Dannie Heineman Prize for Mathematical Physics: Applying mathematical techniques to solve important problems in quantum theory

NASA Astrophysics Data System (ADS)

Bender, Carl

2017-01-01

The theory of complex variables is extremely useful because it helps to explain the mathematical behavior of functions of a real variable. Complex variable theory also provides insight into the nature of physical theories. For example, it provides a simple and beautiful picture of quantization and it explains the underlying reason for the divergence of perturbation theory. By using complex-variable methods one can generalize conventional Hermitian quantum theories into the complex domain. The result is a new class of parity-time-symmetric (PT-symmetric) theories whose remarkable physical properties have been studied and verified in many recent laboratory experiments.

Does sexual selection explain human sex differences in aggression?

PubMed

Archer, John

2009-08-01

I argue that the magnitude and nature of sex differences in aggression, their development, causation, and variability, can be better explained by sexual selection than by the alternative biosocial version of social role theory. Thus, sex differences in physical aggression increase with the degree of risk, occur early in life, peak in young adulthood, and are likely to be mediated by greater male impulsiveness, and greater female fear of physical danger. Male variability in physical aggression is consistent with an alternative life history perspective, and context-dependent variability with responses to reproductive competition, although some variability follows the internal and external influences of social roles. Other sex differences, in variance in reproductive output, threat displays, size and strength, maturation rates, and mortality and conception rates, all indicate that male aggression is part of a sexually selected adaptive complex. Physical aggression between partners can be explained using different evolutionary principles, arising from the conflicts of interest between males and females entering a reproductive alliance, combined with variability following differences in societal gender roles. In this case, social roles are particularly important since they enable both the relatively equality in physical aggression between partners from Western nations, and the considerable cross-national variability, to be explained.

The importance of environment vs. disturbance in the vegetation mosaic of central Arizona

Treesearch

Cynthia D. Huebner; John L. Vankat

2003-01-01

The vegetation of central Arizona is a mosaic of four vegetation types: chaparral, chaparral grassland, woodland, and woodland grassland. We analysed ten environmental variables, three disturbance variables, and five disturbance indicators to answer the question: What is the relative importance of environment and disturbance in explaining the vegetation pattern of our...

Disentangling the drivers of taxonomic and phylogenetic beta diversities in disturbed and undisturbed subtropical forests

NASA Astrophysics Data System (ADS)

Liu, Jinliang; Qian, Hong; Jin, Yi; Wu, Chuping; Chen, Jianhua; Yu, Shuquan; Wei, Xinliang; Jin, Xiaofeng; Liu, Jiajia; Yu, Mingjian

2016-10-01

Understanding the relative importance of dispersal limitation and environmental filtering processes in structuring the beta diversities of subtropical forests in human disturbed landscapes is still limited. Here we used taxonomic (TBD) and phylogenetic (PBD), including terminal PBD (PBDt) and basal PBD (PBDb), beta diversity indices to quantify the taxonomic and phylogenetic turnovers at different depths of evolutionary history in disturbed and undisturbed subtropical forests. Multiple linear regression model and distance-based redundancy analysis were used to disentangle the relative importance of environmental and spatial variables. Environmental variables were significantly correlated with TBD and PBDt metrics. Temperature and precipitation were major environmental drivers of beta diversity patterns, which explained 7-27% of the variance in TBD and PBDt, whereas the spatial variables independently explained less than 1% of the variation for all forests. The relative importance of environmental and spatial variables differed between disturbed and undisturbed forests (e.g., when Bray-Curtis was used as a beta diversity metric, environmental variable had a significant effect on beta diversity for disturbed forests but had no effect on undisturbed forests). We conclude that environmental filtering plays a more important role than geographical limitation and disturbance history in driving taxonomic and terminal phylogenetic beta diversity.

Disentangling the drivers of taxonomic and phylogenetic beta diversities in disturbed and undisturbed subtropical forests

PubMed Central

Liu, Jinliang; Qian, Hong; Jin, Yi; Wu, Chuping; Chen, Jianhua; Yu, Shuquan; Wei, Xinliang; Jin, Xiaofeng; Liu, Jiajia; Yu, Mingjian

2016-01-01

Understanding the relative importance of dispersal limitation and environmental filtering processes in structuring the beta diversities of subtropical forests in human disturbed landscapes is still limited. Here we used taxonomic (TBD) and phylogenetic (PBD), including terminal PBD (PBDt) and basal PBD (PBDb), beta diversity indices to quantify the taxonomic and phylogenetic turnovers at different depths of evolutionary history in disturbed and undisturbed subtropical forests. Multiple linear regression model and distance-based redundancy analysis were used to disentangle the relative importance of environmental and spatial variables. Environmental variables were significantly correlated with TBD and PBDt metrics. Temperature and precipitation were major environmental drivers of beta diversity patterns, which explained 7–27% of the variance in TBD and PBDt, whereas the spatial variables independently explained less than 1% of the variation for all forests. The relative importance of environmental and spatial variables differed between disturbed and undisturbed forests (e.g., when Bray-Curtis was used as a beta diversity metric, environmental variable had a significant effect on beta diversity for disturbed forests but had no effect on undisturbed forests). We conclude that environmental filtering plays a more important role than geographical limitation and disturbance history in driving taxonomic and terminal phylogenetic beta diversity. PMID:27775021

Reassessing regime shifts in the North Pacific: incremental climate change and commercial fishing are necessary for explaining decadal-scale biological variability.

PubMed

Litzow, Michael A; Mueter, Franz J; Hobday, Alistair J

2014-01-01

In areas of the North Pacific that are largely free of overfishing, climate regime shifts - abrupt changes in modes of low-frequency climate variability - are seen as the dominant drivers of decadal-scale ecological variability. We assessed the ability of leading modes of climate variability [Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO), Arctic Oscillation (AO), Pacific-North American Pattern (PNA), North Pacific Index (NPI), El Niño-Southern Oscillation (ENSO)] to explain decadal-scale (1965-2008) patterns of climatic and biological variability across two North Pacific ecosystems (Gulf of Alaska and Bering Sea). Our response variables were the first principle component (PC1) of four regional climate parameters [sea surface temperature (SST), sea level pressure (SLP), freshwater input, ice cover], and PCs 1-2 of 36 biological time series [production or abundance for populations of salmon (Oncorhynchus spp.), groundfish, herring (Clupea pallasii), shrimp, and jellyfish]. We found that the climate modes alone could not explain ecological variability in the study region. Both linear models (for climate PC1) and generalized additive models (for biology PC1-2) invoking only the climate modes produced residuals with significant temporal trends, indicating that the models failed to capture coherent patterns of ecological variability. However, when the residual climate trend and a time series of commercial fishery catches were used as additional candidate variables, resulting models of biology PC1-2 satisfied assumptions of independent residuals and out-performed models constructed from the climate modes alone in terms of predictive power. As measured by effect size and Akaike weights, the residual climate trend was the most important variable for explaining biology PC1 variability, and commercial catch the most important variable for biology PC2. Patterns of climate sensitivity and exploitation history for taxa strongly associated with biology PC1-2 suggest plausible mechanistic explanations for these modeling results. Our findings suggest that, even in the absence of overfishing and in areas strongly influenced by internal climate variability, climate regime shift effects can only be understood in the context of other ecosystem perturbations. © 2013 John Wiley & Sons Ltd.

A test of Hirschi's social bonding theory: a comparison of male and female delinquency.

PubMed

Ozbay, Ozden; Ozcan, Yusuf Ziya

2008-04-01

In this study, Hirschi's social bonding theory is employed to identify what aspects of the theory can explain male and female delinquency and whether social bonding variables can equally explain male and female delinquency (generalizability problem) in a developing society, Turkey. The data include a two-stage-stratified cluster sample of 1,710 high school students from the central districts of Ankara, the capital of Turkey. The findings suggest that social bonding variables play a more important role for male students than for female students. Furthermore, they indicate that components of the social bonding theory can equally explain both male and female delinquent acts.

Estimating Catchment-Scale Snowpack Variability in Complex Forested Terrain, Valles Caldera National Preserve, NM

NASA Astrophysics Data System (ADS)

Harpold, A. A.; Brooks, P. D.; Biederman, J. A.; Swetnam, T.

2011-12-01

Difficulty estimating snowpack variability across complex forested terrain currently hinders the prediction of water resources in the semi-arid Southwestern U.S. Catchment-scale estimates of snowpack variability are necessary for addressing ecological, hydrological, and water resources issues, but are often interpolated from a small number of point-scale observations. In this study, we used LiDAR-derived distributed datasets to investigate how elevation, aspect, topography, and vegetation interact to control catchment-scale snowpack variability. The study area is the Redondo massif in the Valles Caldera National Preserve, NM, a resurgent dome that varies from 2500 to 3430 m and drains from all aspects. Mean LiDAR-derived snow depths from four catchments (2.2 to 3.4 km^2) draining different aspects of the Redondo massif varied by 30%, despite similar mean elevations and mixed conifer forest cover. To better quantify this variability in snow depths we performed a multiple linear regression (MLR) at a 7.3 by 7.3 km study area (5 x 106 snow depth measurements) comprising the four catchments. The MLR showed that elevation explained 45% of the variability in snow depths across the study area, aspect explained 18% (dominated by N-S aspect), and vegetation 2% (canopy density and height). This linear relationship was not transferable to the catchment-scale however, where additional MLR analyses showed the influence of aspect and elevation differed between the catchments. The strong influence of North-South aspect in most catchments indicated that the solar radiation is an important control on snow depth variability. To explore the role of solar radiation, a model was used to generate winter solar forcing index (SFI) values based on the local and remote topography. The SFI was able to explain a large amount of snow depth variability in areas with similar elevation and aspect. Finally, the SFI was modified to include the effects of shading from vegetation (in and out of canopy), which further explained snow depth variability. The importance of SFI for explaining catchment-scale snow depth variability demonstrates that aspect is not a sufficient metric for direct radiation in complex terrain where slope and remote topographic shading are significant. Surprisingly, the net effects of interception and shading by vegetation on snow depths were minimal compared to elevation and aspect in these catchments. These results suggest that snowpack losses from interception may be balanced by increased shading to reduce the overall impacts from vegetation compared to topographic factors in this high radiation environment. Our analysis indicated that elevation and solar radiation are likely to control snow variability in larger catchments, with interception and shading from vegetation becoming more important at smaller scales.

Adolescent Girls' STEM Identity Formation and Media Images of STEM Professionals: Considering the Influence of Contextual Cues.

PubMed

Steinke, Jocelyn

2017-01-01

Popular media have played a crucial role in the construction, representation, reproduction, and transmission of stereotypes of science, technology, engineering, and mathematics (STEM) professionals, yet little is known about how these stereotypes influence STEM identity formation. Media images of STEM professionals may be important sources of information about STEM and may be particularly salient and relevant for girls during adolescence as they actively consider future personal and professional identities. This article describes gender-stereotyped media images of STEM professionals and examines theories to identify variables that explain the potential influence of these images on STEM identity formation. Understanding these variables is important for expanding current conceptual frameworks of science/STEM identity to better determine how and when cues in the broader sociocultural context may affect adolescent girls' STEM identity. This article emphasizes the importance of focusing on STEM identity relevant variables and STEM identity status to explain individual differences in STEM identity formation.

Adolescent Girls’ STEM Identity Formation and Media Images of STEM Professionals: Considering the Influence of Contextual Cues

PubMed Central

Steinke, Jocelyn

2017-01-01

Popular media have played a crucial role in the construction, representation, reproduction, and transmission of stereotypes of science, technology, engineering, and mathematics (STEM) professionals, yet little is known about how these stereotypes influence STEM identity formation. Media images of STEM professionals may be important sources of information about STEM and may be particularly salient and relevant for girls during adolescence as they actively consider future personal and professional identities. This article describes gender-stereotyped media images of STEM professionals and examines theories to identify variables that explain the potential influence of these images on STEM identity formation. Understanding these variables is important for expanding current conceptual frameworks of science/STEM identity to better determine how and when cues in the broader sociocultural context may affect adolescent girls’ STEM identity. This article emphasizes the importance of focusing on STEM identity relevant variables and STEM identity status to explain individual differences in STEM identity formation. PMID:28603505

Wage Determination and Discrimination among Older Workers.

ERIC Educational Resources Information Center

Quinn, Joseph F.

