAs as potential predictors of response to systemic treatments in BC. Furthermore, upon analyzing the collected published information, we noticed that the overexpression of miR-155, miR-222, miR-125b, and miR-21 predicts the resistance to the most common systemic treatments; nonetheless, the function of these particular miRNAs must be carefully studied and further analyses are still necessary to increase knowledge about their role and future potential clinical uses in BC.

Anticipative management for coral reef ecosystem services in the 21st century.

PubMed

Rogers, Alice; Harborne, Alastair R; Brown, Christopher J; Bozec, Yves-Marie; Castro, Carolina; Chollett, Iliana; Hock, Karlo; Knowland, Cheryl A; Marshell, Alyssa; Ortiz, Juan C; Razak, Tries; Roff, George; Samper-Villarreal, Jimena; Saunders, Megan I; Wolff, Nicholas H; Mumby, Peter J

2015-02-01

Under projections of global climate change and other stressors, significant changes in the ecology, structure and function of coral reefs are predicted. Current management strategies tend to look to the past to set goals, focusing on halting declines and restoring baseline conditions. Here, we explore a complementary approach to decision making that is based on the anticipation of future changes in ecosystem state, function and services. Reviewing the existing literature and utilizing a scenario planning approach, we explore how the structure of coral reef communities might change in the future in response to global climate change and overfishing. We incorporate uncertainties in our predictions by considering heterogeneity in reef types in relation to structural complexity and primary productivity. We examine 14 ecosystem services provided by reefs, and rate their sensitivity to a range of future scenarios and management options. Our predictions suggest that the efficacy of management is highly dependent on biophysical characteristics and reef state. Reserves are currently widely used and are predicted to remain effective for reefs with high structural complexity. However, when complexity is lost, maximizing service provision requires a broader portfolio of management approaches, including the provision of artificial complexity, coral restoration, fish aggregation devices and herbivore management. Increased use of such management tools will require capacity building and technique refinement and we therefore conclude that diversification of our management toolbox should be considered urgently to prepare for the challenges of managing reefs into the 21st century. © 2014 John Wiley & Sons Ltd.

Assessing spatiotemporal changes in forest carbon turnover times in observational data and models

NASA Astrophysics Data System (ADS)

Yu, K.; Smith, W. K.; Trugman, A. T.; van Mantgem, P.; Peng, C.; Condit, R.; Anderegg, W.

2017-12-01

Forests influence global carbon and water cycles, biophysical land-atmosphere feedbacks, and atmospheric composition. The capacity of forests to sequester atmospheric CO2 in a changing climate depends not only on the response of carbon uptake (i.e., gross primary productivity) but also on the simultaneous change in carbon residence time. However, changes in carbon residence with climate change are uncertain, impacting the accuracy of predictions of future terrestrial carbon cycle dynamics. Here, we use long-term forest inventory data representative of tropical, temperate, and boreal forests; satellite-based estimates of net primary productivity and vegetation carbon stock; and six models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to investigate spatiotemporal trends in carbon residence time and its relation to climate. Forest inventory and satellite-based estimates of carbon residence time show a pervasive decreasing trend across global forests. In contrast, the CMIP5 models diverge in predicting historical and future trends in carbon residence time. Divergence across CMIP5 models indicate carbon turnover times are not well constrained by observations, which likely contributes to large variability in future carbon cycle projections.

Bioinformatic analyses to select phenotype affecting polymorphisms in HTR2C gene.

PubMed

Piva, Francesco; Giulietti, Matteo; Baldelli, Luisa; Nardi, Bernardo; Bellantuono, Cesario; Armeni, Tatiana; Saccucci, Franca; Principato, Giovanni

2011-08-01

Single nucleotide polymorphisms (SNPs) in serotonin related genes influence mental disorders, responses to pharmacological and psychotherapeutic treatments. In planning association studies, researchers that want to investigate new SNPs have to select some among a large number of candidates. Our aim is to guide researchers in the selection of the most likely phenotype affecting polymorphisms. Here, we studied serotonin receptor 2C (HTR2C) SNPs because, till now, only relatively few of about 2000 are investigated. We used the most updated and assessed bioinformatic tools to predict which variations can give rise to biological effects among 2450 HTR2C SNPs. We suggest 48 SNPs that are worth considering in future association studies in the field of psychiatry, psychology and pharmacogenomics. Moreover, our analyses point out the biological level probably affected, such as transcription, splicing, miRNA regulation and protein structure, thus allowing to suggest future molecular investigations. Although few association studies are available in literature, their results are in agreement with our predictions, showing that our selection methods can help to guide future association studies. Copyright © 2011 John Wiley & Sons, Ltd.

Experiments with the living dead: Plants as monitors and recorders of Biosphere Geosphere interactions.

NASA Astrophysics Data System (ADS)

Lomax, Barry; Fraser, Wesley

2016-04-01

Understanding variations in the Earth's climate history will enhance our understanding of and capacity to predict future climate change. Importantly this information can then be used to reduce uncertainty around future climate change predictions. However to achieve this, it is necessary to develop well constrained and robustly tested palaeo-proxies. Plants are innately coupled to the atmosphere requiring both sunlight and CO2 to drive photosynthesis and carbon assimilation. When combined with their resilience and persistence, the study of plant responses to climate change in concert with the analysis of fossil plants offer the opportunity to monitor past atmospheric conditions and infer palaeoclimate change. In this presentation we highlight how this approach is leading to the development of mechanistic palaeoproxies tested on palaeobotanically relevant extant species showing that plant fossils can be used as both monitors and geochemical recorders of atmospheric changes.

Model structures amplify uncertainty in predicted soil carbon responses to climate change.

PubMed

Shi, Zheng; Crowell, Sean; Luo, Yiqi; Moore, Berrien

2018-06-04

Large model uncertainty in projected future soil carbon (C) dynamics has been well documented. However, our understanding of the sources of this uncertainty is limited. Here we quantify the uncertainties arising from model parameters, structures and their interactions, and how those uncertainties propagate through different models to projections of future soil carbon stocks. Both the vertically resolved model and the microbial explicit model project much greater uncertainties to climate change than the conventional soil C model, with both positive and negative C-climate feedbacks, whereas the conventional model consistently predicts positive soil C-climate feedback. Our findings suggest that diverse model structures are necessary to increase confidence in soil C projection. However, the larger uncertainty in the complex models also suggests that we need to strike a balance between model complexity and the need to include diverse model structures in order to forecast soil C dynamics with high confidence and low uncertainty.

Antiangiogenic Therapy for Glioblastoma: Current Status and Future Prospects

PubMed Central

Batchelor, Tracy T.; Reardon, David A.; de Groot, John F.; Wick, Wolfgang; Weller, Michael

2014-01-01

Glioblastoma is characterized by high expression levels of pro-angiogenic cytokines and microvascular proliferation, highlighting the potential value of treatments targeting angiogenesis. Antiangiogenic treatment likely achieves a beneficial impact through multiple mechanisms of action. Ultimately, however, alternative pro-angiogenic signal transduction pathways are activated leading to the development of resistance, even in tumors that initially respond. The identification of biomarkers or imaging parameters to predict response and to herald resistance is of high priority. Despite promising phase 2 clinical trial results and patient benefit in terms of clinical improvement and longer progression-free survival, an overall survival benefit has not been demonstrated in 4 randomized phase 3 trials of bevacizumab or cilengitide in newly diagnosed glioblastoma or cediranib or enzastaurin recurrent glioblastoma. However, future studies are warranted: predictive markers may allow appropriate patient enrichment, combination with chemotherapy may ultimately prove successful in improving overall survival, and novel agents targeting multiple pro-angiogenic pathways may prove effective. PMID:25398844

Who Provides Care? A Prospective Study of Caregiving Among Adult Siblings

PubMed Central

Pillemer, Karl; Suitor, J. Jill

2014-01-01

Purpose: We use data from a longitudinal, within-family study to identify factors that predict which adult siblings assumed caregiving responsibilities to older mothers over a 7-year period. Design and Methods: Data for the study were collected from 139 older mothers at 2 points 7 years apart regarding their expectations and experiences of care from 537 adult children. Results: Children whom mothers identified at T1 as their expected future caregivers were much more likely to provide care when a serious illness occurred. Caregiving offspring were also more likely at T1 to have shared their mothers’ values, lived in proximity, and to be daughters. Implications: The findings indicate the degree to which a mother’s expectations for care predict actual caregiving by that child. Practitioners working with older adults should explore parents’ expectations for future care that involves their adult children. PMID:23840019

The Emergence of Precision Urologic Oncology: A Collaborative Review on Biomarker-driven Therapeutics.

PubMed

Barbieri, Christopher E; Chinnaiyan, Arul M; Lerner, Seth P; Swanton, Charles; Rubin, Mark A

2017-02-01

Biomarker-driven cancer therapy, also referred to as precision oncology, has received increasing attention for its promise of improving patient outcomes by defining subsets of patients more likely to respond to various therapies. In this collaborative review article, we examine recent literature regarding biomarker-driven therapeutics in urologic oncology, to better define the state of the field, explore the current evidence supporting utility of this approach, and gauge potential for the future. We reviewed relevant literature, with a particular focus on recent studies about targeted therapy, predictors of response, and biomarker development. The recent advances in molecular profiling have led to a rapid expansion of potential biomarkers and predictive information for patients with urologic malignancies. Across disease states, distinct molecular subtypes of cancers have been identified, with the potential to inform choices of management strategy. Biomarkers predicting response to standard therapies (such as platinum-based chemotherapy) are emerging. In several malignancies (particularly renal cell carcinoma and castration-resistant prostate cancer), targeted therapy against commonly altered signaling pathways has emerged as standard of care. Finally, targeted therapy against alterations present in rare patients (less than 2%) across diseases has the potential to drastically alter patterns of care and choices of therapeutic options. Precision medicine has the highest potential to impact the care of patients. Prospective studies in the setting of clinical trials and standard of care therapy will help define reliable predictive biomarkers and new therapeutic targets leading to real improvement in patient outcomes. Precision oncology uses molecular information (DNA and RNA) from the individual and the tumor to match the right patient with the right treatment. Tremendous strides have been made in defining the molecular underpinnings of urologic malignancies and understanding how these predict response to treatment-this represents the future of urologic oncology. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

The Emergence of Precision Urologic Oncology: A Collaborative Review on Biomarker-driven Therapeutics

PubMed Central

Barbieri, Christopher E.; Chinnaiyan, Arul M.; Lerner, Seth P.; Swanton, Charles; Rubin, Mark A.

2016-01-01

Context Biomarker-driven cancer therapy, also referred to as precision oncology, has received increasing attention for its promise of improving patient outcomes by defining subsets of patients more likely to respond to various therapies. Objective In this collaborative review article, we examine recent literature regarding biomarker-driven therapeutics in urologic oncology, to better define the state of the field, explore the current evidence supporting utility of this approach, and gauge potential for the future. Evidence acquisition We reviewed relevant literature, with a particular focus on recent studies about targeted therapy, predictors of response, and biomarker development. Evidence synthesis The recent advances in molecular profiling have led to a rapid expansion of potential biomarkers and predictive information for patients with urologic malignancies. Across disease states, distinct molecular subtypes of cancers have been identified, with the potential to inform choices of management strategy. Biomarkers predicting response to standard therapies (such as platinum-based chemotherapy) are emerging. In several malignancies (particularly renal cell carcinoma and castration-resistant prostate cancer), targeted therapy against commonly altered signaling pathways has emerged as standard of care. Finally, targeted therapy against alterations present in rare patients (less than 2%) across diseases has the potential to drastically alter patterns of care and choices of therapeutic options. Conclusions Precision medicine has the highest potential to impact the care of patients. Prospective studies in the setting of clinical trials and standard of care therapy will help define reliable predictive biomarkers and new therapeutic targets leading to real improvement in patient outcomes. Patient summary Precision oncology uses molecular information (DNA and RNA) from the individual and the tumor to match the right patient with the right treatment. Tremendous strides have been made in defining the molecular underpinnings of urologic malignancies and understanding how these predict response to treatment—this represents the future of urologic oncology. PMID:27567210

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

PubMed Central

French, Susannah S.; Brodie, Edmund D.

2017-01-01

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

Emotional arousal and discount rate in intertemporal choice are reference dependent.

PubMed

Lempert, Karolina M; Glimcher, Paul W; Phelps, Elizabeth A

2015-04-01

Many decisions involve weighing immediate gratification against future consequences. In such intertemporal choices, people often choose smaller, immediate rewards over larger delayed rewards. It has been proposed that emotional responses to immediate rewards lead us to choose them at our long-term expense. Here we utilize an objective measure of emotional arousal-pupil dilation-to examine the role of emotion in these decisions. We show that emotional arousal responses, as well as choices, in intertemporal choice tasks are reference-dependent and reflect the decision-maker's recent history of offers. Arousal increases when less predictable rewards are better than expected, whether those rewards are immediate or delayed. Furthermore, when immediate rewards are less predictable than delayed rewards, participants tend to be patient. When delayed rewards are less predictable, immediate rewards are preferred. Our findings suggest that we can encourage people to be more patient by changing the context in which intertemporal choices are made. (c) 2015 APA, all rights reserved).

A Bayesian network to predict vulnerability to sea-level rise: data report

USGS Publications Warehouse

Gutierrez, Benjamin T.; Plant, Nathaniel G.; Thieler, E. Robert

2011-01-01

During the 21st century, sea-level rise is projected to have a wide range of effects on coastal environments, development, and infrastructure. Consequently, there has been an increased focus on developing modeling or other analytical approaches to evaluate potential impacts to inform coastal management. This report provides the data that were used to develop and evaluate the performance of a Bayesian network designed to predict long-term shoreline change due to sea-level rise. The data include local rates of relative sea-level rise, wave height, tide range, geomorphic classification, coastal slope, and shoreline-change rate compiled as part of the U.S. Geological Survey Coastal Vulnerability Index for the U.S. Atlantic coast. In this project, the Bayesian network is used to define relationships among driving forces, geologic constraints, and coastal responses. Using this information, the Bayesian network is used to make probabilistic predictions of shoreline change in response to different future sea-level-rise scenarios.

Evolution and behavioural responses to human-induced rapid environmental change

PubMed Central

Sih, Andrew; Ferrari, Maud C O; Harris, David J

2011-01-01

Almost all organisms live in environments that have been altered, to some degree, by human activities. Because behaviour mediates interactions between an individual and its environment, the ability of organisms to behave appropriately under these new conditions is crucial for determining their immediate success or failure in these modified environments. While hundreds of species are suffering dramatically from these environmental changes, others, such as urbanized and pest species, are doing better than ever. Our goal is to provide insights into explaining such variation. We first summarize the responses of some species to novel situations, including novel risks and resources, habitat loss/fragmentation, pollutants and climate change. Using a sensory ecology approach, we present a mechanistic framework for predicting variation in behavioural responses to environmental change, drawing from models of decision-making processes and an understanding of the selective background against which they evolved. Where immediate behavioural responses are inadequate, learning or evolutionary adaptation may prove useful, although these mechanisms are also constrained by evolutionary history. Although predicting the responses of species to environmental change is difficult, we highlight the need for a better understanding of the role of evolutionary history in shaping individuals’ responses to their environment and provide suggestion for future work. PMID:25567979

Evolution and behavioural responses to human-induced rapid environmental change.

PubMed

Sih, Andrew; Ferrari, Maud C O; Harris, David J

2011-03-01

Almost all organisms live in environments that have been altered, to some degree, by human activities. Because behaviour mediates interactions between an individual and its environment, the ability of organisms to behave appropriately under these new conditions is crucial for determining their immediate success or failure in these modified environments. While hundreds of species are suffering dramatically from these environmental changes, others, such as urbanized and pest species, are doing better than ever. Our goal is to provide insights into explaining such variation. We first summarize the responses of some species to novel situations, including novel risks and resources, habitat loss/fragmentation, pollutants and climate change. Using a sensory ecology approach, we present a mechanistic framework for predicting variation in behavioural responses to environmental change, drawing from models of decision-making processes and an understanding of the selective background against which they evolved. Where immediate behavioural responses are inadequate, learning or evolutionary adaptation may prove useful, although these mechanisms are also constrained by evolutionary history. Although predicting the responses of species to environmental change is difficult, we highlight the need for a better understanding of the role of evolutionary history in shaping individuals' responses to their environment and provide suggestion for future work.

T cell Bim levels reflect responses to anti–PD-1 cancer therapy

PubMed Central

Dronca, Roxana S.; Liu, Xin; Harrington, Susan M.; Chen, Lingling; Cao, Siyu; Kottschade, Lisa A.; McWilliams, Robert R.; Block, Matthew S.; Nevala, Wendy K.; Thompson, Michael A.; Mansfield, Aaron S.; Park, Sean S.; Markovic, Svetomir N.

2016-01-01

Immune checkpoint therapy with PD-1 blockade has emerged as an effective therapy for many advanced cancers; however, only a small fraction of patients achieve durable responses. To date, there is no validated blood-based means of predicting the response to PD-1 blockade. We report that Bim is a downstream signaling molecule of the PD-1 pathway, and its detection in T cells is significantly associated with expression of PD-1 and effector T cell markers. High levels of Bim in circulating tumor-reactive (PD-1+CD11ahiCD8+) T cells were prognostic of poor survival in patients with metastatic melanoma who did not receive anti–PD-1 therapy and were also predictive of clinical benefit in patients with metastatic melanoma who were treated with anti–PD-1 therapy. Moreover, this circulating tumor-reactive T cell population significantly decreased after successful anti–PD-1 therapy. Our study supports a crucial role of Bim in both T cell activation and apoptosis as regulated by PD-1 and PD-L1 interactions in effector CD8+ T cells. Measurement of Bim levels in circulating T cells of patients with cancer may provide a less invasive strategy to predict and monitor responses to anti–PD-1 therapy, although future prospective analyses are needed to validate its utility. PMID:27182556

The Esophagiome: concept, status, and future perspectives.

PubMed

Gregersen, Hans; Liao, Donghua; Brasseur, James G

2016-09-01

The term "Esophagiome" is meant to imply a holistic, multiscale treatment of esophageal function from cellular and muscle physiology to the mechanical responses that transport and mix fluid contents. The development and application of multiscale mathematical models of esophageal function are central to the Esophagiome concept. These model elements underlie the development of a "virtual esophagus" modeling framework to characterize and analyze function and disease by quantitatively contrasting normal and pathophysiological function. Functional models incorporate anatomical details with sensory-motor properties and functional responses, especially related to biomechanical functions, such as bolus transport and gastrointestinal fluid mixing. This brief review provides insight into Esophagiome research. Future advanced models can provide predictive evaluations of the therapeutic consequences of surgical and endoscopic treatments and will aim to facilitate clinical diagnostics and treatment. © 2016 New York Academy of Sciences.

Applying metabolomics to cardiometabolic intervention studies and trials: past experiences and a roadmap for the future.

PubMed

Rankin, Naomi J; Preiss, David; Welsh, Paul; Sattar, Naveed

2016-10-01

Metabolomics and lipidomics are emerging methods for detailed phenotyping of small molecules in samples. It is hoped that such data will: (i) enhance baseline prediction of patient response to pharmacotherapies (beneficial or adverse); (ii) reveal changes in metabolites shortly after initiation of therapy that may predict patient response, including adverse effects, before routine biomarkers are altered; and( iii) give new insights into mechanisms of drug action, particularly where the results of a trial of a new agent were unexpected, and thus help future drug development. In these ways, metabolomics could enhance research findings from intervention studies. This narrative review provides an overview of metabolomics and lipidomics in early clinical intervention studies for investigation of mechanisms of drug action and prediction of drug response (both desired and undesired). We highlight early examples from drug intervention studies associated with cardiometabolic disease. Despite the strengths of such studies, particularly the use of state-of-the-art technologies and advanced statistical methods, currently published studies in the metabolomics arena are largely underpowered and should be considered as hypothesis-generating. In order for metabolomics to meaningfully improve stratified medicine approaches to patient treatment, there is a need for higher quality studies, with better exploitation of biobanks from randomized clinical trials i.e. with large sample size, adjudicated outcomes, standardized procedures, validation cohorts, comparison witth routine biochemistry and both active and control/placebo arms. On the basis of this review, and based on our research experience using clinically established biomarkers, we propose steps to more speedily advance this area of research towards potential clinical impact. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Estimating drought induced tree mortality in the Amazon rainforest: A simulation study with a focus on plant hydraulic processes

NASA Astrophysics Data System (ADS)

Papastefanou, P.; Fleischer, K.; Hickler, T.; Grams, T.; Lapola, D.; Quesada, C. A.; Zang, C.; Rammig, A.

2017-12-01

The Amazon basin was recently hit by severe drought events that were unprecedented in their severity and spatial extent, e.g. during 2005, 2010 and 2015/2016. Significant amounts of biomass were lost, turning large parts of the rainforest from a carbon sink into a carbon source. It is assumed that drought-induced tree mortality from hydraulic failure played an important role during these events and may become more frequent in the Amazon region in the future. Many state-of-the-art dynamic vegetation models do not include plant hydraulic processes and fail to reproduce observed rainforest responses to drought events, such as e.g. increased tree mortality. We address this research gap by developing a simple plant-hydraulic module for the dynamic vegetation model LPJ-GUESS. This plant-hydraulic module uses leaf water potential and cavitation as baseline processes to simulate tree mortality under drought stress. Furthermore, we introduce different plant strategies in the model, which describe e.g. differences in the stomatal regulation under drought stress. To parameterize and evaluate our hydraulic module, we use a set of available observational data from the Amazon region. We apply our model to the Amazon Basin and highlight similarities and differences across other measured and predicted drought responses, e.g. extrapolated observations and data derived from satellite measurements. Our results highlight the importance of including plant hydraulic processes in dynamic vegetation models to correctly predict vegetation dynamics under drought stress and show major differences on the vegetation dynamics depending on the selected plant strategies. We also identify gaps in process understanding of the triggering factors, the extent and the consequences of drought responses that hampers our ability to predict potential impact of future drought events on the Amazon rainforest.

Modeling forest ecosystem responses to elevated carbon dioxide and ozone using artificial neural networks.

PubMed

Larsen, Peter E; Cseke, Leland J; Miller, R Michael; Collart, Frank R

2014-10-21

Rising atmospheric levels of carbon dioxide and ozone will impact productivity and carbon sequestration in forest ecosystems. The scale of this process and the potential economic consequences provide an incentive for the development of models to predict the types and rates of ecosystem responses and feedbacks that result from and influence of climate change. In this paper, we use phenotypic and molecular data derived from the Aspen Free Air CO2 Enrichment site (Aspen-FACE) to evaluate modeling approaches for ecosystem responses to changing conditions. At FACE, it was observed that different aspen clones exhibit clone-specific responses to elevated atmospheric levels of carbon dioxide and ozone. To identify the molecular basis for these observations, we used artificial neural networks (ANN) to examine above and below-ground community phenotype responses to elevated carbon dioxide, elevated ozone and gene expression profiles. The aspen community models generated using this approach identified specific genes and subnetworks of genes associated with variable sensitivities for aspen clones. The ANN model also predicts specific co-regulated gene clusters associated with differential sensitivity to elevated carbon dioxide and ozone in aspen species. The results suggest ANN is an effective approach to predict relevant gene expression changes resulting from environmental perturbation and provides useful information for the rational design of future biological experiments. Copyright © 2014 Elsevier Ltd. All rights reserved.

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach-A Case Study for the City of Wuhan in China.

PubMed

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-06-15

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study-simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.

A predictive framework to understand forest responses to global change.

PubMed

McMahon, Sean M; Dietze, Michael C; Hersh, Michelle H; Moran, Emily V; Clark, James S

2009-04-01

Forests are one of Earth's critical biomes. They have been shown to respond strongly to many of the drivers that are predicted to change natural systems over this century, including climate, introduced species, and other anthropogenic influences. Predicting how different tree species might respond to this complex of forces remains a daunting challenge for forest ecologists. Yet shifts in species composition and abundance can radically influence hydrological and atmospheric systems, plant and animal ranges, and human populations, making this challenge an important one to address. Forest ecologists have gathered a great deal of data over the past decades and are now using novel quantitative and computational tools to translate those data into predictions about the fate of forests. Here, after a brief review of the threats to forests over the next century, one of the more promising approaches to making ecological predictions is described: using hierarchical Bayesian methods to model forest demography and simulating future forests from those models. This approach captures complex processes, such as seed dispersal and mortality, and incorporates uncertainty due to unknown mechanisms, data problems, and parameter uncertainty. After describing the approach, an example by simulating drought for a southeastern forest is offered. Finally, there is a discussion of how this approach and others need to be cast within a framework of prediction that strives to answer the important questions posed to environmental scientists, but does so with a respect for the challenges inherent in predicting the future of a complex biological system.

Determining the response of African biota to climate change: using the past to model the future.

PubMed

Willis, K J; Bennett, K D; Burrough, S L; Macias-Fauria, M; Tovar, C

2013-01-01

Prediction of biotic responses to future climate change in tropical Africa tends to be based on two modelling approaches: bioclimatic species envelope models and dynamic vegetation models. Another complementary but underused approach is to examine biotic responses to similar climatic changes in the past as evidenced in fossil and historical records. This paper reviews these records and highlights the information that they provide in terms of understanding the local- and regional-scale responses of African vegetation to future climate change. A key point that emerges is that a move to warmer and wetter conditions in the past resulted in a large increase in biomass and a range distribution of woody plants up to 400-500 km north of its present location, the so-called greening of the Sahara. By contrast, a transition to warmer and drier conditions resulted in a reduction in woody vegetation in many regions and an increase in grass/savanna-dominated landscapes. The rapid rate of climate warming coming into the current interglacial resulted in a dramatic increase in community turnover, but there is little evidence for widespread extinctions. However, huge variation in biotic response in both space and time is apparent with, in some cases, totally different responses to the same climatic driver. This highlights the importance of local features such as soils, topography and also internal biotic factors in determining responses and resilience of the African biota to climate change, information that is difficult to obtain from modelling but is abundant in palaeoecological records.

How will SOA change in the future?: SOA IN THE FUTURE

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

Lin, Guangxing; Penner, Joyce E.; Zhou, Cheng

2016-02-17

Secondary organic aerosol (SOA) plays a significant role in the Earth system by altering its radiative balance. Here we use an Earth system model coupled with an explicit SOA formation module to estimate the response of SOA concentrations to changes in climate, anthropogenic emissions, and human land use in the future. We find that climate change is the major driver for SOA change under the representative concentration pathways for the 8.5 future scenario. Climate change increases isoprene emission rate by 18% with the effect of temperature increases outweighing that of the CO2 inhibition effect. Annual mean global SOA mass ismore » increased by 25% as a result of climate change. However, anthropogenic emissions and land use change decrease SOA. The net effect is that future global SOA burden in 2100 is nearly the same as that of the present day. The SOA concentrations over the Northern Hemisphere are predicted to decline in the future due to the control of sulfur emissions.« less

Non-additive Effects in Genomic Selection

PubMed Central

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

2018-01-01

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

Non-additive Effects in Genomic Selection.

PubMed

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

2018-01-01

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

Global warming not so harmful for all plants - response of holomycotrophic orchid species for the future climate change.

PubMed

Kolanowska, Marta; Kras, Marta; Lipińska, Monika; Mystkowska, Katarzyna; Szlachetko, Dariusz L; Naczk, Aleksandra M

2017-10-05

Current and expected changes in global climate are major threat for biological diversity affecting individuals, communities and ecosystems. However, there is no general trend in the plants response to the climate change. The aim of present study was to evaluate impact of the future climate changes on the distribution of holomycotrophic orchid species using ecological niche modeling approach. Three different scenarios of future climate changes were tested to obtain the most comprehensive insight in the possible habitat loss of 16 holomycotrophic orchids. The extinction of Cephalanthera austiniae was predicted in all analyses. The coverage of suitable niches of Pogoniopsis schenckii will decrease to 1-30% of its current extent. The reduction of at least 50% of climatic niche of Erythrorchis cassythoides and Limodorum abortivum will be observed. In turn, the coverage of suitable niches of Hexalectris spicata, Uleiorchis ulaei and Wullschlaegelia calcarata may be even 16-74 times larger than in the present time. The conducted niche modeling and analysis of the similarity of their climatic tolerance showed instead that the future modification of the coverage of their suitable niches will not be unified and the future climate changes may be not so harmful for holomycotrophic orchids as expected.

The role of hunger state and dieting history in neural response to food cues: An event-related potential study.

PubMed

Feig, Emily H; Winter, Samantha R; Kounios, John; Erickson, Brian; Berkowitz, Staci A; Lowe, Michael R

2017-10-01

A history of dieting to lose weight has been shown to be a robust predictor of future weight gain. A potential factor in propensity towards weight gain is the nature of people's reactions to the abundance of highly palatable food cues in the environment. Event Related Potentials (ERPs) have revealed differences in how the brain processes food cues between obese and normal weight individuals, as well as between restrained and unrestrained eaters. However, comparisons by weight status are not informative regarding whether differences predate or follow weight gain in obese individuals and restrained eating has not consistently been found to predict future weight gain. The present study compared ERP responses to food cues in non-obese historic dieters (HDs) to non-obese never dieters (NDs). HDs showed a blunted N1 component relative to NDs overall, and delayed N1 and P2 components compared to NDs in the hungry state, suggesting that early, perceptual processing of food cues differs between these groups, especially when food-deprived. HDs also showed a more hunger-dependent sustained ERP (LPP) compared to NDs. Future research should test ERP-based food cue responsivity as a mediator between dieting history and future weight gain to better identify those most at risk for weight gain as well as the nature of their vulnerability. Copyright © 2017 Elsevier Inc. All rights reserved.

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

USGS Publications Warehouse

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

2011-01-01

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

Young Children’s Affective Responses to Acceptance and Rejection From Peers: A Computer-based Task Sensitive to Variation in Temperamental Shyness and Gender

PubMed Central

Howarth, Grace Z.; Guyer, Amanda E.; Pérez-Edgar, Koraly

2013-01-01

This study presents a novel task examining young children’s affective responses to evaluative feedback—specifically, social acceptance and rejection—from peers. We aimed to determine (1) whether young children report their affective responses to hypothetical peer evaluation predictably and consistently, and (2) whether young children’s responses to peer evaluation vary as a function of temperamental shyness and gender. Four- to seven-year-old children (N = 48) sorted pictures of unknown, similar-aged children into those with whom they wished or did not wish to play. Computerized peer evaluation later noted whether the pictured children were interested in a future playdate with participants. Participants then rated their affective responses to each acceptance or rejection event. Children were happy when accepted by children with whom they wanted to play, and disappointed when these children rejected them. Highly shy boys showed a wider range of responses to acceptance and rejection based on initial social interest, and may be particularly sensitive to both positive and negative evaluation. Overall, the playdate task captures individual differences in affective responses to evaluative peer feedback and is potentially amenable to future applications in research with young children, including pairings with psychophysiological measures. PMID:23997429

Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches

USGS Publications Warehouse

Francy, Donna S.; Brady, Amie M.G.; Carvin, Rebecca B.; Corsi, Steven R.; Fuller, Lori M.; Harrison, John H.; Hayhurst, Brett A.; Lant, Jeremiah; Nevers, Meredith B.; Terrio, Paul J.; Zimmerman, Tammy M.

2013-01-01

Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.). Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as surrogates to estimate concentrations of fecal-indicator bacteria or to provide the probability that a State recreational water-quality standard will be exceeded. When predictive models are used for beach closure or advisory decisions, they are referred to as “nowcasts.” During the recreational seasons of 2010-12, the U.S. Geological Survey (USGS), in cooperation with 23 local and State agencies, worked to improve existing nowcasts at 4 beaches, validate predictive models at another 38 beaches, and collect data for predictive-model development at 7 beaches throughout the Great Lakes. This report summarizes efforts to collect data and develop predictive models by multiple agencies and to compile existing information on the beaches and beach-monitoring programs into one comprehensive report. Local agencies measured E. coli concentrations and variables expected to affect E. coli concentrations such as wave height, turbidity, water temperature, and numbers of birds at the time of sampling. In addition to these field measurements, equipment was installed by the USGS or local agencies at or near several beaches to collect water-quality and metrological measurements in near real time, including nearshore buoys, weather stations, and tributary staff gages and monitors. The USGS worked with local agencies to retrieve data from existing sources either manually or by use of tools designed specifically to compile and process data for predictive-model development. Predictive models were developed by use of linear regression and (or) partial least squares techniques for 42 beaches that had at least 2 years of data (2010-11 and sometimes earlier) and for 1 beach that had 1 year of data. For most models, software designed for model development by the U.S. Environmental Protection Agency (Virtual Beach) was used. The selected model for each beach was based on a combination of explanatory variables including, most commonly, turbidity, day of the year, change in lake level over 24 hours, wave height, wind direction and speed, and antecedent rainfall for various time periods. Forty-two predictive models were validated against data collected during an independent year (2012) and compared to the current method for assessing recreational water quality-using the previous day’s E. coli concentration (persistence model). Goals for good predictive-model performance were responses that were at least 5 percent greater than the persistence model and overall correct responses greater than or equal to 80 percent, sensitivities (percentage of exceedances of the bathing-water standard that were correctly predicted by the model) greater than or equal to 50 percent, and specificities (percentage of nonexceedances correctly predicted by the model) greater than or equal to 85 percent. Out of 42 predictive models, 24 models yielded over-all correct responses that were at least 5 percent greater than the use of the persistence model. Predictive-model responses met the performance goals more often than the persistence-model responses in terms of overall correctness (28 versus 17 models, respectively), sensitivity (17 versus 4 models), and specificity (34 versus 25 models). Gaining knowledge of each beach and the factors that affect E. coli concentrations is important for developing good predictive models. Collection of additional years of data with a wide range of environmental conditions may also help to improve future model performance. The USGS will continue to work with local agencies in 2013 and beyond to develop and validate predictive models at beaches and improve existing nowcasts, restructuring monitoring activities to accommodate future uncertainties in funding and resources.

The predictive validity of the HERO Scorecard in determining future health care cost and risk trends.

PubMed

Goetzel, Ron Z; Henke, Rachel Mosher; Benevent, Richele; Tabrizi, Maryam J; Kent, Karen B; Smith, Kristyn J; Roemer, Enid Chung; Grossmeier, Jessica; Mason, Shawn T; Gold, Daniel B; Noeldner, Steven P; Anderson, David R

2014-02-01

To determine the ability of the Health Enhancement Research Organization (HERO) Scorecard to predict changes in health care expenditures. Individual employee health care insurance claims data for 33 organizations completing the HERO Scorecard from 2009 to 2011 were linked to employer responses to the Scorecard. Organizations were dichotomized into "high" versus "low" scoring groups and health care cost trends were compared. A secondary analysis examined the tool's ability to predict health risk trends. "High" scorers experienced significant reductions in inflation-adjusted health care costs (averaging an annual trend of -1.6% over 3 years) compared with "low" scorers whose cost trend remained stable. The risk analysis was inconclusive because of the small number of employers scoring "low." The HERO Scorecard predicts health care cost trends among employers. More research is needed to determine how well it predicts health risk trends for employees.

Flooding in the future--predicting climate change, risks and responses in urban areas.

PubMed

Ashley, R M; Balmforth, D J; Saul, A J; Blanskby, J D

2005-01-01

Engineering infrastructure is provided at high cost and is expected to have a useful operational life of decades. However, it is clear that the future is uncertain. Traditional approaches to designing and operating urban storm drainage assets have relied on past performance of natural systems and the ability to extrapolate this performance, together with that of the assets across the usable lifetime. Whether or not climate change is going to significantly alter future weather patterns in Europe, it is clear that it is now incumbent on designers and operators of storm drainage systems to prepare for greater uncertainty in the effectiveness of storm drainage systems. A recent U.K. Government study considered the potential effects of climate and socio-economic change in the U.K. in terms of four future scenarios and what the implications are for the performance of existing storm drainage facilities. In this paper the modelling that was undertaken to try to quantify the changes in risk, together with the effectiveness of responses in managing that risk, are described. It shows that flood risks may increase by a factor of almost 30 times and that traditional engineering measures alone are unlikely to be able to provide protection.

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.

Can quantitative sensory testing predict responses to analgesic treatment?

PubMed

Grosen, K; Fischer, I W D; Olesen, A E; Drewes, A M

2013-10-01

The role of quantitative sensory testing (QST) in prediction of analgesic effect in humans is scarcely investigated. This updated review assesses the effectiveness in predicting analgesic effects in healthy volunteers, surgical patients and patients with chronic pain. A systematic review of English written, peer-reviewed articles was conducted using PubMed and Embase (1980-2013). Additional studies were identified by chain searching. Search terms included 'quantitative sensory testing', 'sensory testing' and 'analgesics'. Studies on the relationship between QST and response to analgesic treatment in human adults were included. Appraisal of the methodological quality of the included studies was based on evaluative criteria for prognostic studies. Fourteen studies (including 720 individuals) met the inclusion criteria. Significant correlations were observed between responses to analgesics and several QST parameters including (1) heat pain threshold in experimental human pain, (2) electrical and heat pain thresholds, pressure pain tolerance and suprathreshold heat pain in surgical patients, and (3) electrical and heat pain threshold and conditioned pain modulation in patients with chronic pain. Heterogeneity among studies was observed especially with regard to application of QST and type and use of analgesics. Although promising, the current evidence is not sufficiently robust to recommend the use of any specific QST parameter in predicting analgesic response. Future studies should focus on a range of different experimental pain modalities rather than a single static pain stimulation paradigm. © 2013 European Federation of International Association for the Study of Pain Chapters.

Measuring anxious responses to predictable and unpredictable threat in children and adolescents

PubMed Central

Schmitz, Anja; Merikangas, Kathleen; Swendsen, Haruka; Cui, Lihong; Heaton, Leanne; Grillon, Christian

2011-01-01

Research has highlighted the need for new methods to assess emotions in children on multiple levels in order to gain better insight into the complex processes of emotional development. The startle reflex is a unique translational tool that has been utilized to study physiological processes during fear and anxiety in rodents and in human subjects. However, it has been challenging to implement developmentally-appropriate startle experiments in children. This paper describes a procedure that uses predictable and unpredictable aversive events to distinguish between phasic fear and sustained anxiety in children and adolescents. We investigated anxious responses, as measured with the startle reflex, in youth (N = 36, mean age[range] = 12.63 [7–17]) across three conditions: no aversive events (N), predictable aversive events (P), and unpredictable aversive events (U). Short-duration cues were presented several times in each condition. Aversive events were signaled by the cues in P, but were presented randomly in U. Participants showed fear-potentiated startle to the threat cue in P. Startle responses were also elevated between cues in U compared to N, suggesting that unpredictable aversive events can evoke a sustained state of anxiety in youth. This latter effect was influenced by sex, being greater in girls compared to boys. These findings indicate the feasibility of this experimental induction of the startle reflex in response to predictable and unpredictable events in children and adolescents, enabling future research on inter-individual differences in fear and anxiety and their development in youth. PMID:21440905

The cortisol awakening response predicts major depression: predictive stability over a 4-year follow-up and effect of depression history.