1979-01-01

Analyzed determinants of wage rates of older workers and the large discrepancies existing between wage earned by Whites, non-Whites, men, and women. Human capital and geographic variables were important wage determinants. Differences in variables cannot completely explain the wage differentials of race and sex. (Author)

A descriptivist approach to trait conceptualization and inference.

PubMed

Jonas, Katherine G; Markon, Kristian E

2016-01-01

In their recent article, How Functionalist and Process Approaches to Behavior Can Explain Trait Covariation, Wood, Gardner, and Harms (2015) underscore the need for more process-based understandings of individual differences. At the same time, the article illustrates a common error in the use and interpretation of latent variable models: namely, the misuse of models to arbitrate issues of causation and the nature of latent variables. Here, we explain how latent variables can be understood simply as parsimonious summaries of data, and how statistical inference can be based on choosing those summaries that minimize information required to represent the data using the model. Although Wood, Gardner, and Harms acknowledge this perspective, they underestimate its significance, including its importance to modeling and the conceptualization of psychological measurement. We believe this perspective has important implications for understanding individual differences in a number of domains, including current debates surrounding the role of formative versus reflective latent variables. (c) 2015 APA, all rights reserved).

On climate prediction: how much can we expect from climate memory?

NASA Astrophysics Data System (ADS)

Yuan, Naiming; Huang, Yan; Duan, Jianping; Zhu, Congwen; Xoplaki, Elena; Luterbacher, Jürg

2018-03-01

Slowing variability in climate system is an important source of climate predictability. However, it is still challenging for current dynamical models to fully capture the variability as well as its impacts on future climate. In this study, instead of simulating the internal multi-scale oscillations in dynamical models, we discussed the effects of internal variability in terms of climate memory. By decomposing climate state x(t) at a certain time point t into memory part M(t) and non-memory part ɛ (t) , climate memory effects from the past 30 years on climate prediction are quantified. For variables with strong climate memory, high variance (over 20% ) in x(t) is explained by the memory part M(t), and the effects of climate memory are non-negligible for most climate variables, but the precipitation. Regarding of multi-steps climate prediction, a power law decay of the explained variance was found, indicating long-lasting climate memory effects. The explained variances by climate memory can remain to be higher than 10% for more than 10 time steps. Accordingly, past climate conditions can affect both short (monthly) and long-term (interannual, decadal, or even multidecadal) climate predictions. With the memory part M(t) precisely calculated from Fractional Integral Statistical Model, one only needs to focus on the non-memory part ɛ (t) , which is an important quantity that determines climate predictive skills.

Does microphytobenthos resuspension influence phytoplankton in shallow systems? A comparison through a Fourier series analysis

NASA Astrophysics Data System (ADS)

Brito, Ana C.; Fernandes, Teresa F.; Newton, Alice; Facca, Chiara; Tett, Paul

2012-09-01

Shallow coastal lagoons, especially the ones with clear waters and lighted substrata, are likely to have large microphytobenthos (MPB) communities. MPB is an important component of these systems, representing up to 99% of the chlorophyll concentration when compared to phytoplankton. It is therefore expected that MPB resuspension play a key role in the dynamics of phytoplankton due to the tide and wind action. Water samples were collected twice per month inside and outside Ria Formosa lagoon (Portugal), for nutrients and chlorophyll a (chl a). Sediment samples were also collected for MPB chl a. Chl a was also analysed in water and sediment samples from Venice lagoon (Italy), at least once per month. A truncated Fourier series was fitted to the data to investigate the seasonal and high-frequency components of the time-series. In the Ria Formosa, the best significant fit for MPB was obtained considering the sum of 26 wave-pairs (sin and cosine), which explained 31% of the variability. The seasonal cycle (1-3 waves) explained approximately 5% of the total variability. Within-day variability which includes spatial heterogeneity explained 61% of the variability. The best fit for phytoplankton inside Ria Formosa was obtained considering the sum of 23 wave-pairs. Outside the lagoon the best fit was obtained using only the sum of 16 wave-pairs. For both cases, the sum of waves explained more than 64% of the variability and the seasonal cycle explained more than 31% of the variability. It is expected that primary producers in the water column have a strong seasonal factor due to the direct effect of the solar cycle, which is the case of other clear waters. In the Venice lagoon, which is microtidal, the best fit for MPB was obtained using 10 wave-pairs. However, the best fit for phytoplankton was obtained with only 3 wave-pairs, indicating the importance of the seasonal cycle. Significant relationships were found between phytoplankton inside and outside the Ria Formosa, as well as between microphytobenthos and phytoplankton in the lagoons of Venice and Ria Formosa. These results suggest the influence of MPB resuspension in the phytoplankton community of shallow coastal lagoons and the importance of phytoplankton exportation to the coastal zone.

Explaining racial/ethnic differences in adolescent substance abuse treatment completion in the United States: a decomposition analysis.

PubMed

Saloner, Brendan; Carson, Nicholas; Lê Cook, Benjamin

2014-06-01

To identify contributors to racial/ethnic differences in completion of alcohol and marijuana treatment among adolescents at publicly funded providers. The 2007 Treatment Episode Data Set provided substance use history, treatment setting, and treatment outcomes for youth aged 12-17 years from five racial/ethnic groups (N = 67,060). Individual-level records were linked to variables measuring the social context and service system characteristics of the metropolitan area. We implemented nonlinear regression decomposition to identify variables that explained minority-white differences. Black and Hispanic youth were significantly less likely than whites to complete treatment for both alcohol and marijuana. Completion rates were similar for whites, Native Americans, and Asian-Americans, however. Differences in predictor variables explained 12.7% of the black-white alcohol treatment gap and 7.6% of the marijuana treatment gap. In contrast, predictors explained 57.4% of the Hispanic-white alcohol treatment gap and 19.8% of the marijuana treatment gap. While differences in the distribution of individual-level variables explained little of the completion gaps, metropolitan-level variables substantially contributed to Hispanic-white gaps. For example, racial/ethnic composition of the metropolitan area explained 41.0% of the Hispanic-white alcohol completion gap and 23.2% of the marijuana completion gap. Regional differences in addiction treatment financing (particularly use of Medicaid funding) explained 13.7% of the Hispanic-white alcohol completion gap and 9.8% of the Hispanic-white marijuana treatment completion gap. Factors related to social context are likely to be important contributors to white-minority differences in addiction treatment completion, particularly for Hispanic youth. Increased Medicaid funding, coupled with culturally tailored services, could be particularly beneficial. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Personality and Sociodemographic Variables as Sources of Variation in Environmental Perception.

ERIC Educational Resources Information Center

Feimer, Nickolaus R.

This research paper examines the relationship between individual differences in environmental perception, and variables which may be important in predicting, if not explaining those variations. The analyses reported were based upon an environmental perception research study previously conducted at the University of California at Berkeley during…

[Modelling the effect of local climatic variability on dengue transmission in Medellin (Colombia) by means of time series analysis].

PubMed

Rúa-Uribe, Guillermo L; Suárez-Acosta, Carolina; Chauca, José; Ventosilla, Palmira; Almanza, Rita

2013-09-01

Dengue fever is a major impact on public health vector-borne disease, and its transmission is influenced by entomological, sociocultural and economic factors. Additionally, climate variability plays an important role in the transmission dynamics. A large scientific consensus has indicated that the strong association between climatic variables and disease could be used to develop models to explain the incidence of the disease. To develop a model that provides a better understanding of dengue transmission dynamics in Medellin and predicts increases in the incidence of the disease. The incidence of dengue fever was used as dependent variable, and weekly climatic factors (maximum, mean and minimum temperature, relative humidity and precipitation) as independent variables. Expert Modeler was used to develop a model to better explain the behavior of the disease. Climatic variables with significant association to the dependent variable were selected through ARIMA models. The model explains 34% of observed variability. Precipitation was the climatic variable showing statistically significant association with the incidence of dengue fever, but with a 20 weeks delay. In Medellin, the transmission of dengue fever was influenced by climate variability, especially precipitation. The strong association dengue fever/precipitation allowed the construction of a model to help understand dengue transmission dynamics. This information will be useful to develop appropriate and timely strategies for dengue control.

[Prediction of mathematics achievement: effect of personal, socioeducational and contextual variables].

PubMed

Rosário, Pedro; Lourenço, Abílio; Paiva, Olímpia; Rodrigues, Adriana; Valle, Antonio; Tuero-Herrero, Ellián

2012-05-01

Based upon the self-regulated learning theoretical framework this study examined to what extent students' Math school achievement (fifth to ninth graders from compulsory education) can be explained by different cognitive-motivational, social, educational, and contextual variables. A sample of 571 students (10 to 15 year old) enrolled in the study. Findings suggest that Math achievement can be predicted by self-efficacy in Math, school success and self-regulated learning and that these same variables can be explained by other motivational (ej., achievement goals) and contextual variables (school disruption) stressing this way the main importance of self-regulated learning processes and the role context can play in the promotion of school success. The educational implications of the results to the school levels taken are also discussed in the present paper.

Dispersal Ability Determines the Role of Environmental, Spatial and Temporal Drivers of Metacommunity Structure

PubMed Central

Padial, André A.; Ceschin, Fernanda; Declerck, Steven A. J.; De Meester, Luc; Bonecker, Cláudia C.; Lansac-Tôha, Fabio A.; Rodrigues, Liliana; Rodrigues, Luzia C.; Train, Sueli; Velho, Luiz F. M.; Bini, Luis M.

2014-01-01

Recently, community ecologists are focusing on the relative importance of local environmental factors and proxies to dispersal limitation to explain spatial variation in community structure. Albeit less explored, temporal processes may also be important in explaining species composition variation in metacommunities occupying dynamic systems. We aimed to evaluate the relative role of environmental, spatial and temporal variables on the metacommunity structure of different organism groups in the Upper Paraná River floodplain (Brazil). We used data on macrophytes, fish, benthic macroinvertebrates, zooplankton, periphyton, and phytoplankton collected in up to 36 habitats during a total of eight sampling campaigns over two years. According to variation partitioning results, the importance of predictors varied among biological groups. Spatial predictors were particularly important for organisms with comparatively lower dispersal ability, such as aquatic macrophytes and fish. On the other hand, environmental predictors were particularly important for organisms with high dispersal ability, such as microalgae, indicating the importance of species sorting processes in shaping the community structure of these organisms. The importance of watercourse distances increased when spatial variables were the main predictors of metacommunity structure. The contribution of temporal predictors was low. Our results emphasize the strength of a trait-based analysis and of better defining spatial variables. More importantly, they supported the view that “all-or- nothing” interpretations on the mechanisms structuring metacommunities are rather the exception than the rule. PMID:25340577

Assessing the influence of watershed characteristics on chlorophyll a in waterbodies at global and regional scales

USGS Publications Warehouse

Woelmer, Whitney; Kao, Yu-Chun; Bunnell, David B.; Deines, Andrew M.; Bennion, David; Rogers, Mark W.; Brooks, Colin N.; Sayers, Michael J.; Banach, David M.; Grimm, Amanda G.; Shuchman, Robert A.

2016-01-01

Prediction of primary production of lentic water bodies (i.e., lakes and reservoirs) is valuable to researchers and resource managers alike, but is very rarely done at the global scale. With the development of remote sensing technologies, it is now feasible to gather large amounts of data across the world, including understudied and remote regions. To determine which factors were most important in explaining the variation of chlorophyll a (Chl-a), an indicator of primary production in water bodies, at global and regional scales, we first developed a geospatial database of 227 water bodies and watersheds with corresponding Chl-a, nutrient, hydrogeomorphic, and climate data. Then we used a generalized additive modeling approach and developed model selection criteria to select models that most parsimoniously related Chl-a to predictor variables for all 227 water bodies and for 51 lakes in the Laurentian Great Lakes region in the data set. Our best global model contained two hydrogeomorphic variables (water body surface area and the ratio of watershed to water body surface area) and a climate variable (average temperature in the warmest model selection criteria to select models that most parsimoniously related Chl-a to predictor variables quarter) and explained ~ 30% of variation in Chl-a. Our regional model contained one hydrogeomorphic variable (flow accumulation) and the same climate variable, but explained substantially more variation (58%). Our results indicate that a regional approach to watershed modeling may be more informative to predicting Chl-a, and that nearly a third of global variability in Chl-a may be explained using hydrogeomorphic and climate variables.