PubMed

Vrshek-Schallhorn, S; Doane, L D; Mineka, S; Zinbarg, R E; Craske, M G; Adam, E K

2013-03-01

The cortisol awakening response (CAR) has been shown to predict major depressive episodes (MDEs) over a 1-year period. It is unknown whether this effect: (a) is stable over longer periods of time; (b) is independent of prospective stressful life events; and (c) differentially predicts first onsets or recurrences of MDEs. A total of 270 older adolescents (mean age 17.06 years at cortisol measurement) from the larger prospective Northwestern-UCLA Youth Emotion Project completed baseline diagnostic and life stress interviews, questionnaires, and a 3-day cortisol sampling protocol measuring the CAR and diurnal rhythm, as well as up to four annual follow-up interviews of diagnoses and life stress. Non-proportional person-month survival analyses revealed that higher levels of the baseline CAR significantly predict MDEs for 2.5 years following cortisol measurement. However, the strength of prediction of depressive episodes significantly decays over time, with the CAR no longer significantly predicting MDEs after 2.5 years. Elevations in the CAR did not significantly increase vulnerability to prospective major stressful life events. They did, however, predict MDE recurrences more strongly than first onsets. These results suggest that a high CAR represents a time-limited risk factor for onsets of MDEs, which increases risk for depression independently of future major stressful life events. Possible explanations for the stronger effect of the CAR for predicting MDE recurrences than first onsets are discussed.

Markers predicting response to bacillus Calmette-Guérin immunotherapy in high-risk bladder cancer patients: a systematic review.

PubMed

Zuiverloon, Tahlita C M; Nieuweboer, Annemieke J M; Vékony, Hedvig; Kirkels, Wim J; Bangma, Chris H; Zwarthoff, Ellen C

2012-01-01

Currently, bacillus Calmette-Guérin (BCG) intravesical instillations are standard treatment for patients with high-grade non-muscle-invasive bladder cancer; however, no markers are available to predict BCG response. To review the contemporary literature on markers predicting BCG response, to discuss the key issues concerning the identification of predictive markers, and to provide recommendations for further research studies. We performed a systematic review of the literature using PubMed and Embase databases in the period 1996-2010. The free-text search was extended by adding the following keywords: recurrence, progression, survival, molecular marker, prognosis, TP53, Ki-67, RB, fibronectin, immunotherapy, cytokine, interleukin, natural killer, macrophage, PMN, polymorphism, SNP, single nucleotide polymorphism, and gene signature. If thresholds for the detection of urinary interleukin (IL)-8, IL-18, and tumour necrosis factor apoptosis-inducing ligand levels are standardised, measurement of these cytokines holds promise in the assessment of BCG therapy outcome. Studies on immunohistochemical markers (ie, TP53, Ki-67, and retinoblastoma) display contradictory results, probably because of the small patient groups that were used and seem unsuitable to predict BCG response. Exploring combinations of protein levels might prove to be more helpful to establish the effect of BCG therapy. Single nucleotide polymorphisms, either in cytokines or in genes involved in DNA repair, need to be investigated in different ethnicities before their clinical relevance can be determined. Measurement of urinary IL-2 levels seems to be the most potent marker of all the clinical parameters reviewed. IL-2 levels are currently the most promising predictive markers of BCG response. For future studies focusing on new biomarkers, it is essential to make more use of new biomedical techniques such as microRNA profiling and genomewide sequencing. Copyright © 2011 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Climate model diversity in the Northern Hemisphere Polar vortex response to climate change.

NASA Astrophysics Data System (ADS)

Simpson, I.; Seager, R.; Hitchcock, P.; Cohen, N.

2017-12-01

Global climate models vary widely in their predictions of the future of the Northern Hemisphere stratospheric polar vortex, with some showing a significant strengthening of the vortex, some showing a significant weakening and others displaying a response that is not outside of the range expected from internal variability alone. This inter-model spread in stratospheric predictions may account for some inter-model spread in tropospheric predictions with important implications for the storm tracks and regional climate change, particularly for the North Atlantic sector. Here, our current state of understanding of this model spread and its tropospheric impacts will be reviewed. Previous studies have proposed relationships between a models polar vortex response to climate change and its present day vortex climatology while others have demonstrated links between a models polar vortex response and changing wave activity coming up from the troposphere below under a warming climate. The extent to which these mechanisms can account for the spread in polar vortex changes exhibited by the Coupled Model Intercomparison Project, phase 5 models will be assessed. In addition, preliminary results from a series of idealized experiments with the Community Atmosphere Model will be presented. In these experiments, nudging of the stratospheric zonal mean state has been imposed to mimic the inter-model spread in the polar vortex response to climate change so that the downward influence of the spread in zonal mean stratospheric responses on the tropospheric circulation can be assessed within one model.

Modeling regeneration responses of big sagebrush (Artemisia tridentata) to abiotic conditions

USGS Publications Warehouse

Schlaepfer, Daniel R.; Lauenroth, William K.; Bradford, John B.

2014-01-01

Ecosystems dominated by big sagebrush, Artemisia tridentata Nuttall (Asteraceae), which are the most widespread ecosystems in semiarid western North America, have been affected by land use practices and invasive species. Loss of big sagebrush and the decline of associated species, such as greater sage-grouse, are a concern to land managers and conservationists. However, big sagebrush regeneration remains difficult to achieve by restoration and reclamation efforts and there is no regeneration simulation model available. We present here the first process-based, daily time-step, simulation model to predict yearly big sagebrush regeneration including relevant germination and seedling responses to abiotic factors. We estimated values, uncertainty, and importance of 27 model parameters using a total of 1435 site-years of observation. Our model explained 74% of variability of number of years with successful regeneration at 46 sites. It also achieved 60% overall accuracy predicting yearly regeneration success/failure. Our results identify specific future research needed to improve our understanding of big sagebrush regeneration, including data at the subspecies level and improved parameter estimates for start of seed dispersal, modified wet thermal-time model of germination, and soil water potential influences. We found that relationships between big sagebrush regeneration and climate conditions were site specific, varying across the distribution of big sagebrush. This indicates that statistical models based on climate are unsuitable for understanding range-wide regeneration patterns or for assessing the potential consequences of changing climate on sagebrush regeneration and underscores the value of this process-based model. We used our model to predict potential regeneration across the range of sagebrush ecosystems in the western United States, which confirmed that seedling survival is a limiting factor, whereas germination is not. Our results also suggested that modeled regeneration suitability is necessary but not sufficient to explain sagebrush presence. We conclude that future assessment of big sagebrush responses to climate change will need to account for responses of regenerative stages using a process-based understanding, such as provided by our model.

Predicting future forests: Understanding diverse phenological responses within a community and functional trait framework

NASA Astrophysics Data System (ADS)

Wolkovich, E. M.; Flynn, D. F. B.

2016-12-01

In recent years increasing attention has focused on plant phenology as an important indicator of the biological impacts of climate change, as many plants have shifted their leafing and flowering earlier with increasing temperatures. As data have accumulated, researchers have found a link between phenological responses to warming and plant performance and invasions. Such work suggests phenology may not only be a major impact of warming, but a critical predictor of future plant performance. Yet alongside this increasing interest in phenology, important issues remain unanswered: responses to warming for species at the same site or in the same genus vary often by weeks or more and the explanatory power of phenology for performance and invasions when analyzed across diverse datasets remains low. We propose progress can come from explicitly considering phenology within a community context and as a critical plant trait correlated with other major plant functional traits. Here, we lay out a framework for our proposal: specifically we review how we expect phenology and phenological cues of different species within a community to vary and what other functional traits are predicted to co-vary with phenological traits. Much research currently suggests phenology is a critical functional trait that is shaped strongly by the environment. Plants are expected to adjust their phenologies to avoid periods of high abiotic risk and/or high competition. Thus we may expect phenology to correlate strongly to other traits involved in mitigating risk and high competition. Results from recent meta-analyses as well as experimental and observational research from 28 species in northeastern North American temperate forests suggest that species within a community show the predicted diversified set of phenological cues. We review early work on links to other functional traits and in closing review how these correlations may in turn determine the diversity of phenological responses observed for some species and communities.

Crops in silico: A community wide multi-scale computational modeling framework of plant canopies

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Christensen, A.; Borkiewic, K.; Yiwen, X.; Ellis, A.; Panneerselvam, B.; Kannan, K.; Shrivastava, S.; Cox, D.; Hart, J.; Marshall-Colon, A.; Long, S.

2016-12-01

Current crop models predict a looming gap between supply and demand for primary foodstuffs over the next 100 years. While significant yield increases were achieved in major food crops during the early years of the green revolution, the current rates of yield increases are insufficient to meet future projected food demand. Furthermore, with projected reduction in arable land, decrease in water availability, and increasing impacts of climate change on future food production, innovative technologies are required to sustainably improve crop yield. To meet these challenges, we are developing Crops in silico (Cis), a biologically informed, multi-scale, computational modeling framework that can facilitate whole plant simulations of crop systems. The Cis framework is capable of linking models of gene networks, protein synthesis, metabolic pathways, physiology, growth, and development in order to investigate crop response to different climate scenarios and resource constraints. This modeling framework will provide the mechanistic details to generate testable hypotheses toward accelerating directed breeding and engineering efforts to increase future food security. A primary objective for building such a framework is to create synergy among an inter-connected community of biologists and modelers to create a realistic virtual plant. This framework advantageously casts the detailed mechanistic understanding of individual plant processes across various scales in a common scalable framework that makes use of current advances in high performance and parallel computing. We are currently designing a user friendly interface that will make this tool equally accessible to biologists and computer scientists. Critically, this framework will provide the community with much needed tools for guiding future crop breeding and engineering, understanding the emergent implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment.

From Metabonomics to Pharmacometabonomics: The Role of Metabolic Profiling in Personalized Medicine

PubMed Central

Everett, Jeremy R.

2016-01-01

Variable patient responses to drugs are a key issue for medicine and for drug discovery and development. Personalized medicine, that is the selection of medicines for subgroups of patients so as to maximize drug efficacy and minimize toxicity, is a key goal of twenty-first century healthcare. Currently, most personalized medicine paradigms rely on clinical judgment based on the patient's history, and on the analysis of the patients' genome to predict drug effects i.e., pharmacogenomics. However, variability in patient responses to drugs is dependent upon many environmental factors to which human genomics is essentially blind. A new paradigm for predicting drug responses based on individual pre-dose metabolite profiles has emerged in the past decade: pharmacometabonomics, which is defined as “the prediction of the outcome (for example, efficacy or toxicity) of a drug or xenobiotic intervention in an individual based on a mathematical model of pre-intervention metabolite signatures.” The new pharmacometabonomics paradigm is complementary to pharmacogenomics but has the advantage of being sensitive to environmental as well as genomic factors. This review will chart the discovery and development of pharmacometabonomics, and provide examples of its current utility and possible future developments. PMID:27660611

Food allergy animal models: an overview.

PubMed

Helm, Ricki M

2002-05-01

Specific food allergy is characterized by sensitization to innocuous food proteins with production of allergen-specific IgE that binds to receptors on basophils and mast cells. Upon recurrent exposure to the same allergen, an allergic response is induced by mediator release following cross-linking of cell-bound allergen-specific IgE. The determination of what makes an innocuous food protein an allergen in predisposed individuals is unknown; however, mechanistic and protein allergen predictive models are being actively investigated in a number of animal models. Currently, there is no animal model that will actively profile known food allergens, predict the allergic potential of novel food proteins, or demonstrate clinically the human food allergic sensitization/allergic response. Animal models under investigation include mice, rats, the guinea pig, atopic dog, and neonatal swine. These models are being assessed for production of IgE, clinical responses to re-exposure, and a ranking of food allergens (based on potency) including a nonfood allergen protein source. A selection of animal models actively being investigated that will contribute to our understanding of what makes a protein an allergen and future predictive models for assessing the allergenicity of novel proteins is presented in this review.

Incorporating climate change projections into riparian restoration planning and design

USGS Publications Warehouse

Perry, Laura G.; Reynolds, Lindsay V.; Beechie, Timothy J.; Collins, Mathias J.; Shafroth, Patrick B.

2015-01-01

Climate change and associated changes in streamflow may alter riparian habitats substantially in coming decades. Riparian restoration provides opportunities to respond proactively to projected climate change effects, increase riparian ecosystem resilience to climate change, and simultaneously address effects of both climate change and other human disturbances. However, climate change may alter which restoration methods are most effective and which restoration goals can be achieved. Incorporating climate change into riparian restoration planning and design is critical to long-term restoration of desired community composition and ecosystem services. In this review, we discuss and provide examples of how climate change might be incorporated into restoration planning at the key stages of assessing the project context, establishing restoration goals and design criteria, evaluating design alternatives, and monitoring restoration outcomes. Restoration planners have access to numerous tools to predict future climate, streamflow, and riparian ecology at restoration sites. Planners can use those predictions to assess which species or ecosystem services will be most vulnerable under future conditions, and which sites will be most suitable for restoration. To accommodate future climate and streamflow change, planners may need to adjust methods for planting, invasive species control, channel and floodplain reconstruction, and water management. Given the considerable uncertainty in future climate and streamflow projections, riparian ecological responses, and effects on restoration outcomes, planners will need to consider multiple potential future scenarios, implement a variety of restoration methods, design projects with flexibility to adjust to future conditions, and plan to respond adaptively to unexpected change.

Effects of exercise-heat acclimation on fluid, electrolyte, and endocrine responses during tilt and +Gz acceleration in women and men

NASA Technical Reports Server (NTRS)

Greenleaf, J. E.; Brock, P. J.; Sciaraffa, D.; Polese, A.; Elizondo, R.

1985-01-01

Two aspects of prolonged endurance training were investigated: (1) the effects of exercise-heat acclimation (on a cycle ergometer at 40 C, 42 rh) on orthostatic tolerance (70 deg head-up tilt) and on a +Gz (head-to-foot) acceleration tolerance of male and female subjects; and (2) comparison of their fluid-electrolyte shifts and hormonal (plasma epinephdrine, norepinephrine, renin, and vasopressin) responses during tilting and centrifugation. The adaptive responses during the 12 d, 2-h acclimation did not alter acceleration tolerance of either men or women, or the women's tilt tolerance, but did increase men's tilt tolerance from 30.4 min before to 58.3 min after acclimation. The patterns of fluid, electrolyte, and protein shifts at tolerance in acceleration and tilting tests were virtually the same in men and women. On the other hand, the hormonal plasma epinephrine, norepinephrine, renin, and vasopressin resonses displayed different shift patterns during acceleration and tilting. It is concluded that the responses to tilting cannot be used to predict responses to acceleration. Future experiments for relating the orthostatic and the acceleration tolerances, and the practical questions of the training regimens for future astronauts are discussed.

Longwave emission trends over Africa and implications for Atlantic hurricanes

NASA Astrophysics Data System (ADS)

Zhang, Lei; Rechtman, Thomas; Karnauskas, Kristopher B.; Li, Laifang; Donnelly, Jeffrey P.; Kossin, James P.

2017-09-01

The latitudinal gradient of outgoing longwave radiation (OLR) over Africa is a skillful and physically based predictor of seasonal Atlantic hurricane activity. The African OLR gradient is observed to have strengthened during the satellite era, as predicted by state-of-the-art global climate models (GCMs) in response to greenhouse gas forcing. Prior to the satellite era and the U.S. and European clean air acts, the African OLR gradient weakened due to aerosol forcing of the opposite sign. GCMs predict a continuation of the increasing OLR gradient in response to greenhouse gas forcing. Assuming a steady linear relationship between African easterly waves and tropical cyclogenesis, this result suggests a future increase in Atlantic tropical cyclone frequency by 10% (20%) at the end of the 21st century under the RCP 4.5 (8.5) forcing scenario.

Memory-Guided Attention: Independent Contributions of the Hippocampus and Striatum.

PubMed

Goldfarb, Elizabeth V; Chun, Marvin M; Phelps, Elizabeth A

2016-01-20

Memory can strongly influence how attention is deployed in future encounters. Though memory dependent on the medial temporal lobes has been shown to drive attention, how other memory systems could concurrently and comparably enhance attention is less clear. Here, we demonstrate that both reinforcement learning and context memory facilitate attention in a visual search task. Using functional magnetic resonance imaging, we dissociate the mechanisms by which these memories guide attention: trial by trial, the hippocampus (not the striatum) predicted attention benefits from context memory, while the striatum (not the hippocampus) predicted facilitation from rewarded stimulus-response associations. Responses in these regions were also distinctly correlated with individual differences in each type of memory-guided attention. This study provides novel evidence for the role of the striatum in guiding attention, dissociable from hippocampus-dependent context memory.

Memory-Guided Attention: Independent Contributions of the Hippocampus and Striatum

PubMed Central

Goldfarb, Elizabeth V.; Chun, Marvin M.; Phelps, Elizabeth A.

2015-01-01

SUMMARY Memory can strongly influence how attention is deployed in future encounters. Though memory dependent on the medial temporal lobes has been shown to drive attention, how other memory systems could concurrently and comparably enhance attention is less clear. Here, we demonstrate that both reinforcement learning and context memory facilitate attention in a visual search task. Using functional magnetic resonance imaging, we dissociate the mechanisms by which these memories guide attention: trial by trial, the hippocampus (not the striatum) predicted attention benefits from context memory, while the striatum (not the hippocampus) predicted facilitation from rewarded stimulus-response associations. Responses in these regions were also distinctly correlated with individual differences in each type of memory-guided attention. This study provides novel evidence for the role of the striatum in guiding attention, dissociable from hippocampus-dependent context memory. PMID:26777274

Review of ship slamming loads and responses

NASA Astrophysics Data System (ADS)

Wang, Shan; Guedes Soares, C.

2017-12-01

The paper presents an overview of studies of slamming on ship structures. This work focuses on the hull slamming, which is one of the most important types of slamming problems to be considered in the ship design process and the assessment of the ship safety. There are three main research aspects related to the hull slamming phenomenon, a) where and how often a slamming event occurs, b) slamming load prediction and c) structural response due to slamming loads. The approaches used in each aspect are reviewed and commented, together with the presentation of some typical results. The methodology, which combines the seakeeping analysis and slamming load prediction, is discussed for the global analysis of the hull slamming of a ship in waves. Some physical phenomena during the slamming event are discussed also. Recommendations for the future research and developments are made.

Acoustics Research of Propulsion Systems

NASA Technical Reports Server (NTRS)

Gao, Ximing; Houston, Janice D.