Running Technique is an Important Component of Running Economy and Performance

PubMed Central

FOLLAND, JONATHAN P.; ALLEN, SAM J.; BLACK, MATTHEW I.; HANDSAKER, JOSEPH C.; FORRESTER, STEPHANIE E.

2017-01-01

ABSTRACT Despite an intuitive relationship between technique and both running economy (RE) and performance, and the diverse techniques used by runners to achieve forward locomotion, the objective importance of overall technique and the key components therein remain to be elucidated. Purpose This study aimed to determine the relationship between individual and combined kinematic measures of technique with both RE and performance. Methods Ninety-seven endurance runners (47 females) of diverse competitive standards performed a discontinuous protocol of incremental treadmill running (4-min stages, 1-km·h−1 increments). Measurements included three-dimensional full-body kinematics, respiratory gases to determine energy cost, and velocity of lactate turn point. Five categories of kinematic measures (vertical oscillation, braking, posture, stride parameters, and lower limb angles) and locomotory energy cost (LEc) were averaged across 10–12 km·h−1 (the highest common velocity < velocity of lactate turn point). Performance was measured as season's best (SB) time converted to a sex-specific z-score. Results Numerous kinematic variables were correlated with RE and performance (LEc, 19 variables; SB time, 11 variables). Regression analysis found three variables (pelvis vertical oscillation during ground contact normalized to height, minimum knee joint angle during ground contact, and minimum horizontal pelvis velocity) explained 39% of LEc variability. In addition, four variables (minimum horizontal pelvis velocity, shank touchdown angle, duty factor, and trunk forward lean) combined to explain 31% of the variability in performance (SB time). Conclusions This study provides novel and robust evidence that technique explains a substantial proportion of the variance in RE and performance. We recommend that runners and coaches are attentive to specific aspects of stride parameters and lower limb angles in part to optimize pelvis movement, and ultimately enhance performance. PMID:28263283

Desert grassland responses to climate and soil moisture suggest divergent vulnerabilities across the southwestern US

USGS Publications Warehouse

Gremer, Jennifer; Bradford, John B.; Munson, Seth M.; Duniway, Michael C.

2015-01-01

Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long-term (20 to 56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40 to 60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C3 than C4 grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict the future of desert grasslands.

Desert grassland responses to climate and soil moisture suggest divergent vulnerabilities across the southwestern United States.

PubMed

Gremer, Jennifer R; Bradford, John B; Munson, Seth M; Duniway, Michael C

2015-11-01

Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long-term (20-56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40-60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C3 than C4 grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict the future of desert grasslands. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Economic and other determinants of infant and child mortality in small developing countries: the case of Central America and the Caribbean.

PubMed

Hojman, D E

1996-03-01

This analysis involves empirically testing a theoretical model among 22 Central American and Caribbean countries during the 1990s that explains differences in infant and child mortality. Explanatory measures capture demographic, economic, health care, and educational characteristics. The model is expected to allow for an assessment of the potential impact of structural adjustment and external debt. It is pointed out that birth rates and child mortality rates followed similar patterns over time and between countries. In this study's regression analyses all variables in the three models that explain infant mortality are exogenous: low birth weight, immunization, gross domestic product per capita, years of schooling for women, population/nurse, and debt as a proportion of gross national product. As nations became richer, infant mortality declined. Infant mortality was lower in countries with high external debt. In models for explaining the birth rate and the child mortality rate, the best fit included variables for debt, real public expenditure on health care, water supply, and malnutrition. Analysis in a simultaneous model for 10 countries revealed that the birth rate and the child mortality rate were more responsive to shocks in exogenous variables in Barbados than in the Dominican Republic, and more responsive in the Dominican Republic than in Guatemala. The impact of each exogenous variable varied by country. In Barbados education was four times more effective in explaining the birth rate than water. In Guatemala, the most effective exogenous variable was malnutrition. Child mortality rates were affected more by multiplier effects. In richer countries, the most important impact on child survival was improved access to safe water, and the most important impact on the birth rate was increased real public expenditure on education per capita. For the poorest countries, findings suggest first improvement in malnutrition and then improvement in safe water supplies. Structural adjustment variables were found to have small impacts on the birth rate or limited impacts on child survival in poorer countries.

The key kinematic determinants of undulatory underwater swimming at maximal velocity.

PubMed

Connaboy, Chris; Naemi, Roozbeh; Brown, Susan; Psycharakis, Stelios; McCabe, Carla; Coleman, Simon; Sanders, Ross

2016-01-01

The optimisation of undulatory underwater swimming is highly important in competitive swimming performance. Nineteen kinematic variables were identified from previous research undertaken to assess undulatory underwater swimming performance. The purpose of the present study was to determine which kinematic variables were key to the production of maximal undulatory underwater swimming velocity. Kinematic data at maximal undulatory underwater swimming velocity were collected from 17 skilled swimmers. A series of separate backward-elimination analysis of covariance models was produced with cycle frequency and cycle length as dependent variables (DVs) and participant as a fixed factor, as including cycle frequency and cycle length would explain 100% of the maximal swimming velocity variance. The covariates identified in the cycle-frequency and cycle-length models were used to form the saturated model for maximal swimming velocity. The final parsimonious model identified three covariates (maximal knee joint angular velocity, maximal ankle angular velocity and knee range of movement) as determinants of the variance in maximal swimming velocity (adjusted-r2 = 0.929). However, when participant was removed as a fixed factor there was a large reduction in explained variance (adjusted r2 = 0.397) and only maximal knee joint angular velocity continued to contribute significantly, highlighting its importance to the production of maximal swimming velocity. The reduction in explained variance suggests an emphasis on inter-individual differences in undulatory underwater swimming technique and/or anthropometry. Future research should examine the efficacy of other anthropometric, kinematic and coordination variables to better understand the production of maximal swimming velocity and consider the importance of individual undulatory underwater swimming techniques when interpreting the data.

Identifying biotic integrity and water chemistry relations in nonwadeable rivers of Wisconsin: Toward the development of nutrient criteria

USGS Publications Warehouse

Weigel, B.M.; Robertson, Dale M.

2007-01-01

We sampled 41 sites on 34 nonwadeable rivers that represent the types of rivers in Wisconsin, and the kinds and intensities of nutrient and other anthropogenic stressors upon each river type. Sites covered much of United States Environmental Protection Agency national nutrient ecoregions VII-Mostly Glaciated Dairy Region, and VIII-Nutrient Poor, Largely Glaciated upper Midwest. Fish, macroinvertebrates, and three categories of environmental variables including nutrients, other water chemistry, and watershed features were collected using standard protocols. We summarized fish assemblages by index of biotic integrity (IBI) and its 10 component measures, and macroinvertebrates by 2 organic pollution tolerance and 12 proportional richness measures. All biotic and environmental variables represented a wide range of conditions, with biotic measures ranging from poor to excellent status, despite nutrient concentrations being consistently higher than reference concentrations reported for the regions. Regression tree analyses of nutrients on a suite of biotic measures identified breakpoints in total phosphorus (~0.06 mg/l) and total nitrogen (~0.64 mg/l) concentrations at which biotic assemblages were consistently impaired. Redundancy analyses (RDA) were used to identify the most important variables within each of the three environmental variable categories, which were then used to determine the relative influence of each variable category on the biota. Nutrient measures, suspended chlorophyll a, water clarity, and watershed land cover type (forest or row-crop agriculture) were the most important variables and they explained significant amounts of variation within the macroinvertebrate (R 2 = 60.6%) and fish (R 2 = 43.6%) assemblages. The environmental variables selected in the macroinvertebrate model were correlated to such an extent that partial RDA analyses could not attribute variation explained to individual environmental categories, assigning 89% of the explained variation to interactions among the categories. In contrast, partial RDA attributed much of the explained variation to the nutrient (25%) and other water chemistry (38%) categories for the fish model. Our analyses suggest that it would be beneficial to develop criteria based upon a suite of biotic and nutrient variables simultaneously to deem waters as not meeting their designated uses. ?? 2007 Springer Science+Business Media, LLC.

Identifying biotic integrity and water chemistry relations in nonwadeable rivers of Wisconsin: toward the development of nutrient criteria.

PubMed

Weigel, Brian M; Robertson, Dale M

2007-10-01

We sampled 41 sites on 34 nonwadeable rivers that represent the types of rivers in Wisconsin, and the kinds and intensities of nutrient and other anthropogenic stressors upon each river type. Sites covered much of United States Environmental Protection Agency national nutrient ecoregions VII--Mostly Glaciated Dairy Region, and VIII--Nutrient Poor, Largely Glaciated upper Midwest. Fish, macroinvertebrates, and three categories of environmental variables including nutrients, other water chemistry, and watershed features were collected using standard protocols. We summarized fish assemblages by index of biotic integrity (IBI) and its 10 component measures, and macroinvertebrates by 2 organic pollution tolerance and 12 proportional richness measures. All biotic and environmental variables represented a wide range of conditions, with biotic measures ranging from poor to excellent status, despite nutrient concentrations being consistently higher than reference concentrations reported for the regions. Regression tree analyses of nutrients on a suite of biotic measures identified breakpoints in total phosphorus (approximately 0.06 mg/l) and total nitrogen (approximately 0.64 mg/l) concentrations at which biotic assemblages were consistently impaired. Redundancy analyses (RDA) were used to identify the most important variables within each of the three environmental variable categories, which were then used to determine the relative influence of each variable category on the biota. Nutrient measures, suspended chlorophyll a, water clarity, and watershed land cover type (forest or row-crop agriculture) were the most important variables and they explained significant amounts of variation within the macroinvertebrate (R(2) = 60.6%) and fish (R(2) = 43.6%) assemblages. The environmental variables selected in the macroinvertebrate model were correlated to such an extent that partial RDA analyses could not attribute variation explained to individual environmental categories, assigning 89% of the explained variation to interactions among the categories. In contrast, partial RDA attributed much of the explained variation to the nutrient (25%) and other water chemistry (38%) categories for the fish model. Our analyses suggest that it would be beneficial to develop criteria based upon a suite of biotic and nutrient variables simultaneously to deem waters as not meeting their designated uses.

Disentangling environmental and spatial effects on phylogenetic structure of angiosperm tree communities in China.

PubMed

Qian, Hong; Chen, Shengbin; Zhang, Jin-Long

2017-07-17

Niche-based and neutrality-based theories are two major classes of theories explaining the assembly mechanisms of local communities. Both theories have been frequently used to explain species diversity and composition in local communities but their relative importance remains unclear. Here, we analyzed 57 assemblages of angiosperm trees in 0.1-ha forest plots across China to examine the effects of environmental heterogeneity (relevant to niche-based processes) and spatial contingency (relevant to neutrality-based processes) on phylogenetic structure of angiosperm tree assemblages distributed across a wide range of environment and space. Phylogenetic structure was quantified with six phylogenetic metrics (i.e., phylogenetic diversity, mean pairwise distance, mean nearest taxon distance, and the standardized effect sizes of these three metrics), which emphasize on different depths of evolutionary histories and account for different degrees of species richness effects. Our results showed that the variation in phylogenetic metrics explained independently by environmental variables was on average much greater than that explained independently by spatial structure, and the vast majority of the variation in phylogenetic metrics was explained by spatially structured environmental variables. We conclude that niche-based processes have played a more important role than neutrality-based processes in driving phylogenetic structure of angiosperm tree species in forest communities in China.

Changes in Situational and Dispositional Factors as Predictors of Job Satisfaction

ERIC Educational Resources Information Center

Keller, Anita C.; Semmer, Norbert K.

2013-01-01

Arguably, job satisfaction is one of the most important variables with regard to work. When explaining job satisfaction, research usually focuses on predictor variables in terms of levels but neglects growth rates. Therefore it remains unclear how potential predictors evolve over time and how their development affects job satisfaction. Using…

Are Attractive Men's Faces Masculine or Feminine? The Importance of Controlling Confounds in Face Stimuli

ERIC Educational Resources Information Center

Debruine, Lisa M.; Jones, Benedict C.; Smith, Finlay G.; Little, Anthony C.

2010-01-01

Women's preferences for male masculinity are highly variable. Although many researchers explain this variability as reflecting systematic individual differences in how women resolve the tradeoff between the costs and benefits of choosing a masculine partner, others suggest that methodological differences between studies are responsible. A recent…

Environmental effects on vertebrate species richness: testing the energy, environmental stability and habitat heterogeneity hypotheses.

PubMed

Luo, Zhenhua; Tang, Songhua; Li, Chunwang; Fang, Hongxia; Hu, Huijian; Yang, Ji; Ding, Jingjing; Jiang, Zhigang

2012-01-01

Explaining species richness patterns is a central issue in biogeography and macroecology. Several hypotheses have been proposed to explain the mechanisms driving biodiversity patterns, but the causes of species richness gradients remain unclear. In this study, we aimed to explain the impacts of energy, environmental stability, and habitat heterogeneity factors on variation of vertebrate species richness (VSR), based on the VSR pattern in China, so as to test the energy hypothesis, the environmental stability hypothesis, and the habitat heterogeneity hypothesis. A dataset was compiled containing the distributions of 2,665 vertebrate species and eleven ecogeographic predictive variables in China. We grouped these variables into categories of energy, environmental stability, and habitat heterogeneity and transformed the data into 100 × 100 km quadrat systems. To test the three hypotheses, AIC-based model selection was carried out between VSR and the variables in each group and correlation analyses were conducted. There was a decreasing VSR gradient from the southeast to the northwest of China. Our results showed that energy explained 67.6% of the VSR variation, with the annual mean temperature as the main factor, which was followed by annual precipitation and NDVI. Environmental stability factors explained 69.1% of the VSR variation and both temperature annual range and precipitation seasonality had important contributions. By contrast, habitat heterogeneity variables explained only 26.3% of the VSR variation. Significantly positive correlations were detected among VSR, annual mean temperature, annual precipitation, and NDVI, whereas the relationship of VSR and temperature annual range was strongly negative. In addition, other variables showed moderate or ambiguous relations to VSR. The energy hypothesis and the environmental stability hypothesis were supported, whereas little support was found for the habitat heterogeneity hypothesis.

Environmental Effects on Vertebrate Species Richness: Testing the Energy, Environmental Stability and Habitat Heterogeneity Hypotheses

PubMed Central

Luo, Zhenhua; Tang, Songhua; Li, Chunwang; Fang, Hongxia; Hu, Huijian; Yang, Ji; Ding, Jingjing; Jiang, Zhigang

2012-01-01

Background Explaining species richness patterns is a central issue in biogeography and macroecology. Several hypotheses have been proposed to explain the mechanisms driving biodiversity patterns, but the causes of species richness gradients remain unclear. In this study, we aimed to explain the impacts of energy, environmental stability, and habitat heterogeneity factors on variation of vertebrate species richness (VSR), based on the VSR pattern in China, so as to test the energy hypothesis, the environmental stability hypothesis, and the habitat heterogeneity hypothesis. Methodology/Principal Findings A dataset was compiled containing the distributions of 2,665 vertebrate species and eleven ecogeographic predictive variables in China. We grouped these variables into categories of energy, environmental stability, and habitat heterogeneity and transformed the data into 100×100 km quadrat systems. To test the three hypotheses, AIC-based model selection was carried out between VSR and the variables in each group and correlation analyses were conducted. There was a decreasing VSR gradient from the southeast to the northwest of China. Our results showed that energy explained 67.6% of the VSR variation, with the annual mean temperature as the main factor, which was followed by annual precipitation and NDVI. Environmental stability factors explained 69.1% of the VSR variation and both temperature annual range and precipitation seasonality had important contributions. By contrast, habitat heterogeneity variables explained only 26.3% of the VSR variation. Significantly positive correlations were detected among VSR, annual mean temperature, annual precipitation, and NDVI, whereas the relationship of VSR and temperature annual range was strongly negative. In addition, other variables showed moderate or ambiguous relations to VSR. Conclusions/Significance The energy hypothesis and the environmental stability hypothesis were supported, whereas little support was found for the habitat heterogeneity hypothesis. PMID:22530038

Understanding Recombination.

ERIC Educational Resources Information Center

Zimmerman, Ira

2003-01-01

Describes a science activity on the importance of meiosis for variability. Uses a coin flip to demonstrate the random arrangement of genetic materials and explains how this results in zygotes with a new DNA combination. (YDS)

Dimensions Underlying Measures of Disability, Personal Factors, and Health Status in Cervical Radiculopathy

PubMed Central

Halvorsen, Marie; Kierkegaard, Marie; Harms-Ringdahl, Karin; Peolsson, Anneli; Dedering, Åsa

2015-01-01

Abstract This cross-sectional study sought to identify dimensions underlying measures of impairment, disability, personal factors, and health status in patients with cervical radiculopathy. One hundred twenty-four patients with magnetic resonance imaging-verified cervical radiculopathy, attending a neurosurgery clinic in Sweden, participated. Data from clinical tests and questionnaires on disability, personal factors, and health status were used in a principal-component analysis (PCA) with oblique rotation. The PCA supported a 3-component model including 14 variables from clinical tests and questionnaires, accounting for 73% of the cumulative percentage. The first component, pain and disability, explained 56%. The second component, health, fear-avoidance beliefs, kinesiophobia, and self-efficacy, explained 9.2%. The third component including anxiety, depression, and catastrophizing explained 7.6%. The strongest-loading variables of each dimension were “present neck pain intensity,” “fear avoidance,” and “anxiety.” The three underlying dimensions identified and labeled Pain and functioning, Health, beliefs, and kinesiophobia, and Mood state and catastrophizing captured aspects of importance for cervical radiculopathy. Since the variables “present neck pain intensity,” “fear avoidance,” and “anxiety” had the strongest loading in each of the three dimensions; it may be important to include them in a reduced multidimensional measurement set in cervical radiculopathy. PMID:26091482

Dimensions Underlying Measures of Disability, Personal Factors, and Health Status in Cervical Radiculopathy: A Cross-Sectional Study.

PubMed

Halvorsen, Marie; Kierkegaard, Marie; Harms-Ringdahl, Karin; Peolsson, Anneli; Dedering, Åsa

2015-06-01

This cross-sectional study sought to identify dimensions underlying measures of impairment, disability, personal factors, and health status in patients with cervical radiculopathy. One hundred twenty-four patients with magnetic resonance imaging-verified cervical radiculopathy, attending a neurosurgery clinic in Sweden, participated. Data from clinical tests and questionnaires on disability, personal factors, and health status were used in a principal-component analysis (PCA) with oblique rotation. The PCA supported a 3-component model including 14 variables from clinical tests and questionnaires, accounting for 73% of the cumulative percentage. The first component, pain and disability, explained 56%. The second component, health, fear-avoidance beliefs, kinesiophobia, and self-efficacy, explained 9.2%. The third component including anxiety, depression, and catastrophizing explained 7.6%. The strongest-loading variables of each dimension were "present neck pain intensity," "fear avoidance," and "anxiety." The three underlying dimensions identified and labeled Pain and functioning, Health, beliefs, and kinesiophobia, and Mood state and catastrophizing captured aspects of importance for cervical radiculopathy. Since the variables "present neck pain intensity," "fear avoidance," and "anxiety" had the strongest loading in each of the three dimensions; it may be important to include them in a reduced multidimensional measurement set in cervical radiculopathy.

The relationship between observational scale and explained variance in benthic communities

PubMed Central

Flood, Roger D.; Frisk, Michael G.; Garza, Corey D.; Lopez, Glenn R.; Maher, Nicole P.

2018-01-01

This study addresses the impact of spatial scale on explaining variance in benthic communities. In particular, the analysis estimated the fraction of community variation that occurred at a spatial scale smaller than the sampling interval (i.e., the geographic distance between samples). This estimate is important because it sets a limit on the amount of community variation that can be explained based on the spatial configuration of a study area and sampling design. Six benthic data sets were examined that consisted of faunal abundances, common environmental variables (water depth, grain size, and surficial percent cover), and sonar backscatter treated as a habitat proxy (categorical acoustic provinces). Redundancy analysis was coupled with spatial variograms generated by multiscale ordination to quantify the explained and residual variance at different spatial scales and within and between acoustic provinces. The amount of community variation below the sampling interval of the surveys (< 100 m) was estimated to be 36–59% of the total. Once adjusted for this small-scale variation, > 71% of the remaining variance was explained by the environmental and province variables. Furthermore, these variables effectively explained the spatial structure present in the infaunal community. Overall, no scale problems remained to compromise inferences, and unexplained infaunal community variation had no apparent spatial structure within the observational scale of the surveys (> 100 m), although small-scale gradients (< 100 m) below the observational scale may be present. PMID:29324746

Species associations structured by environment and land-use history promote beta-diversity in a temperate forest.

PubMed

Murphy, Stephen J; Audino, Livia D; Whitacre, James; Eck, Jenalle L; Wenzel, John W; Queenborough, Simon A; Comita, Liza S

2015-03-01

Patterns of diversity and community composition in forests are controlled by a combination of environmental factors, historical events, and stochastic or neutral mechanisms. Each of these processes has been linked to forest community assembly, but their combined contributions to alpha and beta-diversity in forests has not been well explored. Here we use variance partitioning to analyze approximately 40,000 individual trees of 49 species, collected within 137 ha of sampling area spread across a 900-ha temperate deciduous forest reserve in Pennsylvania to ask (1) To what extent is site-to-site variation in species richness and community composition of a temperate forest explained by measured environmental gradients and by spatial descriptors (used here to estimate dispersal-assembly or unmeasured, spatially structured processes)? (2) How does the incorporation of land-use history information increase the importance attributed to deterministic community assembly? and (3) How do the distributions and abundances of individual species within the community correlate with these factors? Environmental variables (i.e., topography, soils, and distance to stream), spatial descriptors (i.e., spatial eigenvectors derived from Cartesian coordinates), and land-use history variables (i.e., land-use type and intensity, forest age, and distance to road), explained about half of the variation in both species richness and community composition. Spatial descriptors explained the most variation, followed by measured environmental variables and then by land- use history. Individual species revealed variable responses to each of these sets of predictor variables. Several species were associated with stream habitats, and others were strictly delimited across opposing north- and south-facing slopes. Several species were also associated with areas that experienced recent (i.e., <100 years) human land-use impacts. These results indicate that deterministic factors, including environmental and land-use history variables, are important drivers of community response. The large amount of "unexplained" variation seen here (about 50%) is commonly observed in other such studies attempting to explain distribution and abundance patterns of plant communities. Determining whether such large fractions of unaccounted for variation are caused by a lack of sufficient data, or are an indication of stochastic features of forest communities globally, will remain an important challenge for ecologists in the future.

The Importance of Biotic vs. Abiotic Drivers of Local Plant Community Composition Along Regional Bioclimatic Gradients

PubMed Central

Klanderud, Kari; Vandvik, Vigdis; Goldberg, Deborah

2015-01-01

We assessed if the relative importance of biotic and abiotic factors for plant community composition differs along environmental gradients and between functional groups, and asked which implications this may have in a warmer and wetter future. The study location is a unique grid of sites spanning regional-scale temperature and precipitation gradients in boreal and alpine grasslands in southern Norway. Within each site we sampled vegetation and associated biotic and abiotic factors, and combined broad- and fine-scale ordination analyses to assess the relative explanatory power of these factors for species composition. Although the community responses to biotic and abiotic factors did not consistently change as predicted along the bioclimatic gradients, abiotic variables tended to explain a larger proportion of the variation in species composition towards colder sites, whereas biotic variables explained more towards warmer sites, supporting the stress gradient hypothesis. Significant interactions with precipitation suggest that biotic variables explained more towards wetter climates in the sub alpine and boreal sites, but more towards drier climates in the colder alpine. Thus, we predict that biotic interactions may become more important in alpine and boreal grasslands in a warmer future, although more winter precipitation may counteract this trend in oceanic alpine climates. Our results show that both local and regional scales analyses are needed to disentangle the local vegetation-environment relationships and their regional-scale drivers, and biotic interactions and precipitation must be included when predicting future species assemblages. PMID:26091266

The Importance of Biotic vs. Abiotic Drivers of Local Plant Community Composition Along Regional Bioclimatic Gradients.