2014-01-01

The liftoff phase induces some of the highest acoustic loading over a broad frequency for a launch vehicle. These external acoustic environments are used in the prediction of the internal vibration responses of the vehicle and components. Thus, predicting these liftoff acoustic environments is critical to the design requirements of any launch vehicle but there are challenges. Present liftoff vehicle acoustic environment prediction methods utilize stationary data from previously conducted hold-down tests; i.e. static firings conducted in the 1960's, to generate 1/3 octave band Sound Pressure Level (SPL) spectra. These data sets are used to predict the liftoff acoustic environments for launch vehicles. To facilitate the accuracy and quality of acoustic loading, predictions at liftoff for future launch vehicles such as the Space Launch System (SLS), non-stationary flight data from the Ares I-X were processed in PC-Signal in two forms which included a simulated hold-down phase and the entire launch phase. In conjunction, the Prediction of Acoustic Vehicle Environments (PAVE) program was developed in MATLAB to allow for efficient predictions of sound pressure levels (SPLs) as a function of station number along the vehicle using semiempirical methods. This consisted, initially, of generating the Dimensionless Spectrum Function (DSF) and Dimensionless Source Location (DSL) curves from the Ares I-X flight data. These are then used in the MATLAB program to generate the 1/3 octave band SPL spectra. Concluding results show major differences in SPLs between the hold-down test data and the processed Ares IX flight data making the Ares I-X flight data more practical for future vehicle acoustic environment predictions.

Modeling potential hydrochemical responses to climate change and rising CO2 at the Hubbard Brook Experimental Forest using a dynamic biogeochemical model (PnET-BGC)

Treesearch

Afshin Pourmokhtarian; Charles T. Driscoll; John L. Campbell; Katharine Hayhoe

2012-01-01

Dynamic hydrochemical models are useful tools for understanding and predicting the interactive effects of climate change, atmospheric CO2, and atmospheric deposition on the hydrology and water quality of forested watersheds. We used the biogeochemical model, PnET-BGC, to evaluate the effects of potential future changes in temperature,...

Selecting At-Risk Readers in First Grade for Early Intervention: A Two-Year Longitudinal Study of Decision Rules and Procedures

ERIC Educational Resources Information Center

Compton, Donald L.; Fuchs, Douglas; Fuchs, Lynn S.; Bryant, Joan D.

2006-01-01

Response to intervention (RTI) models for identifying learning disabilities rely on the accurate identification of children who, without Tier 2 tutoring, would develop reading disability (RD). This study examined 2 questions concerning the use of 1st-grade data to predict future RD: (1) Does adding initial word identification fluency (WIF) and 5…

Detecting Intervention Effects in a Cluster-Randomized Design Using Multilevel Structural Equation Modeling for Binary Responses

ERIC Educational Resources Information Center

Cho, Sun-Joo; Preacher, Kristopher J.; Bottge, Brian A.

2015-01-01

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test--post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test…

Control of the induced microgravity environment of the Man Tended Free Flyer (MTFF)

NASA Technical Reports Server (NTRS)

Schlund, Juergen

1988-01-01

Induced disturbance sources have been identified on board the Man Tended Free Flyer (MTFF). Vibration responses at sensitive payload/spacecraft interfaces have been predicted by the application of an empirically found spacecraft dynamic transfer function. Vibrations from fluid loops (Freon, water) and of reaction wheels are assessed to be the main contributors to the induced microgravity environment. The expected payload acceleration response amplitudes presented here are more than one hundred times higher than the admissible values given by the MTFF system requirement, not considering the structural striction-friction effects which could be avoided by appropriate design. Real responses will be significantly lower because the derivation of excitation and transmission functions are based on worst case assumptions. The results indicate that future activities must be concentrated on equipment design improvement and the implementation of vibration reduction along the disturbance transmission path. The activities must be accompanied by early equipment and assembly development tests and transmissibility measurements with the integrated spacecraft engineering and structural models in order to improve the accuracy of payload response predictions.

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

PubMed

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

2012-08-01

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

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

PubMed

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

2018-03-01

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

Early stress and human behavioral development: emerging evolutionary perspectives.

PubMed

Del Giudice, M

2014-08-01

Stress experienced early in life exerts a powerful, lasting influence on development. Converging empirical findings show that stressful experiences become deeply embedded in the child's neurobiology, with an astonishing range of long-term effects on cognition, emotion, and behavior. In contrast with the prevailing view that such effects are the maladaptive outcomes of 'toxic' stress, adaptive models regard them as manifestations of evolved developmental plasticity. In this paper, I offer a brief introduction to adaptive models of early stress and human behavioral development, with emphasis on recent theoretical contributions and emerging concepts in the field. I begin by contrasting dysregulation models of early stress with their adaptive counterparts; I then introduce life history theory as a unifying framework, and review recent work on predictive adaptive responses (PARs) in human life history development. In particular, I discuss the distinction between forecasting the future state of the environment (external prediction) and forecasting the future state of the organism (internal prediction). Next, I present the adaptive calibration model, an integrative model of individual differences in stress responsivity based on life history concepts. I conclude by examining how maternal-fetal conflict may shape the physiology of prenatal stress and its adaptive and maladaptive effects on postnatal development. In total, I aim to show how theoretical work from evolutionary biology is reshaping the way we think about the role of stress in human development, and provide researchers with an up-to-date conceptual map of this fascinating and rapidly evolving field.

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

USGS Publications Warehouse

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

2008-01-01

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

Phylogenetic responses of forest trees to global change.

PubMed

Senior, John K; Schweitzer, Jennifer A; O'Reilly-Wapstra, Julianne; Chapman, Samantha K; Steane, Dorothy; Langley, Adam; Bailey, Joseph K

2013-01-01

In a rapidly changing biosphere, approaches to understanding the ecology and evolution of forest species will be critical to predict and mitigate the effects of anthropogenic global change on forest ecosystems. Utilizing 26 forest species in a factorial experiment with two levels each of atmospheric CO2 and soil nitrogen, we examined the hypothesis that phylogeny would influence plant performance in response to elevated CO2 and nitrogen fertilization. We found highly idiosyncratic responses at the species level. However, significant, among-genetic lineage responses were present across a molecularly determined phylogeny, indicating that past evolutionary history may have an important role in the response of whole genetic lineages to future global change. These data imply that some genetic lineages will perform well and that others will not, depending upon the environmental context.

Do causal concentration-response functions exist? A critical review of associational and causal relations between fine particulate matter and mortality.

PubMed

Cox, Louis Anthony Tony

2017-08-01

Concentration-response (C-R) functions relating concentrations of pollutants in ambient air to mortality risks or other adverse health effects provide the basis for many public health risk assessments, benefits estimates for clean air regulations, and recommendations for revisions to existing air quality standards. The assumption that C-R functions relating levels of exposure and levels of response estimated from historical data usefully predict how future changes in concentrations would change risks has seldom been carefully tested. This paper critically reviews literature on C-R functions for fine particulate matter (PM2.5) and mortality risks. We find that most of them describe historical associations rather than valid causal models for predicting effects of interventions that change concentrations. The few papers that explicitly attempt to model causality rely on unverified modeling assumptions, casting doubt on their predictions about effects of interventions. A large literature on modern causal inference algorithms for observational data has been little used in C-R modeling. Applying these methods to publicly available data from Boston and the South Coast Air Quality Management District around Los Angeles shows that C-R functions estimated for one do not hold for the other. Changes in month-specific PM2.5 concentrations from one year to the next do not help to predict corresponding changes in average elderly mortality rates in either location. Thus, the assumption that estimated C-R relations predict effects of pollution-reducing interventions may not be true. Better causal modeling methods are needed to better predict how reducing air pollution would affect public health.

Predicting Health Resilience in Pediatric Type 1 Diabetes: A Test of the Resilience Model Framework.

PubMed

Rohan, Jennifer M; Huang, Bin; Pendley, Jennifer Shroff; Delamater, Alan; Dolan, Lawrence; Reeves, Grafton; Drotar, Dennis

2015-10-01

This research examined whether individual and family-level factors during the transition from late childhood to early adolescence protected individuals from an increased risk of poor glycemic control across time, which is a predictor of future diabetes-related complications (i.e., health resilience). This longitudinal, multisite study included 239 patients with type 1 diabetes and their caregivers. Glycemic control was based on hemoglobin A1c. Individual and family-level factors included: demographic variables, youth behavioral regulation, adherence (frequency of blood glucose monitoring), diabetes self-management, level of parental support for diabetes autonomy, level of youth mastery and responsibility for diabetes management, and diabetes-related family conflict. Longitudinal mixed-effects logistic regression indicated that testing blood glucose more frequently, better self-management, and less diabetes-related family conflict were indicators of health resilience. Multiple individual and family-level factors predicted risk for future health complications. Future research should develop interventions targeting specific individual and family-level factors to sustain glycemic control within recommended targets, which reduces the risk of developing future health complications during the transition to adolescence and adulthood. © The Author 2015. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Reducing Uncertainty in Chemistry Climate Model Predictions of Stratospheric Ozone

NASA Technical Reports Server (NTRS)

Douglass, A. R.; Strahan, S. E.; Oman, L. D.; Stolarski, R. S.

2014-01-01

Chemistry climate models (CCMs) are used to predict the future evolution of stratospheric ozone as ozone-depleting substances decrease and greenhouse gases increase, cooling the stratosphere. CCM predictions exhibit many common features, but also a broad range of values for quantities such as year of ozone-return-to-1980 and global ozone level at the end of the 21st century. Multiple linear regression is applied to each of 14 CCMs to separate ozone response to chlorine change from that due to climate change. We show that the sensitivity of lower atmosphere ozone to chlorine change deltaO3/deltaCly is a near linear function of partitioning of total inorganic chlorine (Cly) into its reservoirs; both Cly and its partitioning are controlled by lower atmospheric transport. CCMs with realistic transport agree with observations for chlorine reservoirs and produce similar ozone responses to chlorine change. After 2035 differences in response to chlorine contribute little to the spread in CCM results as the anthropogenic contribution to Cly becomes unimportant. Differences among upper stratospheric ozone increases due to temperature decreases are explained by differences in ozone sensitivity to temperature change deltaO3/deltaT due to different contributions from various ozone loss processes, each with their own temperature dependence. In the lower atmosphere, tropical ozone decreases caused by a predicted speed-up in the Brewer-Dobson circulation may or may not be balanced by middle and high latitude increases, contributing most to the spread in late 21st century predictions.

Assessing climate change impact by integrated hydrological modelling

NASA Astrophysics Data System (ADS)

Lajer Hojberg, Anker; Jørgen Henriksen, Hans; Olsen, Martin; der Keur Peter, van; Seaby, Lauren Paige; Troldborg, Lars; Sonnenborg, Torben; Refsgaard, Jens Christian

2013-04-01

Future climate may have a profound effect on the freshwater cycle, which must be taken into consideration by water management for future planning. Developments in the future climate are nevertheless uncertain, thus adding to the challenge of managing an uncertain system. To support the water managers at various levels in Denmark, the national water resources model (DK-model) (Højberg et al., 2012; Stisen et al., 2012) was used to propagate future climate to hydrological response under considerations of the main sources of uncertainty. The DK-model is a physically based and fully distributed model constructed on the basis of the MIKE SHE/MIKE11 model system describing groundwater and surface water systems and the interaction between the domains. The model has been constructed for the entire 43.000 km2 land area of Denmark only excluding minor islands. Future climate from General Circulation Models (GCM) was downscaled by Regional Climate Models (RCM) by a distribution-based scaling method (Seaby et al., 2012). The same dataset was used to train all combinations of GCM-RCMs and they were found to represent the mean and variance at the seasonal basis equally well. Changes in hydrological response were computed by comparing the short term development from the period 1990 - 2010 to 2021 - 2050, which is the time span relevant for water management. To account for uncertainty in future climate predictions, hydrological response from the DK-model using nine combinations of GCMs and RCMs was analysed for two catchments representing the various hydrogeological conditions in Denmark. Three GCM-RCM combinations displaying high, mean and low future impacts were selected as representative climate models for which climate impact studies were carried out for the entire country. Parameter uncertainty was addressed by sensitivity analysis and was generally found to be of less importance compared to the uncertainty spanned by the GCM-RCM combinations. Analysis of the simulations showed some unexpected results, where climate models predicting the largest increase in net precipitation did not result in the largest increase in groundwater heads. This was found to be the result of different initial conditions (1990 - 2010) for the various climate models. In some areas a combination of a high initial groundwater head and an increase in precipitation towards 2021 - 2050 resulted in a groundwater head raise that reached the drainage or the surface water system. This will increase the exchange from the groundwater to the surface water system, but reduce the raise in groundwater heads. An alternative climate model, with a lower initial head can thus predict a higher increase in the groundwater head, although the increase in precipitation is lower. This illustrates an extra dimension in the uncertainty assessment, namely the climate models capability of simulating the current climatic conditions in a way that can reproduce the observed hydrological response. Højberg, AL, Troldborg, L, Stisen, S, et al. (2012) Stakeholder driven update and improvement of a national water resources model - http://www.sciencedirect.com/science/article/pii/S1364815212002423 Seaby, LP, Refsgaard, JC, Sonnenborg, TO, et al. (2012) Assessment of robustness and significance of climate change signals for an ensemble of distribution-based scaled climate projections (submitted) Journal of Hydrology Stisen, S, Højberg, AL, Troldborg, L et al., (2012): On the importance of appropriate rain-gauge catch correction for hydrological modelling at mid to high latitudes - http://www.hydrol-earth-syst-sci.net/16/4157/2012/

Potential for shoreline changes due to sea-level rise along the U.S. mid-Atlantic region

USGS Publications Warehouse

Gutierrez, Benjamin T.; Williams, S. Jeffress; Thieler, E. Robert

2007-01-01

Sea-level rise over the next century is expected to contribute significantly to physical changes along open-ocean shorelines. Predicting the form and magnitude of coastal changes is important for understanding the impacts to humans and the environment. Presently, the ability to predict coastal changes is limited by the scientific understanding of the many variables and processes involved in coastal change, and the lack of consensus regarding the validity of existing conceptual, analytical, or numerical models. In order to assess potential future coastal changes in the mid-Atlantic U.S. for the U.S. Climate Change Science Program (CCSP), a workshop was convened by the U.S. Geological Survey. Assessments of future coastal change were made by a committee of coastal scientists with extensive professional experience in the mid-Atlantic region. Thirteen scientists convened for a two-day meeting to exchange information and develop a consensus opinion on potential future coastal changes for the mid-Atlantic coast in response to sea-level rise. Using criteria defined in past work, the mid-Atlantic coast was divided into four geomorphic compartments: spits, headlands, wave-dominated barriers, and mixed-energy barriers. A range of potential coastal responses was identified for each compartment based on four sea-level rise scenarios. The four scenarios were based on the assumptions that: a) the long-term sea-level rise rate observed over the 20th century would persist over the 21st century, b) the 20th century rate would increase by 2 mm/yr, c) the 20th century rate would increase by 7 mm/yr, or d) sea-level would rise by 2 m over the next few hundred years. Potential responses to these sea-level rise scenarios depend on the landforms that occur within a region and include increased likelihood for erosion and shoreline retreat for all coastal types, increased likelihood for erosion, overwash and inlet breaching for barrier islands, as well as the possibility of a threshold state (e.g., dramatic change in barrier evolution, such as segmentation or disintegration) for some barrier island systems. The likelihood of the potential coastal responses is expressed using standard terminology employed in climate change assessments (e.g., as used by the Intergovernmental Panel on Climate Change and CCSP). This assessment was based on the coastal geomorphology in its present condition and does not consider any coastal protection that might be undertaken in the future. The committee recognized that a variety of erosion mitigation measures have been implemented along developed portions of the coast and these are very likely to be applied in the future. It was also acknowledged that economics, political will, and other factors can drive decisions to implement these measures, and that such decisions cannot be predicted with confidence. The results of this assessment are depicted graphically on maps of the study area.

Inside the black box: starting to uncover the underlying decision rules used in one-by-one expert assessment of occupational exposure in case-control studies

PubMed Central

Wheeler, David C.; Burstyn, Igor; Vermeulen, Roel; Yu, Kai; Shortreed, Susan M.; Pronk, Anjoeka; Stewart, Patricia A.; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Schwenn, Molly; Johnson, Alison; Silverman, Debra T.; Friesen, Melissa C.

2014-01-01

Objectives Evaluating occupational exposures in population-based case-control studies often requires exposure assessors to review each study participants' reported occupational information job-by-job to derive exposure estimates. Although such assessments likely have underlying decision rules, they usually lack transparency, are time-consuming and have uncertain reliability and validity. We aimed to identify the underlying rules to enable documentation, review, and future use of these expert-based exposure decisions. Methods Classification and regression trees (CART, predictions from a single tree) and random forests (predictions from many trees) were used to identify the underlying rules from the questionnaire responses and an expert's exposure assignments for occupational diesel exhaust exposure for several metrics: binary exposure probability and ordinal exposure probability, intensity, and frequency. Data were split into training (n=10,488 jobs), testing (n=2,247), and validation (n=2,248) data sets. Results The CART and random forest models' predictions agreed with 92–94% of the expert's binary probability assignments. For ordinal probability, intensity, and frequency metrics, the two models extracted decision rules more successfully for unexposed and highly exposed jobs (86–90% and 57–85%, respectively) than for low or medium exposed jobs (7–71%). Conclusions CART and random forest models extracted decision rules and accurately predicted an expert's exposure decisions for the majority of jobs and identified questionnaire response patterns that would require further expert review if the rules were applied to other jobs in the same or different study. This approach makes the exposure assessment process in case-control studies more transparent and creates a mechanism to efficiently replicate exposure decisions in future studies. PMID:23155187

Arctic climatechange and its impacts on the ecology of the North Atlantic.

PubMed

Greene, Charles H; Pershing, Andrew J; Cronin, Thomas M; Ceci, Nicole

2008-11-01

Arctic climate change from the Paleocene epoch to the present is reconstructed with the objective of assessing its recent and future impacts on the ecology of the North Atlantic. A recurring theme in Earth's paleoclimate record is the importance of the Arctic atmosphere, ocean, and cryosphere in regulating global climate on a variety of spatial and temporal scales. A second recurring theme in this record is the importance of freshwater export from the Arctic in regulating global- to basin-scale ocean circulation patterns and climate. Since the 1970s, historically unprecedented changes have been observed in the Arctic as climate warming has increased precipitation, river discharge, and glacial as well as sea-ice melting. In addition, modal shifts in the atmosphere have altered Arctic Ocean circulation patterns and the export of freshwater into the North Atlantic. The combination of these processes has resulted in variable patterns of freshwater export from the Arctic Ocean and the emergence of salinity anomalies that have periodically freshened waters in the North Atlantic. Since the early 1990s, changes in Arctic Ocean circulation patterns and freshwater export have been associated with two types of ecological responses in the North Atlantic. The first of these responses has been an ongoing series of biogeographic range expansions by boreal plankton, including renewal of the trans-Arctic exchanges of Pacific species with the Atlantic. The second response was a dramatic regime shift in the shelf ecosystems of the Northwest Atlantic that occurred during the early 1990s. This regime shift resulted from freshening and stratification of the shelf waters, which in turn could be linked to changes in the abundances and seasonal cycles of phytoplankton, zooplankton, and higher trophic-level consumer populations. It is predicted that the recently observed ecological responses to Arctic climate change in the North Atlantic will continue into the near future if current trends in sea ice, freshwater export, and surface ocean salinity continue. It is more difficult to predict ecological responses to abrupt climate change in the more distant future as tipping points in the Earth's climate system are exceeded.

Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder

PubMed Central

Kessler, R.C.; van Loo, H.M.; Wardenaar, K.J.; Bossarte, R.M.; Brenner, L.A.; Ebert, D.D; de Jonge, P.; Nierenberg, A.A.; Rosellini, A.J.; Sampson, N.A.; Schoevers, R.A.; Wilcox, M.A.; Zaslavsky, A.M.

2016-01-01

Aims Clinicians need guidance to address the heterogeneity of treatment responses of patients with major depressive disorder (MDD). While prediction schemes based on symptom clustering and biomarkers have so far not yielded results of sufficient strength to inform clinical decision-making, prediction schemes based on big data predictive analytic models might be more practically useful. Methods We review evidence suggesting that prediction equations based on symptoms and other easily-assessed clinical features found in previous research to predict MDD treatment outcomes might provide a foundation for developing predictive analytic clinical decision support models that could help clinicians select optimal (personalized) MDD treatments. These methods could also be useful in targeting patient subsamples for more expensive biomarker assessments. Results Approximately two dozen baseline variables obtained from medical records or patient reports have been found repeatedly in MDD treatment trials to predict overall treatment outcomes (i.e., intervention versus control) or differential treatment outcomes (i.e., intervention A versus intervention B). Similar evidence has been found in observational studies of MDD persistence-severity. However, no treatment studies have yet attempted to develop treatment outcome equations using the full set of these predictors. Promising preliminary empirical results coupled with recent developments in statistical methodology suggest that models could be developed to provide useful clinical decision support in personalized treatment selection. These tools could also provide a strong foundation to increase statistical power in focused studies of biomarkers and MDD heterogeneity of treatment response in subsequent controlled trials. Conclusions Coordinated efforts are needed to develop a protocol for systematically collecting information about established predictors of heterogeneity of MDD treatment response in large observational treatment studies, applying and refining these models in subsequent pragmatic trials, carrying out pooled secondary analyses to extract the maximum amount of information from these coordinated studies, and using this information to focus future discovery efforts in the segment of the patient population in which continued uncertainty about treatment response exists. PMID:26810628

Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder.

PubMed

Kessler, R C; van Loo, H M; Wardenaar, K J; Bossarte, R M; Brenner, L A; Ebert, D D; de Jonge, P; Nierenberg, A A; Rosellini, A J; Sampson, N A; Schoevers, R A; Wilcox, M A; Zaslavsky, A M

2017-02-01

Clinicians need guidance to address the heterogeneity of treatment responses of patients with major depressive disorder (MDD). While prediction schemes based on symptom clustering and biomarkers have so far not yielded results of sufficient strength to inform clinical decision-making, prediction schemes based on big data predictive analytic models might be more practically useful. We review evidence suggesting that prediction equations based on symptoms and other easily-assessed clinical features found in previous research to predict MDD treatment outcomes might provide a foundation for developing predictive analytic clinical decision support models that could help clinicians select optimal (personalised) MDD treatments. These methods could also be useful in targeting patient subsamples for more expensive biomarker assessments. Approximately two dozen baseline variables obtained from medical records or patient reports have been found repeatedly in MDD treatment trials to predict overall treatment outcomes (i.e., intervention v. control) or differential treatment outcomes (i.e., intervention A v. intervention B). Similar evidence has been found in observational studies of MDD persistence-severity. However, no treatment studies have yet attempted to develop treatment outcome equations using the full set of these predictors. Promising preliminary empirical results coupled with recent developments in statistical methodology suggest that models could be developed to provide useful clinical decision support in personalised treatment selection. These tools could also provide a strong foundation to increase statistical power in focused studies of biomarkers and MDD heterogeneity of treatment response in subsequent controlled trials. Coordinated efforts are needed to develop a protocol for systematically collecting information about established predictors of heterogeneity of MDD treatment response in large observational treatment studies, applying and refining these models in subsequent pragmatic trials, carrying out pooled secondary analyses to extract the maximum amount of information from these coordinated studies, and using this information to focus future discovery efforts in the segment of the patient population in which continued uncertainty about treatment response exists.

Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes?

DOE PAGES

Allen, Kara; Dupuy, Juan Manuel; Gei, Maria G.; ...

2017-02-03

Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are alreadymore » limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales.« less

Climate-change influences on the response of macroinvertebrate communities to pesticide contamination in the Sacramento River, California watershed.

PubMed

Chiu, Ming-Chih; Hunt, Lisa; Resh, Vincent H

2017-03-01

Limited studies have addressed how future climate-change scenarios may alter the effects of pesticides on biotic assemblages or the effects of exposures to repeated pulses of pesticide mixtures. We used reported pesticide-use data as input to a hydrological fate and transport model (Soil and Water Assessment Tool) under multiple climate-change scenarios to simulate spatiotemporal dynamics of pesticides mixtures in streams on a daily time-step in the Sacramento River watershed of California. We predicted that there will be increased pesticide application with warming across the watershed, especially in upstream areas. Using a statistical model describing the relationship between macroinvertebrate communities and pesticide dynamics, we found that compared to the baseline period of 1970-1999: (1) most climate-change scenarios predicted increased rainfall and warming across the watershed during 2070-2099; and (2) increasing pesticide contamination and increased impact on macroinvertebrates will likely occur in most areas of the watershed by 2070-2099; and (3) lower increases in effects of pesticides on macroinvertebrates were predicted for the downstream areas with intensive agriculture compared to some upstream areas with less-intensive agriculture. Future efforts on practical adaptation and mitigation strategies can be improved by awareness of altered threats of pesticide mixtures under future climate-change conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes?

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

Allen, Kara; Dupuy, Juan Manuel; Gei, Maria G.

Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are alreadymore » limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales.« less

Current Pressure Transducer Application of Model-based Prognostics Using Steady State Conditions

NASA Technical Reports Server (NTRS)

Teubert, Christopher; Daigle, Matthew J.

2014-01-01

Prognostics is the process of predicting a system's future states, health degradation/wear, and remaining useful life (RUL). This information plays an important role in preventing failure, reducing downtime, scheduling maintenance, and improving system utility. Prognostics relies heavily on wear estimation. In some components, the sensors used to estimate wear may not be fast enough to capture brief transient states that are indicative of wear. For this reason it is beneficial to be capable of detecting and estimating the extent of component wear using steady-state measurements. This paper details a method for estimating component wear using steady-state measurements, describes how this is used to predict future states, and presents a case study of a current/pressure (I/P) Transducer. I/P Transducer nominal and off-nominal behaviors are characterized using a physics-based model, and validated against expected and observed component behavior. This model is used to map observed steady-state responses to corresponding fault parameter values in the form of a lookup table. This method was chosen because of its fast, efficient nature, and its ability to be applied to both linear and non-linear systems. Using measurements of the steady state output, and the lookup table, wear is estimated. A regression is used to estimate the wear propagation parameter and characterize the damage progression function, which are used to predict future states and the remaining useful life of the system.

Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes?

NASA Astrophysics Data System (ADS)

Allen, Kara; Dupuy, Juan Manuel; Gei, Maria G.; Hulshof, Catherine; Medvigy, David; Pizano, Camila; Salgado-Negret, Beatriz; Smith, Christina M.; Trierweiler, Annette; Van Bloem, Skip J.; Waring, Bonnie G.; Xu, Xiangtao; Powers, Jennifer S.

2017-02-01

Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are already limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales.

The vegetation outlook (VegOut): a new method for predicting vegetation seasonal greenness

USGS Publications Warehouse

Tadesse, T.; Wardlow, B.; Hayes, M.; Svoboda, M.; Brown, J.

2010-01-01

The vegetation outlook (VegOut) is a geospatial tool for predicting general vegetation condition patterns across large areas. VegOut predicts a standardized seasonal greenness (SSG) measure, which represents a general indicator of relative vegetation health. VegOut predicts SSG values at multiple time steps (two to six weeks into the future) based on the analysis of "historical patterns" (i.e., patterns at each 1 km grid cell and time of the year) of satellite, climate, and oceanic data over an 18-year period (1989 to 2006). The model underlying VegOut capitalizes on historical climate-vegetation interactions and ocean-climate teleconnections (such as El Niño and the Southern Oscillation, ENSO) expressed over the 18-year data record and also considers several environmental characteristics (e.g., land use/cover type and soils) that influence vegetation's response to weather conditions to produce 1 km maps that depict future general vegetation conditions. VegOut provides regionallevel vegetation monitoring capabilities with local-scale information (e.g., county to sub-county level) that can complement more traditional remote sensing-based approaches that monitor "current" vegetation conditions. In this paper, the VegOut approach is discussed and a case study over the central United States for selected periods of the 2008 growing season is presented to demonstrate the potential of this new tool for assessing and predicting vegetation conditions.

Prediction of future uniform milk prices in Florida federal milk marketing order 6 from milk futures markets.

PubMed

De Vries, A; Feleke, S

2008-12-01

This study assessed the accuracy of 3 methods that predict the uniform milk price in Federal Milk Marketing Order 6 (Florida). Predictions were made for 1 to 12 mo into the future. Data were from January 2003 to May 2007. The CURRENT method assumed that future uniform milk prices were equal to the last announced uniform milk price. The F+BASIS and F+UTIL methods were based on the milk futures markets because the futures prices reflect the market's expectation of the class III and class IV cash prices that are announced monthly by USDA. The F+BASIS method added an exponentially weighted moving average of the difference between the class III cash price and the historical uniform milk price (also known as basis) to the class III futures price. The F+UTIL method used the class III and class IV futures prices, the most recently announced butter price, and historical utilizations to predict the skim milk prices, butterfat prices, and utilizations in all 4 classes. Predictions of future utilizations were made with a Holt-Winters smoothing method. Federal Milk Marketing Order 6 had high class I utilization (85 +/- 4.8%). Mean and standard deviation of the class III and class IV cash prices were $13.39 +/- 2.40/cwt (1 cwt = 45.36 kg) and $12.06 +/- 1.80/cwt, respectively. The actual uniform price in Tampa, Florida, was $16.62 +/- 2.16/cwt. The basis was $3.23 +/- 1.23/cwt. The F+BASIS and F+UTIL predictions were generally too low during the period considered because the class III cash prices were greater than the corresponding class III futures prices. For the 1- to 6-mo-ahead predictions, the root of the mean squared prediction errors from the F+BASIS method were $1.12, $1.20, $1.55, $1.91, $2.16, and $2.34/cwt, respectively. The root of the mean squared prediction errors ranged from $2.50 to $2.73/cwt for predictions up to 12 mo ahead. Results from the F+UTIL method were similar. The accuracies of the F+BASIS and F+UTIL methods for all 12 fore-cast horizons were not significantly different. Application of the modified Mariano-Diebold tests showed that no method included all the information contained in the other methods. In conclusion, both F+BASIS and F+UTIL methods tended to more accurately predict the future uniform milk prices than the CURRENT method, but prediction errors could be substantial even a few months into the future. The majority of the prediction error was caused by the inefficiency of the futures markets to predict the class III cash prices.

Evidence base and future research directions in the management of low back pain

PubMed Central

Abbott, Allan

2016-01-01

Low back pain (LBP) is a prevalent and costly condition. Awareness of valid and reliable patient history taking, physical examination and clinical testing is important for diagnostic accuracy. Stratified care which targets treatment to patient subgroups based on key characteristics is reliant upon accurate diagnostics. Models of stratified care that can potentially improve treatment effects include prognostic risk profiling for persistent LBP, likely response to specific treatment based on clinical prediction models or suspected underlying causal mechanisms. The focus of this editorial is to highlight current research status and future directions for LBP diagnostics and stratified care. PMID:27004162

Predicting the response of the Amazon rainforest to persistent drought conditions under current and future climates: a major challenge for global land surface models

NASA Astrophysics Data System (ADS)

Joetzjer, E.; Delire, C.; Douville, H.; Ciais, P.; Decharme, B.; Fisher, R.; Christoffersen, B.; Calvet, J. C.; da Costa, A. C. L.; Ferreira, L. V.; Meir, P.

2014-08-01

While a majority of Global Climate Models project dryer and longer dry seasons over the Amazon under higher CO2 levels, large uncertainties surround the response of vegetation to persistent droughts in both present-day and future climates. We propose a detailed evaluation of the ability of the ISBACC Land Surface Model to capture drought effects on both water and carbon budgets, comparing fluxes and stocks at two recent ThroughFall Exclusion (TFE) experiments performed in the Amazon. We also explore the model sensitivity to different Water Stress Function (WSF) and to an idealized increase in CO2 concentration and/or temperature. In spite of a reasonable soil moisture simulation, ISBACC struggles to correctly simulate the vegetation response to TFE whose amplitude and timing is highly sensitive to the WSF. Under higher CO2 concentration, the increased Water Use Efficiency (WUE) mitigates the ISBACC's sensitivity to drought. While one of the proposed WSF formulation improves the response of most ISBACC fluxes, except respiration, a parameterization of drought-induced tree mortality is missing for an accurate estimate of the vegetation response. Also, a better mechanistic understanding of the forest responses to drought under a warmer climate and higher CO2 concentration is clearly needed.

Clinical Relevance of Prognostic and Predictive Molecular Markers in Gliomas.

PubMed

Siegal, Tali

2016-01-01

Sorting and grading of glial tumors by the WHO classification provide clinicians with guidance as to the predicted course of the disease and choice of treatment. Nonetheless, histologically identical tumors may have very different outcome and response to treatment. Molecular markers that carry both diagnostic and prognostic information add useful tools to traditional classification by redefining tumor subtypes within each WHO category. Therefore, molecular markers have become an integral part of tumor assessment in modern neuro-oncology and biomarker status now guides clinical decisions in some subtypes of gliomas. The routine assessment of IDH status improves histological diagnostic accuracy by differentiating diffuse glioma from reactive gliosis. It carries a favorable prognostic implication for all glial tumors and it is predictive for chemotherapeutic response in anaplastic oligodendrogliomas with codeletion of 1p/19q chromosomes. Glial tumors that contain chromosomal codeletion of 1p/19q are defined as tumors of oligodendroglial lineage and have favorable prognosis. MGMT promoter methylation is a favorable prognostic marker in astrocytic high-grade gliomas and it is predictive for chemotherapeutic response in anaplastic gliomas with wild-type IDH1/2 and in glioblastoma of the elderly. The clinical implication of other molecular markers of gliomas like mutations of EGFR and ATRX genes and BRAF fusion or point mutation is highlighted. The potential of molecular biomarker-based classification to guide future therapeutic approach is discussed and accentuated.

Human-Centered Technologies and Procedures for Future Air Traffic Management

NASA Technical Reports Server (NTRS)

Smith, Philip; Woods, David; McCoy, Elaine; Billings, Charles; Sarter, Nadine; Denning, Rebecca; Dekker, Sidney

1997-01-01

The use of various methodologies to predict the impact of future Air Traffic Management (ATM) concepts and technologies is explored. The emphasis has been on the importance of modeling coordination and cooperation among multiple agents within this system, and on understanding how the interactions among these agents will be influenced as new roles, responsibilities, procedures and technologies are introduced. To accomplish this, we have been collecting data on performance under the current air traffic management system, identifying critical problem areas and looking for examples suggestive of general approaches for solving such problems. Using the results of these field studies, we have developed a set of concrete scenarios centered around future designs, and have studied performance in these scenarios with a set of 40 controllers, dispatchers, pilots and traffic managers.

Predicting Future Commitment to Care for Frail Parents Among Employed Caregivers.

PubMed

Lechner, Viola M

1992-06-01

A study of 133 full time employees with parent care responsibilities investigated various factors that could reduce this group's future caregiving commitment to aging parents. Study factors included: caregiver attributes, level of caregiving involvement, job stress, tensions between the caregiver and the dependent parent, caregiver's level of physical and mental strain, and limited support from family and friends. The relationship between the caregiver and the parent was the best predictor of sustained commitment to caregiving. One aspect of the employees' work experience made a small, but important contribution to respondents' future care plans. Those employees who frequently adjusted their work schedule and routine to accommodate parent care demands were less likely to sustain their caregiving commitment. Reasons for these findings are explored and implications for social policy and clinical practice are discussed.

Early non-response to certolizumab pegol in rheumatoid arthritis predicts treatment failure at one year. Data from a randomised phase III clinical trial.

PubMed

Berenbaum, Francis; Pham, Thao; Claudepierre, Pascal; de Chalus, Thibault; Joubert, Jean-Michel; Saadoun, Carine; Riou França, Lionel; Fautrel, Bruno

2018-01-01

To compare different early clinical criteria of non-response determined at three months as predictors of clinical failure at one year in patients with rheumatoid arthritis starting therapy with certolizumab pegol. Data were derived from a randomised Phase III clinical trial in patients with rheumatoid arthritis who failed to respond to methotrexate monotherapy. Patients included in this post-hoc analysis were treated with certolizumab pegol (400mg qd reduced to 200mg qd after one month) and with methotrexate. The study duration was twelve months. Response at three months was determined with the American College of Rheumatology-50, Disease Assessment Score-28 ESR, Health Assessment Questionnaire and the Clinical Disease Activity Index. The performance of these measures at predicting treatment failure at twelve months defined by the American College of Rheumatology-50 criteria was determined, using the positive predictive values as the principal evaluation criterion. Three hundred and eighty two patients were available for analysis and 225 completed the twelve-month follow-up. At Week 52, 149 (38.1%) patients met the American College of Rheumatology-50 response criterion. Positive predictive values ranged from 81% for a decrease in Health Assessment Questionnaire- Disability index score since baseline >0.22 to 95% for a decrease in Disease Assessment Score-28 score since baseline≥1.2. Sensitivity was≤70% in all cases. Performance of these measures was similar irrespective of the definition of treatment failure at 12months. Simple clinical measures of disease activity can predict future treatment failure reliably and are appropriate for implementing treat-to-target treatment strategies in everyday practice. Copyright © 2017 Société française de rhumatologie. Published by Elsevier SAS. All rights reserved.

Evaluation of Human and Anthropomorphic Test Device Finite Element Models under Spaceflight Loading Conditions

NASA Technical Reports Server (NTRS)

Putnam, Jacob P.; Untaroiu, Costin; Somers. Jeffrey

2014-01-01

In an effort to develop occupant protection standards for future multipurpose crew vehicles, the National Aeronautics and Space Administration (NASA) has looked to evaluate the test device for human occupant restraint with the modification kit (THOR-K) anthropomorphic test device (ATD) in relevant impact test scenarios. With the allowance and support of the National Highway Traffic Safety Administration, NASA has performed a series of sled impact tests on the latest developed THOR-K ATD. These tests were performed to match test conditions from human volunteer data previously collected by the U.S. Air Force. The objective of this study was to evaluate the THOR-K finite element (FE) model and the Total HUman Model for Safety (THUMS) FE model with respect to the tests performed. These models were evaluated in spinal and frontal impacts against kinematic and kinetic data recorded in ATD and human testing. Methods: The FE simulations were developed based on recorded pretest ATD/human position and sled acceleration pulses measured during testing. Predicted responses by both human and ATD models were compared to test data recorded under the same impact conditions. The kinematic responses of the models were quantitatively evaluated using the ISO-metric curve rating system. In addition, ATD injury criteria and human stress/strain data were calculated to evaluate the risk of injury predicted by the ATD and human model, respectively. Results: Preliminary results show well-correlated response between both FE models and their physical counterparts. In addition, predicted ATD injury criteria and human model stress/strain values are shown to positively relate. Kinematic comparison between human and ATD models indicates promising biofidelic response, although a slightly stiffer response is observed within the ATD. Conclusion: As a compliment to ATD testing, numerical simulation provides efficient means to assess vehicle safety throughout the design process and further improve the design of physical ATDs. The assessment of the THOR-K and THUMS FE models in a spaceflight testing condition is an essential first step to implementing these models in the computational evaluation of spacecraft occupant safety. Promising results suggest future use of these models in the aerospace field.

Leveraging Psychological Insights to Encourage the Responsible Use of Consumer Debt.

PubMed

Hershfield, Hal E; Sussman, Abigail B; O'Brien, Rourke L; Bryan, Christopher J

2015-11-01

U.S. consumers currently hold $880 billion in revolving debt, with a mean household credit card balance of approximately $6,000. Although economic factors play a role in this societal issue, it is clear that psychological forces also affect consumers' decisions to take on and maintain unmanageable debt balances. We examine three psychological barriers to the responsible use of credit and debt. We discuss the tendency for consumers to (a) make erroneous predictions about future spending habits, (b) rely too heavily on values presented on billing statements, and (c) categorize debt and saving into separate mental accounts. To overcome these obstacles, we urge policymakers to implement methods that facilitate better budgeting of future expenses, modify existing credit card statement disclosures, and allow consumers to easily apply government transfers (such as tax credits) to debt repayment. In doing so, we highlight minimal and inexpensive ways to remedy the debt problem. © The Author(s) 2015.

Synthetic B-Cell Epitopes Eliciting Cross-Neutralizing Antibodies: Strategies for Future Dengue Vaccine

PubMed Central

Poh, Chit Laa; Kirk, Kristin; McBride, William John Hannan; Aaskov, John; Grollo, Lara

2016-01-01

Dengue virus (DENV) is a major public health threat worldwide. A key element in protection from dengue fever is the neutralising antibody response. Anti-dengue IgG purified from DENV-2 infected human sera showed reactivity against several peptides when evaluated by ELISA and epitope extraction techniques. A multi-step computational approach predicted six antigenic regions within the E protein of DENV-2 that concur with the 6 epitopes identified by the combined ELISA and epitope extraction approach. The selected peptides representing B-cell epitopes were attached to a known dengue T-helper epitope and evaluated for their vaccine potency. Immunization of mice revealed two novel synthetic vaccine constructs that elicited good humoral immune responses and produced cross-reactive neutralising antibodies against DENV-1, 2 and 3. The findings indicate new directions for epitope mapping and contribute towards the future development of multi-epitope based synthetic peptide vaccine. PMID:27223692

Coastlines of the past: clues for our future

NASA Astrophysics Data System (ADS)

Reynolds, L.

2017-12-01

Coastlines are constantly evolving due to the long-term effects of sea-level change and human impacts, as well as in response to high-impact, short duration hazard events such as storms, tsunamis, and earthquakes. The sediments that accumulate in coastal systems such as estuaries, dunes, and beaches archieve the enviornmental record of the past, providing us a baseline with which to predict future coastal hazard magnitude and recurrence intervals. We study this record to understand future hazard potential, as well as to aid restoration efforts. Many coastal systems around the world have been degraded in the last few hundred years by human activity- these regions are important breeding grounds for commercially viable species, natural pollution filters, and barriers against inundation. Efforts to restore coastal systems often rely on data from historical sources to reconstruct past coastal conditions-the geological record can extend the timeframe with which we think about possible restoration points. In addition, studying past coastal response to enviornmental changes can aid the effort to restore systems to a point of sustainability and resilience instead of simply restoring to an arbirtary point in time.

Patent Analysis for Supporting Merger and Acquisition (M&A) Prediction: A Data Mining Approach

NASA Astrophysics Data System (ADS)

Wei, Chih-Ping; Jiang, Yu-Syun; Yang, Chin-Sheng

M&A plays an increasingly important role in the contemporary business environment. Companies usually conduct M&A to pursue complementarity from other companies for preserving and/or extending their competitive advantages. For the given bidder company, a critical first step to the success of M&A activities is the appropriate selection of target companies. However, existing studies on M&A prediction incur several limitations, such as the exclusion of technological variables in M&A prediction models and the omission of the profile of the respective bidder company and its compatibility with candidate target companies. In response to these limitations, we propose an M&A prediction technique which not only encompasses technological variables derived from patent analysis as prediction indictors but also takes into account the profiles of both bidder and candidate target companies when building an M&A prediction model. We collect a set of real-world M&A cases to evaluate the proposed technique. The evaluation results are encouraging and will serve as a basis for future studies.

Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control.

PubMed

Adeleke, Jude Adekunle; Moodley, Deshendran; Rens, Gavin; Adewumi, Aderemi Oluyinka

2017-04-09

Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web.

Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control

PubMed Central

Adeleke, Jude Adekunle; Moodley, Deshendran; Rens, Gavin; Adewumi, Aderemi Oluyinka

2017-01-01

Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM2.5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM2.5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web. PMID:28397776

Effective Mitigation and Adaptation Strategies for Public Health Impacts of Heatwaves for Brookline, MA

NASA Astrophysics Data System (ADS)

Jalalzadeh Fard, B.; Hassanzadeh, H.; Bhatia, U.; Ganguly, A. R.

2016-12-01

Studies on urban areas show a significant increase in frequency and intensity of heatwaves over the past decades, and predict the same trend for future. Since heatwaves have been responsible for a large number of life losses, urgent adaptation and mitigation strategies are required in the policy and decision making level for a sustainable urban planning. The Sustainability and Data Sciences Laboratory at Northeastern University, under the aegis of Thriving Earth Exchange of AGU, is working with the town of Brookline to understand the potential public health impacts of anticipated heatwaves. We consider the most important social and physical factors to obtain vulnerability and exposure parameters for each census block group of the town. Utilizing remote sensing data, we locate Urban Heat Islands (UHIs) during a recent heatwave event, as the hazard parameter. We then create priority risk map using the risk framework. Our analyses show spatial correlations between the UHIs and social factors such as poverty, and physical factors such as land cover variations. Furthermore, we investigate the future heatwave frequency and intensity increases by analyzing the climate models predictions. For future changes of UHIs, land cover changes are investigated using available predictive data. Also, socioeconomic predictions are carried out to complete the futuristic models of heatwave risks. Considering plausible scenarios for Brookline, we develop different risk maps based on the vulnerability, exposure and hazard parameters. Eventually, we suggest guidelines for Heatwave Action Plans for prioritizing effective mitigation and adaptation strategies in urban planning for the town of Brookline.

Matsu: An Elastic Cloud Connected to a SensorWeb for Disaster Response

NASA Technical Reports Server (NTRS)

Mandl, Daniel

2011-01-01

This slide presentation reviews the use of cloud computing combined with the SensorWeb in aiding disaster response planning. Included is an overview of the architecture of the SensorWeb, and overviews of the phase 1 of the EO-1 system and the steps to improve it to transform it to an On-demand product cloud as part of the Open Cloud Consortium (OCC). The effectiveness of this system is demonstrated in the SensorWeb for the Namibia flood in 2010, using information blended from MODIS, TRMM, River Gauge data, and the Google Earth version of Namibia the system enabled river surge predictions and could enable planning for future disaster responses.

Searching for and Finding Meaning in Collective Trauma: Results From a National Longitudinal Study of the 9/11 Terrorist Attacks

PubMed Central

Updegraff, John A.; Silver, Roxane Cohen; Holman, E. Alison

2008-01-01

The ability to make sense of events in one’s life has held a central role in theories of adaptation to adversity. However, there are few rigorous studies on the role of meaning in adjustment, and those that have been conducted have focused predominantly on direct personal trauma. The authors examined the predictors and long-term consequences of Americans’ searching for and finding meaning in a widespread cultural upheaval—the terrorist attacks of September 11, 2001—among a national probability sample of U.S. adults (N = 931). Searching for meaning at 2 months post-9/11 was predicted by demographics and high acute stress response. In contrast, finding meaning was predicted primarily by demographics and specific early coping strategies. Whereas searching for meaning predicted greater posttraumatic stress (PTS) symptoms across the following 2 years, finding meaning predicted lower PTS symptoms, even after controlling for pre-9/11 mental health, exposure to 9/11, and acute stress response. Mediation analyses suggest that finding meaning supported adjustment by reducing fears of future terrorism. Results highlight the role of meaning in adjustment following collective traumas that shatter people’s fundamental assumptions about security and invulnerability. PMID:18729704

Seismic design and engineering research at the U.S. Geological Survey

USGS Publications Warehouse

1988-01-01

The Engineering Seismology Element of the USGS Earthquake Hazards Reduction Program is responsible for the coordination and operation of the National Strong Motion Network to collect, process, and disseminate earthquake strong-motion data; and, the development of improved methodologies to estimate and predict earthquake ground motion.  Instrumental observations of strong ground shaking induced by damaging earthquakes and the corresponding response of man-made structures provide the basis for estimating the severity of shaking from future earthquakes, for earthquake-resistant design, and for understanding the physics of seismologic failure in the Earth's crust.

Harnessing system models of cell death signalling for cytotoxic chemotherapy: towards personalised medicine approaches?

PubMed

Huber, Heinrich J; McKiernan, Ross G; Prehn, Jochen H M

2014-03-01

Most cytotoxic chemotherapeutics are believed to kill cancer cells by inducing apoptosis. Understanding the factors that contribute to impairment of apoptosis in cancer cells is therefore critical for the development of novel therapies that circumvent the widespread chemoresistance. Apoptosis, however, is a complex and tightly controlled process that can be induced by different classes of chemotherapeutics targeting different signalling nodes and pathways. Moreover, apoptosis initiation and apoptosis execution strongly depend on patient-specific, genomic and proteomic signatures. Here, we will review recent translational studies that suggest a critical link between the sensitivity of cancer cells to initiate apoptosis and clinical outcome. Next we will discuss recent advances in the field of system modelling of apoptosis pathways for the prediction of treatment responses. We propose that initiation of mitochondrial apoptosis, defined as the process of mitochondrial outer membrane permeabilisation (MOMP), is a dose-dependent decision process that allows for a prediction of individual therapy responses and therapeutic windows. We provide evidence in contrast that apoptosis execution post-MOMP may be a binary decision that dictates whether apoptosis is executed or not. We will discuss the implications of this concept for the future use of novel adjuvant therapeutics that specifically target apoptosis signalling pathways or which may be used to reduce the impact of cell-to-cell heterogeneity on therapy responses. Finally, we will discuss the technical and regulatory requirements surrounding the use and implications of system-based patient stratification tools for the future of personalised oncology.

The effect of species and colony size on the bleaching response of reef-building corals in the Florida Keys during the 2005 mass bleaching event

NASA Astrophysics Data System (ADS)

Brandt, M. E.

2009-12-01

Understanding the variation in coral bleaching response is necessary for making accurate predictions of population changes and the future state of reefs in a climate of increasing thermal stress events. Individual coral colonies, belonging to inshore patch reef communities of the Florida Keys, were followed through the 2005 mass bleaching event. Overall, coral bleaching patterns followed an index of accumulated thermal stress more closely than in situ temperature measurements. Eight coral species ( Colpophyllia natans, Diploria strigosa, Montastraea cavernosa, M. faveolata, Porites astreoides, P. porites, Siderastrea siderea, and Stephanocoenia intersepta), representing >90% of the coral colonies studied, experienced intense levels of bleaching, but responses varied. Bleaching differed significantly among species: Colpophyllia natans and Diploria strigosa were most susceptible to thermal stress, while Stephanocoenia intersepta was the most tolerant. For colonies of C. natans, M. faveolata, and S. siderea, larger colonies experienced more extensive bleaching than smaller colonies. The inshore patch reef communities of the Florida Keys have historically been dominated by large colonies of Montastraea sp. and Colpophyllia natans. These results provide evidence that colony-level differences can affect bleaching susceptibility in this habitat and suggest that the impact of future thermal stress events may be biased toward larger colonies of dominant reef-building species. Predicted increases in the frequency of mass bleaching and subsequent mortality may therefore result in significant structural shifts of these ecologically important communities.

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach—A Case Study for the City of Wuhan in China

PubMed Central

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-01-01

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study—simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan. PMID:28617348

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

PubMed

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

2007-10-01

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

Development of Response Spectral Ground Motion Prediction Equations from Empirical Models for Fourier Spectra and Duration of Ground Motion

NASA Astrophysics Data System (ADS)

Bora, S. S.; Scherbaum, F.; Kuehn, N. M.; Stafford, P.; Edwards, B.

2014-12-01

In a probabilistic seismic hazard assessment (PSHA) framework, it still remains a challenge to adjust ground motion prediction equations (GMPEs) for application in different seismological environments. In this context, this study presents a complete framework for the development of a response spectral GMPE easily adjustable to different seismological conditions; and which does not suffer from the technical problems associated with the adjustment in response spectral domain. Essentially, the approach consists of an empirical FAS (Fourier Amplitude Spectrum) model and a duration model for ground motion which are combined within the random vibration theory (RVT) framework to obtain the full response spectral ordinates. Additionally, FAS corresponding to individual acceleration records are extrapolated beyond the frequency range defined by the data using the stochastic FAS model, obtained by inversion as described in Edwards & Faeh, (2013). To that end, an empirical model for a duration, which is tuned to optimize the fit between RVT based and observed response spectral ordinate, at each oscillator frequency is derived. Although, the main motive of the presented approach was to address the adjustability issues of response spectral GMPEs; comparison, of median predicted response spectra with the other regional models indicate that presented approach can also be used as a stand-alone model. Besides that, a significantly lower aleatory variability (σ<0.5 in log units) in comparison to other regional models, at shorter periods brands it to a potentially viable alternative to the classical regression (on response spectral ordinates) based GMPEs for seismic hazard studies in the near future. The dataset used for the presented analysis is a subset of the recently compiled database RESORCE-2012 across Europe, Middle East and the Mediterranean region.

Predicting photosynthesis and transpiration responses to ozone: decoupling modeled photosynthesis and stomatal conductance

NASA Astrophysics Data System (ADS)

Lombardozzi, D.; Levis, S.; Bonan, G.; Sparks, J. P.

2012-08-01

Plants exchange greenhouse gases carbon dioxide and water with the atmosphere through the processes of photosynthesis and transpiration, making them essential in climate regulation. Carbon dioxide and water exchange are typically coupled through the control of stomatal conductance, and the parameterization in many models often predict conductance based on photosynthesis values. Some environmental conditions, like exposure to high ozone (O3) concentrations, alter photosynthesis independent of stomatal conductance, so models that couple these processes cannot accurately predict both. The goals of this study were to test direct and indirect photosynthesis and stomatal conductance modifications based on O3 damage to tulip poplar (Liriodendron tulipifera) in a coupled Farquhar/Ball-Berry model. The same modifications were then tested in the Community Land Model (CLM) to determine the impacts on gross primary productivity (GPP) and transpiration at a constant O3 concentration of 100 parts per billion (ppb). Modifying the Vcmax parameter and directly modifying stomatal conductance best predicts photosynthesis and stomatal conductance responses to chronic O3 over a range of environmental conditions. On a global scale, directly modifying conductance reduces the effect of O3 on both transpiration and GPP compared to indirectly modifying conductance, particularly in the tropics. The results of this study suggest that independently modifying stomatal conductance can improve the ability of models to predict hydrologic cycling, and therefore improve future climate predictions.

A 15,000 year record of vegetation and climate change from a treeline lake in the Rocky Mountains, Wyoming, USA

Treesearch

Scott A. Mensing; John L. Korfmacher; Thomas Minckley; Robert C. Musselman

2012-01-01

Future climate projections predict warming at high elevations that will impact treeline species, but complex topographic relief in mountains complicates ecologic response, and we have a limited number of long-term studies examining vegetation change related to climate. In this study, pollen and conifer stomata were analyzed from a 2.3 m sediment core extending to 15,...

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.

Developing Present-day Proxy Cases Based on NARVAL Data for Investigating Low Level Cloud Responses to Future Climate Change.

NASA Astrophysics Data System (ADS)

Reilly, Stephanie

2017-04-01

The energy budget of the entire global climate is significantly influenced by the presence of boundary layer clouds. The main aim of the High Definition Clouds and Precipitation for Advancing Climate Prediction (HD(CP)2) project is to improve climate model predictions by means of process studies of clouds and precipitation. This study makes use of observed elevated moisture layers as a proxy of future changes in tropospheric humidity. The associated impact on radiative transfer triggers fast responses in boundary layer clouds, providing a framework for investigating this phenomenon. The investigation will be carried out using data gathered during the Next-generation Aircraft Remote-sensing for VALidation (NARVAL) South campaigns. Observational data will be combined with ECMWF reanalysis data to derive the large scale forcings for the Large Eddy Simulations (LES). Simulations will be generated for a range of elevated moisture layers, spanning a multi-dimensional phase space in depth, amplitude, elevation, and cloudiness. The NARVAL locations will function as anchor-points. The results of the large eddy simulations and the observations will be studied and compared in an attempt to determine how simulated boundary layer clouds react to changes in radiative transfer from the free troposphere. Preliminary LES results will be presented and discussed.

Near-future carbon dioxide levels alter fish behaviour by interfering with neurotransmitter function

NASA Astrophysics Data System (ADS)

Nilsson, Göran E.; Dixson, Danielle L.; Domenici, Paolo; McCormick, Mark I.; Sørensen, Christina; Watson, Sue-Ann; Munday, Philip L.

2012-03-01

Predicted future CO2 levels have been found to alter sensory responses and behaviour of marine fishes. Changes include increased boldness and activity, loss of behavioural lateralization, altered auditory preferences and impaired olfactory function. Impaired olfactory function makes larval fish attracted to odours they normally avoid, including ones from predators and unfavourable habitats. These behavioural alterations have significant effects on mortality that may have far-reaching implications for population replenishment, community structure and ecosystem function. However, the underlying mechanism linking high CO2 to these diverse responses has been unknown. Here we show that abnormal olfactory preferences and loss of behavioural lateralization exhibited by two species of larval coral reef fish exposed to high CO2 can be rapidly and effectively reversed by treatment with an antagonist of the GABA-A receptor. GABA-A is a major neurotransmitter receptor in the vertebrate brain. Thus, our results indicate that high CO2 interferes with neurotransmitter function, a hitherto unrecognized threat to marine populations and ecosystems. Given the ubiquity and conserved function of GABA-A receptors, we predict that rising CO2 levels could cause sensory and behavioural impairment in a wide range of marine species, especially those that tightly control their acid-base balance through regulatory changes in HCO3- and Cl- levels.

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

Abbott, Benjamin; Jones, Jeremy B.; Schuur, Edward A.