PubMed

Klanderud, Kari; Vandvik, Vigdis; Goldberg, Deborah

2015-01-01

We assessed if the relative importance of biotic and abiotic factors for plant community composition differs along environmental gradients and between functional groups, and asked which implications this may have in a warmer and wetter future. The study location is a unique grid of sites spanning regional-scale temperature and precipitation gradients in boreal and alpine grasslands in southern Norway. Within each site we sampled vegetation and associated biotic and abiotic factors, and combined broad- and fine-scale ordination analyses to assess the relative explanatory power of these factors for species composition. Although the community responses to biotic and abiotic factors did not consistently change as predicted along the bioclimatic gradients, abiotic variables tended to explain a larger proportion of the variation in species composition towards colder sites, whereas biotic variables explained more towards warmer sites, supporting the stress gradient hypothesis. Significant interactions with precipitation suggest that biotic variables explained more towards wetter climates in the sub alpine and boreal sites, but more towards drier climates in the colder alpine. Thus, we predict that biotic interactions may become more important in alpine and boreal grasslands in a warmer future, although more winter precipitation may counteract this trend in oceanic alpine climates. Our results show that both local and regional scales analyses are needed to disentangle the local vegetation-environment relationships and their regional-scale drivers, and biotic interactions and precipitation must be included when predicting future species assemblages.

Mechanisms driving recruitment variability in fish: comparisons between the Laurentian Great Lakes and marine systems

USGS Publications Warehouse

Pritt, Jeremy J.; Roseman, Edward F.; O'Brien, Timothy P.

2014-01-01

In his seminal work, Hjort (in Fluctuations in the great fisheries of Northern Europe. Conseil Parmanent International Pour L'Exploration De La Mar. Rapports et Proces-Verbaux, 20: 1–228, 1914) observed that fish population levels fluctuated widely, year-class strength was set early in life, and egg production by adults could not alone explain variability in year-class strength. These observations laid the foundation for hypotheses on mechanisms driving recruitment variability in marine systems. More recently, researchers have sought to explain year-class strength of important fish in the Laurentian Great Lakes and some of the hypotheses developed for marine fisheries have been transferred to Great Lakes fish. We conducted a literature review to determine the applicability of marine recruitment hypotheses to Great Lakes fish. We found that temperature, interspecific interactions, and spawner effects (abundance, age, and condition of adults) were the most important factors in explaining recruitment variability in Great Lakes fish, whereas relatively fewer studies identified bottom-up trophodynamic factors or hydrodynamic factors as important. Next, we compared recruitment between Great Lakes and Baltic Sea fish populations and found no statistical difference in factors driving recruitment between the two systems, indicating that recruitment hypotheses may often be transferable between Great Lakes and marine systems. Many recruitment hypotheses developed for marine fish have yet to be applied to Great Lakes fish. We suggest that future research on recruitment in the Great Lakes should focus on forecasting the effects of climate change and invasive species. Further, because the Great Lakes are smaller and more enclosed than marine systems, and have abundant fishery-independent data, they are excellent candidates for future hypothesis testing on recruitment in fish.

The contribution of individual psychological resilience in determining the professional quality of life of Australian nurses

PubMed Central

Hegney, Desley G.; Rees, Clare S.; Eley, Robert; Osseiran-Moisson, Rebecca; Francis, Karen

2015-01-01

Research Topic: The aim of this study was to determine the relative contribution of trait negative affect and individual psychological resilience in explaining the professional quality of life of nurses. Materials and Methods: One thousand, seven hundred and forty-three Australian nurses from the public, private, and aged care sectors completed an online Qualtrics survey. The survey collected demographic data as well as measures of depression, anxiety and stress, trait negative affect, resilience, and professional quality of life. Results: Significant positive relationships were observed between anxiety, depression and stress, trait negative affectivity, burnout, and secondary traumatic stress (compassion fatigue). Significant negative relationships were observed between each of the aforementioned variables and resilience and compassion satisfaction (CS). Results of mediated regression analysis indicated that resilience partially mediates the relationship between trait negative affect and CS. Conclusion: Results confirm the importance of both trait negative affect and resilience in explaining positive aspects of professional quality of life. Importantly, resilience was confirmed as a key variable impacting levels of CS and thus a potentially important variable to target in interventions aimed at improving nurse’s professional quality of life. PMID:26539150

Factors influencing geographic patterns in diversity of forest bird communities of eastern Connecticut, USA

USGS Publications Warehouse

Craig, Robert J.; Klaver, Robert W.

2012-01-01

At regional scales, the most important variables associated with diversity are latitudinally-based temperature and net primary productivity, although diversity is also influenced by habitat. We examined bird species richness, community density and community evenness in forests of eastern Connecticut to determine whether: 1) spatial and seasonal patterns exist in diversity, 2) energy explains the greatest proportion of variation in diversity parameters, 3) variation in habitat explains remaining diversity variance, and 4) seasonal shifts in diversity provide clues about how environmental variables shape communities. We sought to discover if our data supported predictions of the species–energy hypothesis. We used the variable circular plot technique to estimate bird populations and quantified the location, elevation, forest type, vegetation type, canopy cover, moisture regime, understory density and primary production for the study sites. We found that 1) summer richness and population densities are roughly equal in northeastern and southeastern Connecticut, whereas in winter both concentrate toward the coast, 2) variables linked with temperature explained much of the patterns in winter diversity, but energy-related variables showed little relationship to summer diversity, 3) the effect of habitat variables on diversity parameters predominated in summer, although their effect was weak, 4) contrary to theory, evenness increased from summer to winter, and 5) support for predictions of species–energy theory was primarily restricted to winter data. Although energy and habitat played a role in explaining community patterns, they left much of the variance in regional diversity unexplained, suggesting that a large stochastic component to diversity also may exist.

Fishing, fast growth and climate variability increase the risk of collapse

PubMed Central

Pinsky, Malin L.; Byler, David

2015-01-01

Species around the world have suffered collapses, and a key question is why some populations are more vulnerable than others. Traditional conservation biology and evidence from terrestrial species suggest that slow-growing populations are most at risk, but interactions between climate variability and harvest dynamics may alter or even reverse this pattern. Here, we test this hypothesis globally. We use boosted regression trees to analyse the influences of harvesting, species traits and climate variability on the risk of collapse (decline below a fixed threshold) across 154 marine fish populations around the world. The most important factor explaining collapses was the magnitude of overfishing, while the duration of overfishing best explained long-term depletion. However, fast growth was the next most important risk factor. Fast-growing populations and those in variable environments were especially sensitive to overfishing, and the risk of collapse was more than tripled for fast-growing when compared with slow-growing species that experienced overfishing. We found little evidence that, in the absence of overfishing, climate variability or fast growth rates alone drove population collapse over the last six decades. Expanding efforts to rapidly adjust harvest pressure to account for climate-driven lows in productivity could help to avoid future collapses, particularly among fast-growing species. PMID:26246548

Fishing, fast growth and climate variability increase the risk of collapse.

PubMed

Pinsky, Malin L; Byler, David

2015-08-22

Species around the world have suffered collapses, and a key question is why some populations are more vulnerable than others. Traditional conservation biology and evidence from terrestrial species suggest that slow-growing populations are most at risk, but interactions between climate variability and harvest dynamics may alter or even reverse this pattern. Here, we test this hypothesis globally. We use boosted regression trees to analyse the influences of harvesting, species traits and climate variability on the risk of collapse (decline below a fixed threshold) across 154 marine fish populations around the world. The most important factor explaining collapses was the magnitude of overfishing, while the duration of overfishing best explained long-term depletion. However, fast growth was the next most important risk factor. Fast-growing populations and those in variable environments were especially sensitive to overfishing, and the risk of collapse was more than tripled for fast-growing when compared with slow-growing species that experienced overfishing. We found little evidence that, in the absence of overfishing, climate variability or fast growth rates alone drove population collapse over the last six decades. Expanding efforts to rapidly adjust harvest pressure to account for climate-driven lows in productivity could help to avoid future collapses, particularly among fast-growing species. © 2015 The Author(s).

Weather explains high annual variation in butterfly dispersal

PubMed Central

Rytteri, Susu; Heikkinen, Risto K.; Heliölä, Janne; von Bagh, Peter

2016-01-01

Weather conditions fundamentally affect the activity of short-lived insects. Annual variation in weather is therefore likely to be an important determinant of their between-year variation in dispersal, but conclusive empirical studies are lacking. We studied whether the annual variation of dispersal can be explained by the flight season's weather conditions in a Clouded Apollo (Parnassius mnemosyne) metapopulation. This metapopulation was monitored using the mark–release–recapture method for 12 years. Dispersal was quantified for each monitoring year using three complementary measures: emigration rate (fraction of individuals moving between habitat patches), average residence time in the natal patch, and average distance moved. There was much variation both in dispersal and average weather conditions among the years. Weather variables significantly affected the three measures of dispersal and together with adjusting variables explained 79–91% of the variation observed in dispersal. Different weather variables became selected in the models explaining variation in three dispersal measures apparently because of the notable intercorrelations. In general, dispersal rate increased with increasing temperature, solar radiation, proportion of especially warm days, and butterfly density, and decreased with increasing cloudiness, rainfall, and wind speed. These results help to understand and model annually varying dispersal dynamics of species affected by global warming. PMID:27440662

Present and future ecological niche modeling of garter snake species from the Trans-Mexican Volcanic Belt

PubMed Central

García-Vázquez, Uri; D’Addario, Maristella

2018-01-01

Land use and climate change are affecting the abundance and distribution of species. The Trans-Mexican Volcanic Belt (TMVB) is a very diverse region due to geological history, geographic position, and climate. It is also one of the most disturbed regions in Mexico. Reptiles are particularly sensitive to environmental changes due to their low dispersal capacity and thermal ecology. In this study, we define the important environmental variables (considering climate, topography, and land use) and potential distribution (present and future) of the five Thamnophis species present in TMVB. To do so, we used the maximum entropy modeling software (MAXENT). First, we modeled to select the most important variables to explain the distribution of each species, then we modeled again using only the most important variables and projected these models to the future considering a middle-moderate climate change scenario (rcp45), and land use and vegetation variables for the year 2050 (generated according to land use changes that occurred between years 2002 and 2011). Arid vegetation had an important negative effect on habitat suitability for all species, and minimum temperature of the coldest month was important for four of the five species. Thamnophis cyrtopsis was the species with the lowest tolerance to minimum temperatures. The maximum temperature of the warmest month was important for T. scalaris and T. cyrtopsis. Low percentages of agriculture were positive for T. eques and T. melanogaster but, at higher values, agriculture had a negative effect on habitat suitability for both species. Elevation was the most important variable to explain T. eques and T. melanogaster potential distribution while distance to Abies forests was the most important variable for T. scalaris and T. scaliger. All species had a high proportion of their potential distribution in the TMVB. However, according to our models, all Thamnophis species will experience reductions in their potential distribution in this region. T. scalaris will suffer the biggest reduction because this species is limited by high temperatures and will not be able to shift its distribution upward, as it is already present in the highest elevations of the TMVB. PMID:29666767

RESOLVING FINE SCALE IN AIR TOXICS MODELING AND THE IMPORTANCE OF ITS SUB-GRID VARIABILITY FOR EXPOSURE ESTIMATES

EPA Science Inventory

This presentation explains the importance of the fine-scale features for air toxics exposure modeling. The paper presents a new approach to combine local-scale and regional model results for the National Air Toxic Assessment. The technique has been evaluated with a chemical tra...

Estimation of streamflow, base flow, and nitrate-nitrogen loads in Iowa using multiple linear regression models

USGS Publications Warehouse

Schilling, K.E.; Wolter, C.F.

2005-01-01

Nineteen variables, including precipitation, soils and geology, land use, and basin morphologic characteristics, were evaluated to develop Iowa regression models to predict total streamflow (Q), base flow (Qb), storm flow (Qs) and base flow percentage (%Qb) in gauged and ungauged watersheds in the state. Discharge records from a set of 33 watersheds across the state for the 1980 to 2000 period were separated into Qb and Qs. Multiple linear regression found that 75.5 percent of long term average Q was explained by rainfall, sand content, and row crop percentage variables, whereas 88.5 percent of Qb was explained by these three variables plus permeability and floodplain area variables. Qs was explained by average rainfall and %Qb was a function of row crop percentage, permeability, and basin slope variables. Regional regression models developed for long term average Q and Qb were adapted to annual rainfall and showed good correlation between measured and predicted values. Combining the regression model for Q with an estimate of mean annual nitrate concentration, a map of potential nitrate loads in the state was produced. Results from this study have important implications for understanding geomorphic and land use controls on streamflow and base flow in Iowa watersheds and similar agriculture dominated watersheds in the glaciated Midwest. (JAWRA) (Copyright ?? 2005).

Feeling old today? Daily health, stressors, and affect explain day-to-day variability in subjective age.

PubMed

Kotter-Grühn, Dana; Neupert, Shevaun D; Stephan, Yannick

2015-01-01

Subjective age is an important correlate of health, well-being, and longevity. So far, little is known about short-term variability in subjective age and the circumstances under which individuals feel younger/older in daily life. This study examined whether (a) older adults' felt age fluctuates on a day-to-day basis, (b) daily changes in health, stressors, and affect explain fluctuations in felt age, and (c) the daily associations between felt age and health, stressors, or affect are time-ordered. Using an eight-day daily diary approach, N = 43 adults (60-96 years, M = 74.65, SD = 8.19) filled out daily questionnaires assessing subjective age, health, daily stressors, and affect. Data were analysed using multilevel modelling. Subjective age, health, daily stressors, affect. Intra-individual variability in felt age was not explained by time but by short-term variability in other variables. Specifically, on days when participants experienced more than average health problems, stress, or negative affect they felt older than on days with average health, stress, or negative affect. No time-ordered effects were found. Bad health, many stressors, and negative affective experiences constitute circumstances under which older adults feel older than they typically do. Thus, daily measures of subjective age could be markers of health and well-being.

Distribution of Chironomidae in a semiarid intermittent river of Brazil.

PubMed

Farias, R L; Carvalho, L K; Medeiros, E S F

2012-12-01

The effects of the intermittency of water flow on habitat structure and substrate composition have been reported to create a patch dynamics for the aquatic fauna, mostly for that associated with the substrate. This study aims to describe the spatial distribution of Chironomidae in an intermittent river of semiarid Brazil and to associate assemblage composition with environmental variables. Benthic invertebrates were sampled during the wet and dry seasons using a D-shaped net (40 cm wide and 250 μm mesh), and the Chironomidae were identified to genus level. The most abundant genera were Tanytarsus, Polypedilum, and Saetheria with important contributions of the genera Procladius, Aedokritus, and Dicrotendipes. Richness and density were not significantly different between the study sites, and multiple regression showed that the variation in richness and density explained by the environmental variables was significant only for substrate composition. The composition of genera showed significant spatial segregation across the study sites. Canonical Correspondence Analysis showed significant correspondence between Chironomidae composition and the environmental variables, with submerged vegetation, elevation, and leaf litter being important predictors of the Chironomidae fauna. This study showed that Chironomidae presented important spatial variation along the river and that this variation was substantially explained by environmental variables associated with the habitat structure and river hierarchy. We suggest that the observed spatial segregation in the fauna results in the high diversity of this group of organisms in intermittent streams.

Not Noisy, Just Wrong: The Role of Suboptimal Inference in Behavioral Variability

PubMed Central

Beck, Jeffrey M.; Ma, Wei Ji; Pitkow, Xaq; Latham, Peter E.; Pouget, Alexandre

2015-01-01

Behavior varies from trial to trial even when the stimulus is maintained as constant as possible. In many models, this variability is attributed to noise in the brain. Here, we propose that there is another major source of variability: suboptimal inference. Importantly, we argue that in most tasks of interest, and particularly complex ones, suboptimal inference is likely to be the dominant component of behavioral variability. This perspective explains a variety of intriguing observations, including why variability appears to be larger on the sensory than on the motor side, and why our sensors are sometimes surprisingly unreliable. PMID:22500627

Impacts of weather on long-term patterns of plant richness and diversity vary with location and management

USGS Publications Warehouse

Jonas, Jayne L.; Buhl, Deborah A.; Symstad, Amy J.

2015-01-01

Better understanding the influence of precipitation and temperature on plant assemblages is needed to predict the effects of climate change. Many studies have examined the relationship between plant productivity and weather (primarily precipitation), but few have directly assessed the relationship between plant richness or diversity and weather despite their increased use as metrics of ecosystem condition. We focus on the grasslands of central North America, which are characterized by high temporal climatic variability. Over the next 100 years, these grasslands are predicted to experience further increased variability in growing season precipitation, as well as increased temperatures, due to global climate change. We assess 1) the portion of interannual variability of richness and diversity explained by weather, 2) how relationships between these metrics and weather vary among plant assemblages, and 3) which aspects of weather best explain temporal variability. We used an information-theoretic approach to assess relationships between long-term plant richness and diversity patterns and a priori weather covariates using six datasets from four grasslands. Weather explained up to 49% and 63% of interannual variability in total plant species richness and diversity, respectively. However, richness and diversity responses to specific weather variables varied both among sites and among experimental treatments within sites. In general, we found many instances in which temperature was of equal or greater importance as precipitation, as well as evidence of the importance of lagged effects and precipitation or temperature variability. Although precipitation has been shown to be a key driver of productivity in grasslands, our results indicate that increasing temperatures alone, without substantial changes in precipitation patterns, could have measurable effects on Great Plains grassland plant assemblages and biodiversity metrics. Our results also suggest that richness and diversity will respond in unique ways to changing climate and management can affect these responses; additional research and monitoring will be essential for further understanding of these complex relationships.Read More: http://www.esajournals.org/doi/abs/10.1890/14-1989.1

Impacts of weather on long-term patterns of plant richness and diversity vary with location and management.

PubMed

Jonas, Jayne L; Buhl, Deborah A; Symstad, Amy J

2015-09-01

Better understanding the influence of precipitation and temperature on plant assemblages is needed to predict the effects of climate change. Many studies have examined the relationship between plant productivity and weather (primarily precipitation), but few have directly assessed the relationship between plant richness or diversity and weather despite their increased use as metrics of ecosystem condition. We focus on the grasslands of central North America, which are characterized by high temporal climatic variability. Over the next 100 years, these grasslands are predicted to experience further increased variability in growing season precipitation, as well as increased temperatures, due to global climate change. We assess the portion of interannual variability of richness and diversity explained by weather, how relationships between these metrics and weather vary among plant assemblages, and which aspects of weather best explain temporal variability. We used an information-theoretic approach to assess relationships between long-term plant richness and diversity patterns and a priori weather covariates using six data sets from four grasslands. Weather explained up to 49% and 63% of interannual variability in total plant species richness and diversity, respectively. However, richness and diversity responses to specific weather variables varied both among sites and among experimental treatments within sites. In general, we found many instances in which temperature was of equal or greater importance as precipitation, as well as evidence of the importance of lagged effects and precipitation or temperature variability. Although precipitation has been shown to be a key driver of productivity in grasslands, our results indicate that increasing temperatures alone, without substantial changes in precipitation patterns, could have measurable effects on Great Plains grassland plant assemblages and biodiversity metrics. Our results also suggest that richness and diversity will respond in unique ways to changing climate and management can affect these responses; additional research and monitoring will be essential for further understanding of these complex relationships.

Emotional abilities as predictors of risky driving behavior among a cohort of middle aged drivers.

PubMed

Arnau-Sabatés, Laura; Sala-Roca, Josefina; Jariot-Garcia, Mercè

2012-03-01

The aim of this study is to analyze the relationship between emotional abilities and the influence of this relationship on self reported drivers' risky attitudes. The risky driving attitudes and emotional abilities of 177 future driving instructors were measured. The results demonstrate that risky attitudes correlate negatively with emotional abilities. Regression analysis showed that adaptability and interpersonal abilities explained the differences observed in the global risk attitude index. There were some differences in the specific risk factors. The variability observed in the speed and distraction and fatigue factors could also be explained by interpersonal and adaptability abilities. Nevertheless the tendency to take risks was explained by stress management and also interpersonal components. Emotional abilities have the weakest relation with alcohol and drugs factor, and in this case the variability observed was explained by the adaptability component. The results obtained highlight the importance take off including emotional abilities in prevention programs to reduce risky driving behaviors. Copyright © 2011 Elsevier Ltd. All rights reserved.

Separating the effects of environment and space on tree species distribution: from population to community.

PubMed

Lin, Guojun; Stralberg, Diana; Gong, Guiquan; Huang, Zhongliang; Ye, Wanhui; Wu, Linfang

2013-01-01

Quantifying the relative contributions of environmental conditions and spatial factors to species distribution can help improve our understanding of the processes that drive diversity patterns. In this study, based on tree inventory, topography and soil data from a 20-ha stem-mapped permanent forest plot in Guangdong Province, China, we evaluated the influence of different ecological processes at different spatial scales using canonical redundancy analysis (RDA) at the community level and multiple linear regression at the species level. At the community level, the proportion of explained variation in species distribution increased with grid-cell sizes, primarily due to a monotonic increase in the explanatory power of environmental variables. At the species level, neither environmental nor spatial factors were important determinants of overstory species' distributions at small cell sizes. However, purely spatial variables explained most of the variation in the distributions of understory species at fine and intermediate cell sizes. Midstory species showed patterns that were intermediate between those of overstory and understory species. At the 20-m cell size, the influence of spatial factors was stronger for more dispersal-limited species, suggesting that much of the spatial structuring in this community can be explained by dispersal limitation. Comparing environmental factors, soil variables had higher explanatory power than did topography for species distribution. However, both topographic and edaphic variables were highly spatial structured. Our results suggested that dispersal limitation has an important influence on fine-intermediate scale (from several to tens of meters) species distribution, while environmental variability facilitates species distribution at intermediate (from ten to tens of meters) and broad (from tens to hundreds of meters) scales.

The association of clinical parameters and ultrasound verified inflammation with patients' and physicians' global assessments in psoriatic arthritis.

PubMed

Lackner, Angelika; Duftner, Christina; Ficjan, Anja; Gretler, Judith; Hermann, Josef; Husic, Rusmir; Graninger, Winfried B; Dejaco, Christian

2016-10-01

To study the association of clinical and/or ultrasound variables with patients' (PGA) and physicians' (EGA) global assessment of disease activity in psoriatic arthritis (PsA). The correlation of these parameters with the discordance between PGA and EGA, as well as with PGA/EGA changes over 6 months was also investigated. Prospective study of 83 consecutive PsA patients with 2 visits scheduled 6 months apart. All patients underwent the following assessments: tender (TJC) and swollen joint count (SJC), PASI, dactylitis and Leeds enthesitis index. PGA, patients' level of pain (pain VAS), EGA, and HAQ were also recorded. Grey scale (GS) and power Doppler (PD) ultrasound were performed at 68 joints (evaluating synovia and tendons) and 14 entheses. Regression analyses were performed to assess the association of these variables with PGA and EGA. Two new variables "PGAminusEGA" and "PGAchange - EGAchange" were developed to explore the discrepancy between PGA and EGA and the consistency of PGA/EGA changes over time, respectively. The parameters explaining most of PGA and EGA variability were pain VAS (30.5%) and SJC (48.5%), respectively. The correlation between EGA and joint counts was stronger in patients with high vs. low levels of ultrasound verified inflammation. PGAminusEGA was mainly explained by pain and SJC. Pain was the most important predictor of PGA change whereas TJC and HAQ were more closely associated with EGA changes. "PGAchange-EGAchange" was linked to pain and SJC. Ultrasound scores were not linked with either of these variables. Pain VAS and joint counts are the most important clinical parameters explaining patients' and physicians' perception of disease activity, whereas the correlation of active inflammation as verified by sonography with these factors is limited. Copyright © 2016 Elsevier Inc. All rights reserved.

Characteristics of German hospitals adopting health IT systems - results from an empirical study.

PubMed

Liebe, Jan-David; Egbert, Nicole; Frey, Andreas; Hübner, Ursula

2011-01-01

Hospital characteristics that facilitate IT adoption have been described by the literature extensively, however with controversial results. The aim of this study therefore is to draw a set of the most important variables from previous studies and include them in a combined analysis for testing their contribution as single factors and their interactions. Total number of IT systems installed and number of clinical IT systems in the hospital were used as criterion variables. Data from a national survey of German hospitals served as basis. Based on a stepwise multiple regression analysis four variables were identified to significantly explain the degree of IT adoption (60% explained variance): 1) hospital size, 2) IT department, 3) reference customer and 4) ownership (private vs. public). Our results replicate previous findings with regard to hospital size and ownership. In addition our study emphasizes the importance of a reliable internal structure for IT projects (existence of an IT department) and the culture of testing and installing most recent IT products (being a reference customer). None of the interactions between factors was significant.