As the permafrost region warms, its large organic carbon pool will be increasingly vulnerable to decomposition, combustion, and hydrologic export. Models predict that some portion of this release will be offset by increased production of Arctic and boreal biomass; however, the lack of robust estimates of net carbon balance increases the risk of further overshooting international emissions targets. Precise empirical or model-based assessments of the critical factors driving carbon balance are unlikely in the near future, so to address this gap, we present estimates from 98 permafrost-region experts of the response of biomass, wildfire, and hydrologic carbon flux to climatemore » change. Results suggest that contrary to model projections, total permafrost-region biomass could decrease due to water stress and disturbance, factors that are not adequately incorporated in current models. Assessments indicate that end-of-the-century organic carbon release from Arctic rivers and collapsing coastlines could increase by 75% while carbon loss via burning could increase four-fold. Experts identified water balance, shifts in vegetation community, and permafrost degradation as the key sources of uncertainty in predicting future system response. In combination with previous findings, results suggest the permafrost region will become a carbon source to the atmosphere by 2100 regardless of warming scenario but that 65%–85% of permafrost carbon release can still be avoided if human emissions are actively reduced.« less

Respiratory sinus arrhythmia during worry forecasts stress-related increases in psychological distress.

PubMed

Gouin, Jean-Philippe; Deschênes, Sonya S; Dugas, Michel J

2014-09-01

Respiratory sinus arrhythmia (RSA) has been conceptualized as an index of emotion regulation abilities. Although resting RSA has been associated with both concurrent and prospective affective responses to stress, the impact of RSA reactivity on emotional responses to stress is inconsistent across studies. The type of emotional stimuli used to elicit these phasic RSA responses may influence the adaptive value of RSA reactivity. We propose that RSA reactivity to a personally relevant worry-based stressor might forecast future affective responses to stress. To evaluate whether resting RSA and RSA reactivity to worry inductions predict stress-related increases in psychological distress, an academic stress model was used to prospectively examine changes in psychological distress from the well-defined low- and high-stress periods. During the low-stress period, 76 participants completed self-report mood measures and had their RSA assessed during a resting baseline, free worry period and worry catastrophizing interview. Participants completed another mood assessment during the high-stress period. Results indicated that baseline psychological distress predicted larger decreases in RSA during the worry inductions. Lower resting RSA and greater RSA suppression to the worry inductions at baseline prospectively predicted larger increases in psychological distress from the low- to high-stress period, even after accounting for the impact of baseline distress on RSA. These results provide further evidence that RSA may represent a unique index of emotion regulation abilities in times of stress.

Bending induced electrical response variations in ultra-thin flexible chips and device modeling

NASA Astrophysics Data System (ADS)

Heidari, Hadi; Wacker, Nicoleta; Dahiya, Ravinder

2017-09-01

Electronics that conform to 3D surfaces are attracting wider attention from both academia and industry. The research in the field has, thus far, focused primarily on showcasing the efficacy of various materials and fabrication methods for electronic/sensing devices on flexible substrates. As the device response changes are bound to change with stresses induced by bending, the next step will be to develop the capacity to predict the response of flexible systems under various bending conditions. This paper comprehensively reviews the effects of bending on the response of devices on ultra-thin chips in terms of variations in electrical parameters such as mobility, threshold voltage, and device performance (static and dynamic). The discussion also includes variations in the device response due to crystal orientation, applied mechanics, band structure, and fabrication processes. Further, strategies for compensating or minimizing these bending-induced variations have been presented. Following the in-depth analysis, this paper proposes new mathematical relations to simulate and predict the device response under various bending conditions. These mathematical relations have also been used to develop new compact models that have been verified by comparing simulation results with the experimental values reported in the recent literature. These advances will enable next generation computer-aided-design tools to meet the future design needs in flexible electronics.

The measurement of ultrasound scattering from individual micron-sized objects and its application in single cell scattering.

PubMed

Falou, Omar; Rui, Min; El Kaffas, Ahmed; Kumaradas, J Carl; Kolios, Michael C

2010-08-01

The measurement of the ultrasound backscatter from individual micron-sized objects such as cells is required for various applications such as tissue characterization. However, performing such a measurement remains a challenge. For example, the presence of air bubbles in a suspension of cells during the measurements may lead to the incorrect interpretation of the acoustic signals. This work introduces a technique for measuring the ultrasound backscatter from individual micron-sized objects by combining a microinjection system with a co-registered optical microscope and an ultrasound imaging device. This allowed the measurement of the ultrasound backscatter response from a single object under optical microscope guidance. The optical and ultrasonic data were used to determine the size of the object and to deduce its backscatter responses, respectively. In order to calibrate the system, the backscatter frequency responses from polystyrene microspheres were measured and compared to theoretical predictions. A very good agreement was found between the measured backscatter responses of individual microspheres and theoretical predictions of an elastic sphere. The backscatter responses from single OCI-AML-5 cells were also investigated. It was found that the backscatter responses from AML cells are best modeled using the fluid sphere model. The advantages, limitations, and future applications of the developed technique are discussed.

Climate Information Responding to User Needs (CIRUN)

NASA Astrophysics Data System (ADS)

Busalacchi, A. J.

2009-05-01

For the past several decades many different US agencies have been involved in collecting Earth observations, e.g., NASA, NOAA, DoD, USGS, USDA. More recently, the US has led the international effort to design a Global Earth Observation System of Systems (GEOSS). Yet, there has been little substantive progress at the synthesis and integration of the various research and operational, space-based and in situ, observations. Similarly, access to such a range of observations across the atmosphere, ocean, and land surface remains fragmented. With respect to prediction of the Earth System, the US has not developed a comprehensive strategy. For climate, the US (e.g., NOAA, NASA, DoE) has taken a two-track strategy. At the more immediate time scale, coupled ocean-atmosphere models of the physical climate system have built upon the tradition of daily numerical weather prediction in order to extend the forecast window to seasonal to interannual times scales. At the century time scale, the nascent development of Earth System models, combining components of the physical climate system with biogeochemical cycles, are being used to provide future climate change projections in response to anticipated greenhouse gas forcings. Between these to two approaches to prediction lies a key deficiency of interest to decision makers, especially as it pertains to adaptation, i.e., deterministic prediction of the Earth System at time scales from days to decades with spatial scales from global to regional. One of many obstacles to be overcome is the design of present day observation and prediction products based on user needs. To date, most of such products have evolved from the technology and research "push" rather than the user or stakeholder "pull". In the future as planning proceeds for a national climate service, emphasis must be given to a more coordinated approach in which stakeholders' needs help design future Earth System observational and prediction products, and similarly, such products need to be tailored to provide decision support.

Viewing Marine Bacteria, Their Activity and Response to Environmental Drivers from Orbit

PubMed Central

Grimes, D. Jay; Ford, Tim E.; Colwell, Rita R.; Baker-Austin, Craig; Martinez-Urtaza, Jaime; Subramaniam, Ajit; Capone, Douglas G.

2014-01-01

Satellite-based remote sensing of marine microorganisms has become a useful tool in predicting human health risks associated with these microscopic targets. Early applications were focused on harmful algal blooms, but more recently methods have been developed to interrogate the ocean for bacteria. As satellite-based sensors have become more sophisticated and our ability to interpret information derived from these sensors has advanced, we have progressed from merely making fascinating pictures from space to developing process models with predictive capability. Our understanding of the role of marine microorganisms in primary production and global elemental cycles has been vastly improved as has our ability to use the combination of remote sensing data and models to provide early warning systems for disease outbreaks. This manuscript will discuss current approaches to monitoring cyanobacteria and vibrios, their activity and response to environmental drivers, and will also suggest future directions. PMID:24477922

Predicting consumer behavior: using novel mind-reading approaches.

PubMed

Calvert, Gemma A; Brammer, Michael J

2012-01-01

Advances in machine learning as applied to functional magnetic resonance imaging (fMRI) data offer the possibility of pretesting and classifying marketing communications using unbiased pattern recognition algorithms. By using these algorithms to analyze brain responses to brands, products, or existing marketing communications that either failed or succeeded in the marketplace and identifying the patterns of brain activity that characterize success or failure, future planned campaigns or new products can now be pretested to determine how well the resulting brain responses match the desired (successful) pattern of brain activity without the need for verbal feedback. This major advance in signal processing is poised to revolutionize the application of these brain-imaging techniques in the marketing sector by offering greater accuracy of prediction in terms of consumer acceptance of new brands, products, and campaigns at a speed that makes them accessible as routine pretesting tools that will clearly demonstrate return on investment.

Viewing marine bacteria, their activity and response to environmental drivers from orbit: satellite remote sensing of bacteria.

PubMed

Grimes, D Jay; Ford, Tim E; Colwell, Rita R; Baker-Austin, Craig; Martinez-Urtaza, Jaime; Subramaniam, Ajit; Capone, Douglas G

2014-04-01

Satellite-based remote sensing of marine microorganisms has become a useful tool in predicting human health risks associated with these microscopic targets. Early applications were focused on harmful algal blooms, but more recently methods have been developed to interrogate the ocean for bacteria. As satellite-based sensors have become more sophisticated and our ability to interpret information derived from these sensors has advanced, we have progressed from merely making fascinating pictures from space to developing process models with predictive capability. Our understanding of the role of marine microorganisms in primary production and global elemental cycles has been vastly improved as has our ability to use the combination of remote sensing data and models to provide early warning systems for disease outbreaks. This manuscript will discuss current approaches to monitoring cyanobacteria and vibrios, their activity and response to environmental drivers, and will also suggest future directions.

Structure-based energetics of protein interfaces guide Foot-and-Mouth Disease virus vaccine design

PubMed Central

Scott, Katherine; Burman, Alison; Loureiro, Silvia; Ren, Jingshan; Porta, Claudine; Ginn, Helen M.; Jackson, Terry; Perez-Martin, Eva; Siebert, C. Alistair; Paul, Guntram; Huiskonen, Juha T.; Jones, Ian M.; Esnouf, Robert M.; Fry, Elizabeth E.; Maree, Francois F.; Charleston, Bryan; Stuart, David I.

2018-01-01

Summary Virus capsids are primed for disassembly yet capsid integrity is key to generating a protective immune response. Here we devise a computational method to assess relative stability of protein-protein interfaces and use it to design improved candidate vaccines for two of the least stable, but globally important, serotypes of Foot-and-Mouth Disease virus (FMDV), O and SAT2. FMDV capsids comprise identical pentameric protein subunits held together by tenuous non-covalent interactions, and are often unstable. Chemically inactivated or recombinant empty capsids, which could form the basis of future vaccines, are even less stable than live virus. We use a novel restrained molecular dynamics strategy, to rank mutations predicted to strengthen the pentamer interfaces to produce stabilized capsids. Structural analyses and stability assays confirmed the predictions, and vaccinated animals generated improved neutralising antibody responses to stabilised particles over parental viruses and wild-type capsids. PMID:26389739

The cognitive bases of the development of past and future episodic cognition in preschoolers.

PubMed

Ünal, Gülten; Hohenberger, Annette

2017-10-01

The aim of this study was to use a minimalist framework to examine the joint development of past and future episodic cognition and their underlying cognitive abilities in 3- to 5-year-old Turkish preschoolers. Participants engaged in two main tasks, a what-where-when (www) task to measure episodic memory and a future prediction task to measure episodic future thinking. Three additional tasks were used for predicting children's performance in the two main tasks: a temporal language task, an executive function task, and a spatial working memory task. Results indicated that past and future episodic tasks were significantly correlated with each other even after controlling for age. Hierarchical multiple regressions showed that, after controlling for age, the www task was predicted by executive functions, possibly supporting binding of episodic information and by linguistic abilities. The future prediction task was predicted by linguistic abilities alone, underlining the importance of language for episodic past and future thinking. Copyright © 2017 Elsevier Inc. All rights reserved.

Neural and personality correlates of individual differences related to the effects of acute tryptophan depletion on future reward evaluation.

PubMed

Demoto, Yoshihiko; Okada, Go; Okamoto, Yasumasa; Kunisato, Yoshihiko; Aoyama, Shiori; Onoda, Keiichi; Munakata, Ayumi; Nomura, Michio; Tanaka, Saori C; Schweighofer, Nicolas; Doya, Kenji; Yamawaki, Shigeto

2012-01-01

In general, humans tend to discount the value of delayed reward. An increase in the rate of discounting leads to an inability to select a delayed reward over a smaller immediate reward (reward-delay impulsivity). Although deficits in the serotonergic system are implicated in this reward-delay impulsivity, there is individual variation in response to serotonin depletion. The aim of the present study was to investigate whether the effects of serotonin depletion on the ability to evaluate future reward are affected by individual personality traits or brain activation. Personality traits were assessed using the NEO-Five Factor Inventory and Temperament and Character Inventory. The central serotonergic levels of 16 healthy volunteers were manipulated by dietary tryptophan depletion. Subjects performed a delayed reward choice task that required the continuous estimation of reward value during functional magnetic resonance imaging scanning. Discounting rates were increased in 9 participants, but were unchanged or decreased in 7 participants in response to tryptophan depletion. Participants whose discounting rate was increased by tryptophan depletion had significantly higher neuroticism and lower self-directedness. Furthermore, tryptophan depletion differentially affected the groups in terms of hemodynamic responses to the value of predicted future reward in the right insula. These results suggest that individuals who have high neuroticism and low self-directedness as personality traits are particularly vulnerable to the effect of low serotonin on future reward evaluation accompanied by altered brain activation patterns. Copyright © 2012 S. Karger AG, Basel.

Predictive coding accelerates word recognition and learning in the early stages of language development.

PubMed

Ylinen, Sari; Bosseler, Alexis; Junttila, Katja; Huotilainen, Minna

2017-11-01

The ability to predict future events in the environment and learn from them is a fundamental component of adaptive behavior across species. Here we propose that inferring predictions facilitates speech processing and word learning in the early stages of language development. Twelve- and 24-month olds' electrophysiological brain responses to heard syllables are faster and more robust when the preceding word context predicts the ending of a familiar word. For unfamiliar, novel word forms, however, word-expectancy violation generates a prediction error response, the strength of which significantly correlates with children's vocabulary scores at 12 months. These results suggest that predictive coding may accelerate word recognition and support early learning of novel words, including not only the learning of heard word forms but also their mapping to meanings. Prediction error may mediate learning via attention, since infants' attention allocation to the entire learning situation in natural environments could account for the link between prediction error and the understanding of word meanings. On the whole, the present results on predictive coding support the view that principles of brain function reported across domains in humans and non-human animals apply to language and its development in the infant brain. A video abstract of this article can be viewed at: http://hy.fi/unitube/video/e1cbb495-41d8-462e-8660-0864a1abd02c. [Correction added on 27 January 2017, after first online publication: The video abstract link was added.]. © 2016 John Wiley & Sons Ltd.

Recent and possible future variations in the North American Monsoon

USGS Publications Warehouse

Hoell, Andrew; Funk, Chris; Barlow, Mathew; Shukla, Shraddhanand

2016-01-01

The dynamics and recent and possible future changes of the June–September rainfall associated with the North American Monsoon (NAM) are reviewed in this chapter. Our analysis as well as previous analyses of the trend in June–September precipitation from 1948 until 2010 indicate significant precipitation increases over New Mexico and the core NAM region, and significant precipitation decreases over southwest Mexico. The trends in June–September precipitation have been forced by anomalous cyclonic circulation centered at 15°N latitude over the eastern Pacific Ocean. The anomalous cyclonic circulation is responsible for changes in the flux of moisture and the divergence of moisture flux within the core NAM region. Future climate projections using the Coupled Model Intercomparison Project Phase 5 (CMIP5) models, as part of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5), support the observed analyses of a later shift in the monsoon season in the presence of increased greenhouse gas concentrations in the atmosphere under the RCP8.5 scenario. The CMIP5 models under the RCP8.5 scenario predict significant NAM-related rainfall decreases during June and July and predict significant NAM-related rainfall increases during September and October.

Range shifts or extinction? Ancient DNA and distribution modelling reveal past and future responses to climate warming in cold-adapted birds.

PubMed

Lagerholm, Vendela K; Sandoval-Castellanos, Edson; Vaniscotte, Amélie; Potapova, Olga R; Tomek, Teresa; Bochenski, Zbigniew M; Shepherd, Paul; Barton, Nick; Van Dyck, Marie-Claire; Miller, Rebecca; Höglund, Jacob; Yoccoz, Nigel G; Dalén, Love; Stewart, John R

2017-04-01

Global warming is predicted to cause substantial habitat rearrangements, with the most severe effects expected to occur in high-latitude biomes. However, one major uncertainty is whether species will be able to shift their ranges to keep pace with climate-driven environmental changes. Many recent studies on mammals have shown that past range contractions have been associated with local extinctions rather than survival by habitat tracking. Here, we have used an interdisciplinary approach that combines ancient DNA techniques, coalescent simulations and species distribution modelling, to investigate how two common cold-adapted bird species, willow and rock ptarmigan (Lagopus lagopus and Lagopus muta), respond to long-term climate warming. Contrary to previous findings in mammals, we demonstrate a genetic continuity in Europe over the last 20 millennia. Results from back-casted species distribution models suggest that this continuity may have been facilitated by uninterrupted habitat availability and potentially also the greater dispersal ability of birds. However, our predictions show that in the near future, some isolated regions will have little suitable habitat left, implying a future decrease in local populations at a scale unprecedented since the last glacial maximum. © 2016 John Wiley & Sons Ltd.

Exaggerated Exercise Blood Pressure Response and Future Cardiovascular Disease.

PubMed

Tzemos, Nikolaos; Lim, Pitt O; Mackenzie, Isla S; MacDonald, Thomas M

2015-11-01

Exaggerated blood pressure (BP) response to exercise predicts future hypertension. However, there is considerable lack of understanding regarding the mechanism of how this abnormal response is generated, and how it relates to the future establishment of cardiovascular disease. The authors studied 82 healthy male volunteers without cardiovascular risk factors. The participants were categorized into two age-matched groups depending on their exercise systolic BP (ExSBP) rise after 3 minutes of exercise using a submaximal step test: exaggerated ExSBP group (hyper-responders [peak SBP ≥ 180 mm Hg]) and low ExSBP responder group (hypo-responders [peak SBP <180 mm Hg]). Forearm venous occlusion plethysmography and intra-arterial infusions of acetylcholine (ACh), N(G)-monomethyl-L-arginine (L-NMMA), sodium nitroprusside (SNP), and norepinephrine (NE) were used to assess vascular reactivity. Proximal aortic compliance was assessed with ultrasound, and neurohormonal blood sampling was performed at rest and during peak exercise. The hyper-responder group exhibited a significantly lower increase in forearm blood flow (FBF) with ACh compared with the hypo-responder group (ΔFBF 215% [14] vs 332.3% [28], mean [standard error of the mean]; P<.001), as well as decreased proximal aortic compliance. The vasoconstrictive response to L-NMMA was significantly impaired in the hyper-responder group in comparison to the hypo-responder group (ΔFBF -40.2% [1.6] vs -50.2% [2.6]; P<.05). In contrast, the vascular response to SNP and NE were comparable in both groups. Peak exercise plasma angiotensin II levels were significantly higher in the hyper-responder group (31 [1] vs 23 [2] pg/mL, P=.01). An exaggerated BP response to exercise is related to endothelial dysfunction, decreased proximal aortic compliance, and increased exercise-related neurohormonal activation, the constellation of which may explain future cardiovascular disease. © 2015 Wiley Periodicals, Inc.

Resolution Dependence of Future Tropical Cyclone Projections of CAM5.1 in the U.S. CLIVAR Hurricane Working Group Idealized Configurations

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

Wehner, Michael; ., Prabhat; Reed, Kevin A.