Does ecosystem variability explain phytoplankton diversity? Solving an ecological puzzle with long-term data sets

NASA Astrophysics Data System (ADS)

Sarker, Subrata; Lemke, Peter; Wiltshire, Karen H.

2018-05-01

Explaining species diversity as a function of ecosystem variability is a long-term discussion in community-ecology research. Here, we aimed to establish a causal relationship between ecosystem variability and phytoplankton diversity in a shallow-sea ecosystem. We used long-term data on biotic and abiotic factors from Helgoland Roads, along with climate data to assess the effect of ecosystem variability on phytoplankton diversity. A point cumulative semi-variogram method was used to estimate the long-term ecosystem variability. A Markov chain model was used to estimate dynamical processes of species i.e. occurrence, absence and outcompete probability. We identified that the 1980s was a period of high ecosystem variability while the last two decades were comparatively less variable. Ecosystem variability was found as an important predictor of phytoplankton diversity at Helgoland Roads. High diversity was related to low ecosystem variability due to non-significant relationship between probability of a species occurrence and absence, significant negative relationship between probability of a species occurrence and probability of a species to be outcompeted by others, and high species occurrence at low ecosystem variability. Using an exceptional marine long-term data set, this study established a causal relationship between ecosystem variability and phytoplankton diversity.

Identifying Social Trust in Cross-Country Analysis: Do We Really Measure the Same?

ERIC Educational Resources Information Center

Torpe, Lars; Lolle, Henrik

2011-01-01

Many see trust as an important social resource for the welfare of individuals as well as nations. It is therefore important to be able to identify trust and explain its sources. Cross-country survey analysis has been an important tool in this respect, and often one single variable is used to identify social trust understood as trust in strangers,…

Regional sensitivities of seasonal snowpack to elevation, aspect, and vegetation cover in western North America

NASA Astrophysics Data System (ADS)

Tennant, Christopher J.; Harpold, Adrian A.; Lohse, Kathleen Ann; Godsey, Sarah E.; Crosby, Benjamin T.; Larsen, Laurel G.; Brooks, Paul D.; Van Kirk, Robert W.; Glenn, Nancy F.

2017-08-01

In mountains with seasonal snow cover, the effects of climate change on snowpack will be constrained by landscape-vegetation interactions with the atmosphere. Airborne lidar surveys used to estimate snow depth, topography, and vegetation were coupled with reanalysis climate products to quantify these interactions and to highlight potential snowpack sensitivities to climate and vegetation change across the western U.S. at Rocky Mountain (RM), Northern Basin and Range (NBR), and Sierra Nevada (SNV) sites. In forest and shrub areas, elevation captured the greatest amount of variability in snow depth (16-79%) but aspect explained more variability (11-40%) in alpine areas. Aspect was most important at RM sites where incoming shortwave to incoming net radiation (SW:NetR↓) was highest (˜0.5), capturing 17-37% of snow depth variability in forests and 32-37% in shrub areas. Forest vegetation height exhibited negative relationships with snow depth and explained 3-6% of its variability at sites with greater longwave inputs (NBR and SNV). Variability in the importance of physiography suggests differential sensitivities of snowpack to climate and vegetation change. The high SW:NetR↓ and importance of aspect suggests RM sites may be more responsive to decreases in SW:NetR↓ driven by warming or increases in humidity or cloud cover. Reduced canopy-cover could increase snow depths at SNV sites, and NBR and SNV sites are currently more sensitive to shifts from snow to rain. The consistent importance of aspect and elevation indicates that changes in SW:NetR↓ and the elevation of the rain/snow transition zone could have widespread and varied effects on western U.S. snowpacks.

Evaluating the importance of policy amenable factors in explaining influenza vaccination: a cross-sectional multinational study

PubMed Central

Wheelock, Ana; Miraldo, Marisa; Thomson, Angus; Vincent, Charles; Sevdalis, Nick

2017-01-01

Objectives Despite continuous efforts to improve influenza vaccination coverage, uptake among high-risk groups remains suboptimal. We aimed to identify policy amenable factors associated with vaccination and to measure their importance in order to assist in the monitoring of vaccination sentiment and the design of communication strategies and interventions to improve vaccination rates. Setting The USA, the UK and France. Participants A total of 2412 participants were surveyed across the three countries. Outcome measures Self-reported influenza vaccination. Methods Between March and April 2014, a stratified random sampling strategy was employed with the aim of obtaining nationally representative samples in the USA, the UK and France through online databases and random-digit dialling. Participants were asked about vaccination practices, perceptions and feelings. Multivariable logistic regression was used to identify factors associated with past influenza vaccination. Results The models were able to explain 64%–80% of the variance in vaccination behaviour. Overall, sociopsychological variables, which are inherently amenable to policy, were better at explaining past vaccination behaviour than demographic, socioeconomic and health variables. Explanatory variables included social influence (physician), influenza and vaccine risk perceptions and traumatic childhood experiences. Conclusions Our results indicate that evidence-based sociopsychological items should be considered for inclusion into national immunisation surveys to gauge the public’s views, identify emerging concerns and thus proactively and opportunely address potential barriers and harness vaccination drivers. PMID:28706088

Depressive status explains a significant amount of the variance in COPD assessment test (CAT) scores

PubMed Central

Miravitlles, Marc; Molina, Jesús; Quintano, José Antonio; Campuzano, Anna; Pérez, Joselín; Roncero, Carlos

2018-01-01

Background COPD assessment test (CAT) is a short, easy-to-complete health status tool that has been incorporated into the multidimensional assessment of COPD in order to guide therapy; therefore, it is important to understand the factors determining CAT scores. Methods This is a post hoc analysis of a cross-sectional, observational study conducted in respiratory medicine departments and primary care centers in Spain with the aim of identifying the factors determining CAT scores, focusing particularly on the cognitive status measured by the Mini-Mental State Examination (MMSE) and levels of depression measured by the short Beck Depression Inventory (BDI). Results A total of 684 COPD patients were analyzed; 84.1% were men, the mean age of patients was 68.7 years, and the mean forced expiratory volume in 1 second (%) was 55.1%. Mean CAT score was 21.8. CAT scores correlated with the MMSE score (Pearson’s coefficient r=−0.371) and the BDI (r=0.620), both p<0.001. In the multivariate analysis, the usual COPD severity variables (age, dyspnea, lung function, and comorbidity) together with MMSE and BDI scores were significantly associated with CAT scores and explained 45% of the variability. However, a model including only MMSE and BDI scores explained up to 40% and BDI alone explained 38% of the CAT variance. Conclusion CAT scores are associated with clinical variables of severity of COPD. However, cognitive status and, in particular, the level of depression explain a larger percentage of the variance in the CAT scores than the usual COPD clinical severity variables. PMID:29563782

Depressive status explains a significant amount of the variance in COPD assessment test (CAT) scores.

PubMed

Miravitlles, Marc; Molina, Jesús; Quintano, José Antonio; Campuzano, Anna; Pérez, Joselín; Roncero, Carlos

2018-01-01

COPD assessment test (CAT) is a short, easy-to-complete health status tool that has been incorporated into the multidimensional assessment of COPD in order to guide therapy; therefore, it is important to understand the factors determining CAT scores. This is a post hoc analysis of a cross-sectional, observational study conducted in respiratory medicine departments and primary care centers in Spain with the aim of identifying the factors determining CAT scores, focusing particularly on the cognitive status measured by the Mini-Mental State Examination (MMSE) and levels of depression measured by the short Beck Depression Inventory (BDI). A total of 684 COPD patients were analyzed; 84.1% were men, the mean age of patients was 68.7 years, and the mean forced expiratory volume in 1 second (%) was 55.1%. Mean CAT score was 21.8. CAT scores correlated with the MMSE score (Pearson's coefficient r =-0.371) and the BDI ( r =0.620), both p <0.001. In the multivariate analysis, the usual COPD severity variables (age, dyspnea, lung function, and comorbidity) together with MMSE and BDI scores were significantly associated with CAT scores and explained 45% of the variability. However, a model including only MMSE and BDI scores explained up to 40% and BDI alone explained 38% of the CAT variance. CAT scores are associated with clinical variables of severity of COPD. However, cognitive status and, in particular, the level of depression explain a larger percentage of the variance in the CAT scores than the usual COPD clinical severity variables.

Spatial Scaling of Environmental Variables Improves Species-Habitat Models of Fishes in a Small, Sand-Bed Lowland River

PubMed Central

Radinger, Johannes; Wolter, Christian; Kail, Jochem

2015-01-01

Habitat suitability and the distinct mobility of species depict fundamental keys for explaining and understanding the distribution of river fishes. In recent years, comprehensive data on river hydromorphology has been mapped at spatial scales down to 100 m, potentially serving high resolution species-habitat models, e.g., for fish. However, the relative importance of specific hydromorphological and in-stream habitat variables and their spatial scales of influence is poorly understood. Applying boosted regression trees, we developed species-habitat models for 13 fish species in a sand-bed lowland river based on river morphological and in-stream habitat data. First, we calculated mean values for the predictor variables in five distance classes (from the sampling site up to 4000 m up- and downstream) to identify the spatial scale that best predicts the presence of fish species. Second, we compared the suitability of measured variables and assessment scores related to natural reference conditions. Third, we identified variables which best explained the presence of fish species. The mean model quality (AUC = 0.78, area under the receiver operating characteristic curve) significantly increased when information on the habitat conditions up- and downstream of a sampling site (maximum AUC at 2500 m distance class, +0.049) and topological variables (e.g., stream order) were included (AUC = +0.014). Both measured and assessed variables were similarly well suited to predict species’ presence. Stream order variables and measured cross section features (e.g., width, depth, velocity) were best-suited predictors. In addition, measured channel-bed characteristics (e.g., substrate types) and assessed longitudinal channel features (e.g., naturalness of river planform) were also good predictors. These findings demonstrate (i) the applicability of high resolution river morphological and instream-habitat data (measured and assessed variables) to predict fish presence, (ii) the importance of considering habitat at spatial scales larger than the sampling site, and (iii) that the importance of (river morphological) habitat characteristics differs depending on the spatial scale. PMID:26569119

The importance of lake-specific characteristics for water quality across the continental United States.

PubMed

Read, Emily K; Patil, Vijay P; Oliver, Samantha K; Hetherington, Amy L; Brentrup, Jennifer A; Zwart, Jacob A; Winters, Kirsten M; Corman, Jessica R; Nodine, Emily R; Woolway, R Iestyn; Dugan, Hilary A; Jaimes, Aline; Santoso, Arianto B; Hong, Grace S; Winslow, Luke A; Hanson, Paul C; Weathers, Kathleen C

2015-06-01

Lake water quality is affected by local and regional drivers, including lake physical characteristics, hydrology, landscape position, land cover, land use, geology, and climate. Here, we demonstrate the utility of hypothesis testing within the landscape limnology framework using a random forest algorithm on a national-scale, spatially explicit data set, the United States Environmental Protection Agency's 2007 National Lakes Assessment. For 1026 lakes, we tested the relative importance of water quality drivers across spatial scales, the importance of hydrologic connectivity in mediating water quality drivers, and how the importance of both spatial scale and connectivity differ across response variables for five important in-lake water quality metrics (total phosphorus, total nitrogen, dissolved organic carbon, turbidity, and conductivity). By modeling the effect of water quality predictors at different spatial scales, we found that lake-specific characteristics (e.g., depth, sediment area-to-volume ratio) were important for explaining water quality (54-60% variance explained), and that regionalization schemes were much less effective than lake specific metrics (28-39% variance explained). Basin-scale land use and land cover explained between 45-62% of variance, and forest cover and agricultural land uses were among the most important basin-scale predictors. Water quality drivers did not operate independently; in some cases, hydrologic connectivity (the presence of upstream surface water features) mediated the effect of regional-scale drivers. For example, for water quality in lakes with upstream lakes, regional classification schemes were much less effective predictors than lake-specific variables, in contrast to lakes with no upstream lakes or with no surface inflows. At the scale of the continental United States, conductivity was explained by drivers operating at larger spatial scales than for other water quality responses. The current regulatory practice of using regionalization schemes to guide water quality criteria could be improved by consideration of lake-specific characteristics, which were the most important predictors of water quality at the scale of the continental United States. The spatial extent and high quality of contextual data available for this analysis makes this work an unprecedented application of landscape limnology theory to water quality data. Further, the demonstrated importance of lake morphology over other controls on water quality is relevant to both aquatic scientists and managers.