The four idealized configurations of the U.S. CLIVAR Hurricane Working Group are integrated using the global Community Atmospheric Model version 5.1 at two different horizontal resolutions, approximately 100 and 25 km. The publicly released 0.9° × 1.3° configuration is a poor predictor of the sign of the 0.23° × 0.31° model configuration’s change in the total number of tropical storms in a warmer climate. However, it does predict the sign of the higher-resolution configuration’s change in the number of intense tropical cyclones in a warmer climate. In the 0.23° × 0.31° model configuration, both increased CO 2 concentrations and elevatedmore » sea surface temperature (SST) independently lower the number of weak tropical storms and shorten their average duration. Conversely, increased SST causes more intense tropical cyclones and lengthens their average duration, resulting in a greater number of intense tropical cyclone days globally. Increased SST also increased maximum tropical storm instantaneous precipitation rates across all storm intensities. It was found that while a measure of maximum potential intensity based on climatological mean quantities adequately predicts the 0.23° × 0.31° model’s forced response in its most intense simulated tropical cyclones, a related measure of cyclogenesis potential fails to predict the model’s actual cyclogenesis response to warmer SSTs. These analyses lead to two broader conclusions: 1) Projections of future tropical storm activity obtained by a direct tracking of tropical storms simulated by coarse-resolution climate models must be interpreted with caution. 2) Projections of future tropical cyclogenesis obtained from metrics of model behavior that are based solely on changes in long-term climatological fields and tuned to historical records must also be interpreted with caution.« less

Using Streamflow and Stream Temperature to Assess the Potential Responses of Freshwater Fish to Climate Change

NASA Astrophysics Data System (ADS)

VanCompernolle, M.; Ficklin, D. L.; Knouft, J.

2017-12-01

Streamflow and stream temperature are key variables influencing growth, reproduction, and mortality of freshwater fish. Climate-induced changes in these variables are expected to alter the structure and function of aquatic ecosystems. Using Maxent, a species distribution model (SDM) based on the principal of maximum entropy, we predicted potential distributional responses of 100 fish species in the Mobile River Basin (MRB) to changes in climate based on contemporary and future streamflow and stream temperature estimates. Geologic, topographic, and landcover data were also included in each SDM to determine the contribution of these physical variables in defining areas of suitable habitat for each species. Using an ensemble of Global Climate Model (GCM) projections under a high emissions scenario, predicted distributions for each species across the MRB were produced for both a historical time period, 1975-1994, and a future time period, 2060-2079, and changes in total area and the percent change in historical suitable habitat for each species were calculated. Results indicate that flow (28%), temperature (29%), and geology (29%), on average, contribute evenly to determining areas of suitable habitat for fish species in the MRB, with landcover and slope playing more limited roles. Temperature contributed slightly more predictive ability to SDMs (31%) for the 77 species experiencing overall declines in areas of suitable habitat, but only 21% for the 23 species gaining habitat across all GCMs. Species are expected to lose between 15-24% of their historical suitable habitat, with threatened and endangered species losing 22-30% and those endemic to the MRB losing 19-28%. Sculpins (Cottidae) are expected to lose the largest amount of historical habitat (up to 84%), while pygmy sunfish (Elassomatidae) are expected to lose less than 1% of historical habitat. Understanding which species may be at risk of habitat loss under future projections of climate change can help fisheries managers better prepare for potential alterations in species composition not only within the MRB, but other watersheds throughout the world.

Resolution Dependence of Future Tropical Cyclone Projections of CAM5.1 in the U.S. CLIVAR Hurricane Working Group Idealized Configurations

DOE PAGES

Wehner, Michael; ., Prabhat; Reed, Kevin A.; ...

2015-05-12

The four idealized configurations of the U.S. CLIVAR Hurricane Working Group are integrated using the global Community Atmospheric Model version 5.1 at two different horizontal resolutions, approximately 100 and 25 km. The publicly released 0.9° × 1.3° configuration is a poor predictor of the sign of the 0.23° × 0.31° model configuration’s change in the total number of tropical storms in a warmer climate. However, it does predict the sign of the higher-resolution configuration’s change in the number of intense tropical cyclones in a warmer climate. In the 0.23° × 0.31° model configuration, both increased CO 2 concentrations and elevatedmore » sea surface temperature (SST) independently lower the number of weak tropical storms and shorten their average duration. Conversely, increased SST causes more intense tropical cyclones and lengthens their average duration, resulting in a greater number of intense tropical cyclone days globally. Increased SST also increased maximum tropical storm instantaneous precipitation rates across all storm intensities. It was found that while a measure of maximum potential intensity based on climatological mean quantities adequately predicts the 0.23° × 0.31° model’s forced response in its most intense simulated tropical cyclones, a related measure of cyclogenesis potential fails to predict the model’s actual cyclogenesis response to warmer SSTs. These analyses lead to two broader conclusions: 1) Projections of future tropical storm activity obtained by a direct tracking of tropical storms simulated by coarse-resolution climate models must be interpreted with caution. 2) Projections of future tropical cyclogenesis obtained from metrics of model behavior that are based solely on changes in long-term climatological fields and tuned to historical records must also be interpreted with caution.« less

Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.

PubMed

Averill, Colin; Waring, Bonnie G; Hawkes, Christine V

2016-05-01

Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442-887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios. © 2016 John Wiley & Sons Ltd.

Recent advances in understanding idiopathic pulmonary fibrosis

PubMed Central

Daccord, Cécile; Maher, Toby M.

2016-01-01

Despite major research efforts leading to the recent approval of pirfenidone and nintedanib, the dismal prognosis of idiopathic pulmonary fibrosis (IPF) remains unchanged. The elaboration of international diagnostic criteria and disease stratification models based on clinical, physiological, radiological, and histopathological features has improved the accuracy of IPF diagnosis and prediction of mortality risk. Nevertheless, given the marked heterogeneity in clinical phenotype and the considerable overlap of IPF with other fibrotic interstitial lung diseases (ILDs), about 10% of cases of pulmonary fibrosis remain unclassifiable. Moreover, currently available tools fail to detect early IPF, predict the highly variable course of the disease, and assess response to antifibrotic drugs. Recent advances in understanding the multiple interrelated pathogenic pathways underlying IPF have identified various molecular phenotypes resulting from complex interactions among genetic, epigenetic, transcriptional, post-transcriptional, metabolic, and environmental factors. These different disease endotypes appear to confer variable susceptibility to the condition, differing risks of rapid progression, and, possibly, altered responses to therapy. The development and validation of diagnostic and prognostic biomarkers are necessary to enable a more precise and earlier diagnosis of IPF and to improve prediction of future disease behaviour. The availability of approved antifibrotic therapies together with potential new drugs currently under evaluation also highlights the need for biomarkers able to predict and assess treatment responsiveness, thereby allowing individualised treatment based on risk of progression and drug response. This approach of disease stratification and personalised medicine is already used in the routine management of many cancers and provides a potential road map for guiding clinical care in IPF. PMID:27303645

Sibling response to initial antiepileptic medication predicts treatment success.

PubMed

Ueda, Keisuke; Serajee, Fatema; Rajlich, Jan; Taraman, Sharief; Steckling, Lindsey; Huq, Ahm M

2017-10-01

A recent study focusing on a response to antiepileptic drugs (AED) among siblings for epilepsy showed a similar response among epileptic siblings to specific AEDs or AED combinations. Currently, however, family history of treatment response to AEDs is not readily employed in deciding which initial medication to use when treating patients with epilepsy. We tested the hypothesis that sibling response to initial AED predicts treatment success. Presumed siblings were identified from a single-center database of patients diagnosed with epilepsy by matching last name, address, and name of parent(s). We identified 28 sibling pairs and two sibling trios with epilepsy. Seventeen of these sibling pairs were started on the same initial AED, with 15 sibling pairs having the same type of epilepsy. The remaining 11 pairs were started on a different initial AED, with 8 of these sibling pairs having the same type of epilepsy. Subjects with seizure freedom for a period of ≥1year were classified as a "responder". When at least one of the sibling pair responded to an initial AED, the proportion of the other siblings also responding to the initial AED was significantly higher if the siblings were treated with the same AED (8/11) compared to siblings who were treated with different AED (1/10) (Fisher's exact test, p-value=0.0075). These findings suggest that sibling response to initial AED is predictive of the success of AED therapy. This study is limited by a small cohort and retrospective design. Future, larger prospective studies are needed to reproduce and further validate these findings. Copyright © 2017. Published by Elsevier B.V.

An experimental design for quantification of cardiovascular responses to music stimuli in humans.

PubMed

Chang, S-H; Luo, C-H; Yeh, T-L

2004-01-01

There have been several researches on the relationship between music and human physiological or psychological responses. However, there are cardiovascular index factors that have not been explored quantitatively due to the qualitative nature of acoustic stimuli. This study proposes and demonstrates an experimental design for quantification of cardiovascular responses to music stimuli in humans. The system comprises two components: a unit for generating and monitoring quantitative acoustic stimuli and a portable autonomic nervous system (ANS) analysis unit for quantitative recording and analysis of the cardiovascular responses. The experimental results indicate that the proposed system can exactly achieve the goal of full control and measurement for the music stimuli, and also effectively support many quantitative indices of cardiovascular response in humans. In addition, the analysis results are discussed and predicted in the future clinical research.

A joint computational and experimental study to evaluate Inconel-sheathed thermocouple performance in flames.

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

Brundage, Aaron L.; Nicolette, Vernon F.; Donaldson, A. Burl

2005-09-01

A joint experimental and computational study was performed to evaluate the capability of the Sandia Fire Code VULCAN to predict thermocouple response temperature. Thermocouple temperatures recorded by an Inconel-sheathed thermocouple inserted into a near-adiabatic flat flame were predicted by companion VULCAN simulations. The predicted thermocouple temperatures were within 6% of the measured values, with the error primarily attributable to uncertainty in Inconel 600 emissivity and axial conduction losses along the length of the thermocouple assembly. Hence, it is recommended that future thermocouple models (for Inconel-sheathed designs) include a correction for axial conduction. Given the remarkable agreement between experiment and simulation,more » it is recommended that the analysis be repeated for thermocouples in flames with pollutants such as soot.« less

Prediction as a humanitarian and pragmatic contribution from human cognitive neuroscience.

PubMed

Gabrieli, John D E; Ghosh, Satrajit S; Whitfield-Gabrieli, Susan

2015-01-07

Neuroimaging has greatly enhanced the cognitive neuroscience understanding of the human brain and its variation across individuals (neurodiversity) in both health and disease. Such progress has not yet, however, propelled changes in educational or medical practices that improve people's lives. We review neuroimaging findings in which initial brain measures (neuromarkers) are correlated with or predict future education, learning, and performance in children and adults; criminality; health-related behaviors; and responses to pharmacological or behavioral treatments. Neuromarkers often provide better predictions (neuroprognosis), alone or in combination with other measures, than traditional behavioral measures. With further advances in study designs and analyses, neuromarkers may offer opportunities to personalize educational and clinical practices that lead to better outcomes for people. Copyright © 2015 Elsevier Inc. All rights reserved.

Background Predictors and Event-Specific Characteristics of Sexual Aggression Incidents: The Roles of Alcohol and Other Factors.

PubMed

Davis, Kelly Cue; Danube, Cinnamon L; Stappenbeck, Cynthia A; Norris, Jeanette; George, William H

2015-08-01

Sexual assault in the United States is an important public health concern. Using prospective longitudinal methods and responses from 217 community men, we examined whether background characteristics predicted subsequent sexual aggression (SA) perpetration during a 3-month follow-up period. We also examined event-specific characteristics of reported SA occurrences. Consistent with predictions, SA perpetration history, aggressive and impulsive personality traits, rape myth attitudes, and alcohol expectancies predicted SA (both non- and alcohol-involved) at follow-up. In addition, alcohol-involved assaults occurred more often with casual (vs. steady) partners but were more likely to involve condom use with casual (vs. steady) partners. Results suggest important avenues for future research and SA prevention efforts. © The Author(s) 2015.

Belief state representation in the dopamine system.

PubMed

Babayan, Benedicte M; Uchida, Naoshige; Gershman, Samuel J

2018-05-14

Learning to predict future outcomes is critical for driving appropriate behaviors. Reinforcement learning (RL) models have successfully accounted for such learning, relying on reward prediction errors (RPEs) signaled by midbrain dopamine neurons. It has been proposed that when sensory data provide only ambiguous information about which state an animal is in, it can predict reward based on a set of probabilities assigned to hypothetical states (called the belief state). Here we examine how dopamine RPEs and subsequent learning are regulated under state uncertainty. Mice are first trained in a task with two potential states defined by different reward amounts. During testing, intermediate-sized rewards are given in rare trials. Dopamine activity is a non-monotonic function of reward size, consistent with RL models operating on belief states. Furthermore, the magnitude of dopamine responses quantitatively predicts changes in behavior. These results establish the critical role of state inference in RL.

Adaptive responses reveal contemporary and future ecotypes in a desert shrub

USGS Publications Warehouse

Richardson, Bryce A.; Kitchen, Stanley G.; Pendleton, Rosemary L.; Pendleton, Burton K.; Germino, Matthew J.; Rehfeldt, Gerald E.; Meyer, Susan E.

2014-01-01

Interacting threats to ecosystem function, including climate change, wildfire, and invasive species necessitate native plant restoration in desert ecosystems. However, native plant restoration efforts often remain unguided by ecological genetic information. Given that many ecosystems are in flux from climate change, restoration plans need to account for both contemporary and future climates when choosing seed sources. In this study we analyze vegetative responses, including mortality, growth, and carbon isotope ratios in two blackbrush (Coleogyne ramosissima) common gardens that included 26 populations from a range-wide collection. This shrub occupies ecotones between the warm and cold deserts of Mojave and Colorado Plateau ecoregions in western North America. The variation observed in the vegetative responses of blackbrush populations was principally explained by grouping populations by ecoregions and by regression with site-specific climate variables. Aridity weighted by winter minimum temperatures best explained vegetative responses; Colorado Plateau sites were usually colder and drier than Mojave sites. The relationship between climate and vegetative response was mapped within the boundaries of the species–climate space projected for the contemporary climate and for the decade surrounding 2060. The mapped ecological genetic pattern showed that genetic variation could be classified into cool-adapted and warm-adapted ecotypes, with populations often separated by steep clines. These transitions are predicted to occur in both the Mojave Desert and Colorado Plateau ecoregions. While under contemporary conditions the warm-adapted ecotype occupies the majority of climate space, climate projections predict that the cool-adapted ecotype could prevail as the dominant ecotype as the climate space of blackbrush expands into higher elevations and latitudes. This study provides the framework for delineating climate change-responsive seed transfer guidelines, which are needed to inform restoration and management planning. We propose four transfer zones in blackbrush that correspond to areas currently dominated by cool-adapted and warm-adapted ecotypes in each of the two ecoregions.

Adaptive responses reveal contemporary and future ecotypes in a desert shrub.

PubMed

Richardson, Bryce A; Kitchen, Stanley G; Pendleton, Rosemary L; Pendleton, Burton K; Germino, Matthew J; Rehfeldt, Gerald E; Meyer, Susan E

2014-03-01

Interacting threats to ecosystem function, including climate change, wildfire, and invasive species necessitate native plant restoration in desert ecosystems. However, native plant restoration efforts often remain unguided by ecological genetic information. Given that many ecosystems are in flux from climate change, restoration plans need to account for both contemporary and future climates when choosing seed sources. In this study we analyze vegetative responses, including mortality, growth, and carbon isotope ratios in two blackbrush (Coleogyne ramosissima) common gardens that included 26 populations from a range-wide collection. This shrub occupies ecotones between the warm and cold deserts of Mojave and Colorado Plateau ecoregions in western North America. The variation observed in the vegetative responses of blackbrush populations was principally explained by grouping populations by ecoregions and by regression with site-specific climate variables. Aridity weighted by winter minimum temperatures best explained vegetative responses; Colorado Plateau sites were usually colder and drier than Mojave sites. The relationship between climate and vegetative response was mapped within the boundaries of the species-climate space projected for the contemporary climate and for the decade surrounding 2060. The mapped ecological genetic pattern showed that genetic variation could be classified into cool-adapted and warm-adapted ecotypes, with populations often separated by steep dines. These transitions are predicted to occur in both the Mojave Desert and Colorado Plateau ecoregions. While under contemporary conditions the warm-adapted ecotype occupies the majority of climate space, climate projections predict that the cool-adapted ecotype could prevail as the dominant ecotype as the climate space of blackbrush expands into higher elevations and latitudes. This study provides the framework for delineating climate change-responsive seed transfer guidelines, which are needed to inform restoration and management planning. We propose four transfer zones in blackbrush that correspond to areas currently dominated by cool-adapted and warm-adapted ecotypes in each of the two ecoregions.

Exercise blood pressure and the risk of future hypertension.

PubMed

Holmqvist, L; Mortensen, L; Kanckos, C; Ljungman, C; Mehlig, K; Manhem, K

2012-12-01

The aim of this prospective cohort study was to identify which blood pressure measurement during exercise is the best predictor of future hypertension. Further we aimed to create a risk chart to facilitate the evaluation of blood pressure reaction during exercise testing. A number (n=1047) of exercise tests by bicycle ergometry, performed in 1996 and 1997 were analysed. In 2007-2008, 606 patients without hypertension at the time of the exercise test were sent a questionnaire aimed to identify current hypertension. The response rate was 58% (n=352). During the 10-12 years between exercise test and questionnaire, 23% developed hypertension. The strongest predictors of future hypertension were systolic blood pressure (SBP) before exercise (odds ratios (OR) 1.63 (1.31-2.01) for 10 mm Hg difference) in combination with the increase of SBP over time during exercise testing (OR 1.12 (1.01-1.24) steeper increase for every 1 mm Hg min(-1)). A high SBP before exercise and a steep rise in SBP over time represented a higher risk of developing hypertension. A risk chart based on SBP before exercise, increase of SBP over time and body mass index was created. SBP before exercise, maximal SBP during exercise and SBP at 100 W were significant single predictors of future hypertension and the prediction by maximal SBP was improved by adjusting for time/power at which SBP max was reached during exercise testing. Recovery ratio (maximal SBP/SBP 4 min after exercise) was not predictive of future hypertension.

Aggressive behavior and change in salivary testosterone concentrations predict willingness to engage in a competitive task.

PubMed

Carré, Justin M; McCormick, Cheryl M

2008-08-01

The current study investigated relationships among aggressive behavior, change in salivary testosterone concentrations, and willingness to engage in a competitive task. Thirty-eight male participants provided saliva samples before and after performing the Point Subtraction Aggression Paradigm (a laboratory measure that provides opportunity for aggressive and defensive behavior while working for reward; all three involve pressing specific response keys). Baseline testosterone concentrations were not associated with aggressive responding. However, aggressive responding (but not point reward or point protection responding) predicted the pre- to post-PSAP change in testosterone: Those with the highest aggressive responding had the largest percent increase in testosterone concentrations. Together, aggressive responding and change in testosterone predicted willingness to compete following the PSAP. Controlling for aggression, men who showed a rise in testosterone were more likely to choose to compete again (p=0.03) and controlling for testosterone change, men who showed the highest level of aggressive responding were more likely to choose the non-competitive task (p=0.02). These results indicate that situation-specific aggressive behavior and testosterone responsiveness are functionally relevant predictors of future social behavior.

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.