Climate variables explain neutral and adaptive variation within salmonid metapopulations: The importance of replication in landscape genetics

USGS Publications Warehouse

Hand, Brian K.; Muhlfeld, Clint C.; Wade, Alisa A.; Kovach, Ryan; Whited, Diane C.; Narum, Shawn R.; Matala, Andrew P.; Ackerman, Michael W.; Garner, B. A.; Kimball, John S; Stanford, Jack A.; Luikart, Gordon

2016-01-01

Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population-specific and pairwise FST) within five metapopulations (79 populations, 4583 individuals) of steelhead trout (Oncorhynchus mykiss) in the Columbia River Basin, USA. Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate-related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and FST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin-wide to the metapopulation scale). Sensitivity analysis (leave-one-population-out) revealed consistent relationships between climate variables and FST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes (N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.

Weather explains high annual variation in butterfly dispersal.

PubMed

Kuussaari, Mikko; Rytteri, Susu; Heikkinen, Risto K; Heliölä, Janne; von Bagh, Peter

2016-07-27

Weather conditions fundamentally affect the activity of short-lived insects. Annual variation in weather is therefore likely to be an important determinant of their between-year variation in dispersal, but conclusive empirical studies are lacking. We studied whether the annual variation of dispersal can be explained by the flight season's weather conditions in a Clouded Apollo (Parnassius mnemosyne) metapopulation. This metapopulation was monitored using the mark-release-recapture method for 12 years. Dispersal was quantified for each monitoring year using three complementary measures: emigration rate (fraction of individuals moving between habitat patches), average residence time in the natal patch, and average distance moved. There was much variation both in dispersal and average weather conditions among the years. Weather variables significantly affected the three measures of dispersal and together with adjusting variables explained 79-91% of the variation observed in dispersal. Different weather variables became selected in the models explaining variation in three dispersal measures apparently because of the notable intercorrelations. In general, dispersal rate increased with increasing temperature, solar radiation, proportion of especially warm days, and butterfly density, and decreased with increasing cloudiness, rainfall, and wind speed. These results help to understand and model annually varying dispersal dynamics of species affected by global warming. © 2016 The Author(s).

The Role of Climate Covariability on Crop Yields in the Conterminous United States

DOE PAGES

Leng, Guoyong; Zhang, Xuesong; Huang, Maoyi; ...

2016-09-12

The covariability of temperature (T), precipitation (P) and radiation (R) is an important aspect in understanding the climate influence on crop yields. Here in this paper, we analyze county-level corn and soybean yields and observed climate for the period 1983–2012 to understand how growing-season (June, July and August) mean T, P and R influence crop yields jointly and in isolation across the CONterminous United States (CONUS). Results show that nationally averaged corn and soybean yields exhibit large interannual variability of 21% and 22%, of which 35% and 32% can be significantly explained by T and P, respectively. By including R,more » an additional of 5% in variability can be explained for both crops. Using partial regression analyses, we find that studies that ignore the covariability among T, P, and R can substantially overestimate the sensitivity of crop yields to a single climate factor at the county scale. Further analyses indicate large spatial variation in the relative contributions of different climate variables to the variability of historical corn and soybean yields. Finally, the structure of the dominant climate factors did not change substantially over 1983–2012, confirming the robustness of the findings, which have important implications for crop yield prediction and crop model validations.« less

Soil resources and topography shape local tree community structure in tropical forests

PubMed Central

Baldeck, Claire A.; Harms, Kyle E.; Yavitt, Joseph B.; John, Robert; Turner, Benjamin L.; Valencia, Renato; Navarrete, Hugo; Davies, Stuart J.; Chuyong, George B.; Kenfack, David; Thomas, Duncan W.; Madawala, Sumedha; Gunatilleke, Nimal; Gunatilleke, Savitri; Bunyavejchewin, Sarayudh; Kiratiprayoon, Somboon; Yaacob, Adzmi; Supardi, Mohd N. Nur; Dalling, James W.

2013-01-01

Both habitat filtering and dispersal limitation influence the compositional structure of forest communities, but previous studies examining the relative contributions of these processes with variation partitioning have primarily used topography to represent the influence of the environment. Here, we bring together data on both topography and soil resource variation within eight large (24–50 ha) tropical forest plots, and use variation partitioning to decompose community compositional variation into fractions explained by spatial, soil resource and topographic variables. Both soil resources and topography account for significant and approximately equal variation in tree community composition (9–34% and 5–29%, respectively), and all environmental variables together explain 13–39% of compositional variation within a plot. A large fraction of variation (19–37%) was spatially structured, yet unexplained by the environment, suggesting an important role for dispersal processes and unmeasured environmental variables. For the majority of sites, adding soil resource variables to topography nearly doubled the inferred role of habitat filtering, accounting for variation in compositional structure that would previously have been attributable to dispersal. Our results, illustrated using a new graphical depiction of community structure within these plots, demonstrate the importance of small-scale environmental variation in shaping local community structure in diverse tropical forests around the globe. PMID:23256196

An explanatory model of academic achievement based on aptitudes, goal orientations, self-concept and learning strategies.

PubMed

Miñano Pérez, Pablo; Castejón Costa, Juan-Luis; Gilar Corbí, Raquel

2012-03-01

As a result of studies examining factors involved in the learning process, various structural models have been developed to explain the direct and indirect effects that occur between the variables in these models. The objective was to evaluate a structural model of cognitive and motivational variables predicting academic achievement, including general intelligence, academic self-concept, goal orientations, effort and learning strategies. The sample comprised of 341 Spanish students in the first year of compulsory secondary education. Different tests and questionnaires were used to evaluate each variable, and Structural Equation Modelling (SEM) was applied to contrast the relationships of the initial model. The model proposed had a satisfactory fit, and all the hypothesised relationships were significant. General intelligence was the variable most able to explain academic achievement. Also important was the direct influence of academic self-concept on achievement, goal orientations and effort, as well as the mediating ability of effort and learning strategies between academic goals and final achievement.

Transits, Spots, and Eclipses: The Sunís Role in Pedagogy and Outreach (Abstract)

NASA Astrophysics Data System (ADS)

Larsen, K.

2018-06-01

(Abstract only) While most people observe variable stars at night, the observers of the AAVSO Solar Section make a single observation per day, but only if it is sunny, because our variable is the Sun itself. While the Sun can play an important role in astronomy outreach and pedagogy in general, as demonstrated by the recent 2017 eclipse, it can also serve as an ambassador for variable stars. This talk will examine how our sun can be used as a tool to explain several types of variable star behaviors, including transits, spots, and eclipses.

A meta-analysis and statistical modelling of nitrates in groundwater at the African scale

NASA Astrophysics Data System (ADS)

Ouedraogo, Issoufou; Vanclooster, Marnik

2016-06-01

Contamination of groundwater with nitrate poses a major health risk to millions of people around Africa. Assessing the space-time distribution of this contamination, as well as understanding the factors that explain this contamination, is important for managing sustainable drinking water at the regional scale. This study aims to assess the variables that contribute to nitrate pollution in groundwater at the African scale by statistical modelling. We compiled a literature database of nitrate concentration in groundwater (around 250 studies) and combined it with digital maps of physical attributes such as soil, geology, climate, hydrogeology, and anthropogenic data for statistical model development. The maximum, medium, and minimum observed nitrate concentrations were analysed. In total, 13 explanatory variables were screened to explain observed nitrate pollution in groundwater. For the mean nitrate concentration, four variables are retained in the statistical explanatory model: (1) depth to groundwater (shallow groundwater, typically < 50 m); (2) recharge rate; (3) aquifer type; and (4) population density. The first three variables represent intrinsic vulnerability of groundwater systems to pollution, while the latter variable is a proxy for anthropogenic pollution pressure. The model explains 65 % of the variation of mean nitrate contamination in groundwater at the African scale. Using the same proxy information, we could develop a statistical model for the maximum nitrate concentrations that explains 42 % of the nitrate variation. For the maximum concentrations, other environmental attributes such as soil type, slope, rainfall, climate class, and region type improve the prediction of maximum nitrate concentrations at the African scale. As to minimal nitrate concentrations, in the absence of normal distribution assumptions of the data set, we do not develop a statistical model for these data. The data-based statistical model presented here represents an important step towards developing tools that will allow us to accurately predict nitrate distribution at the African scale and thus may support groundwater monitoring and water management that aims to protect groundwater systems. Yet they should be further refined and validated when more detailed and harmonized data become available and/or combined with more conceptual descriptions of the fate of nutrients in the hydrosystem.

Influence of cognition and symptoms of schizophrenia on IADL performance.

PubMed

Lipskaya, Lena; Jarus, Tal; Kotler, Moshe

2011-09-01

People with schizophrenia experience difficulties with instrumental activities of daily living (IADL), which are required for independent living. Yet, factors that influence IADL performance are still poorly understood. Identification of such factors will contribute to the rehabilitation process and recovery. The present study aimed to examine the influence of cognitive abilities, schizophrenia symptoms, and demographic variables on IADL functioning during acute hospital admission. The participants were 81 adults with DSM-IV chronic schizophrenia. They were assessed on the Revised Observed Tasks of Daily Living (OTDL-R), the Positive and Negative Syndrome Scale (PANSS), the Neurobehavioral Cognitive Status Examination (Cognistat), and the Kitchen Task Assessment (KTA) at acute hospitalization. The prediction model of IADL performance at this time consists of executive functioning (explained 21% of variance), memory and abstract thinking (explained 13.5%), negative symptoms (explained 13%), age of illness onset and years of education (explained 8%). The total explained variance is 53.5%. These results provide evidence-based guidelines for the evaluation process in inpatient settings. Such guidelines are important since planning of intervention processes and appropriate community integration programs often occurs during acute hospitalization, while the structured nature of inpatient settings limits natural variability in occupational performance.

Multivariate control of plant species richness and community biomass in blackland prairie

USGS Publications Warehouse

Weiher, E.; Forbes, S.; Schauwecker, T.; Grace, J.B.

2004-01-01

Recent studies have shown that patterns of plant species richness and community biomass are best understood in a multivariate context. The objective of this study was to develop and evaluate a multivariate hypothesis about how herbaceous biomass and richness relate to gradients in soil conditions and woody plant cover in blackland prairies. Structural equation modeling was used to investigate how soil characteristics and shade by scattered Juniperus virginiana trees relate to standing biomass and species richness in 99 0.25 m2 quadrats collected in eastern Mississippi, USA. Analysis proceeded in two stages. In the first stage, we evaluated the hypothesis that correlations among soil parameters could be represented by two underlying (latent) soil factors, mineral content and organic content. In the second stage, we evaluated the hypothesis that richness and biomass were related to (1) soil properties, (2) tree canopy extent, and (3) each other (i.e. reciprocal effects between richness and biomass). With some modification to the details of the original model, it was found that soil properties could be represented as two latent variables. In the overall model, 51% and 53% of the observed variation in richness and biomass were explained. The order of importance for variables explaining variations in richness was (1) soil organic content, (2) soil mineral content, (3) community biomass, and (4) tree canopy extent. The order of importance for variables explaining biomass was (1) tree canopy and (2) soil organic content, with neither soil mineral content nor species richness explaining significant variation in biomass. Based on these findings, we conclude that variations in richness are uniquely related to both variations in soil conditions and variations in herbaceous biomass. We further conclude that there is no evidence in these data for effects of species richness on biomass.

The association between neighbourhoods and educational achievement, a systematic review and meta-analysis.

PubMed

Nieuwenhuis, Jaap; Hooimeijer, Pieter

2016-01-01

Many studies have examined the effects of neighbourhoods on educational outcomes. The results of these studies are often conflicting, even if the same independent variables (such as poverty, educational climate, social disorganisation, or ethnic composition) are used. A systematic meta-analysis may help to resolve this lack of external validity. We identified 5516 articles from which we selected 88 that met all of the inclusion criteria. Using meta-regression, we found that the relation between neighbourhoods and individual educational outcomes is a function of neighbourhood poverty, the neighbourhood's educational climate, the proportion of ethnic/migrant groups, and social disorganisation in the neighbourhood. The variance in the findings from different studies can partly be explained by the sampling design and the type of model used in each study. More important is the use of control variables (school, family SES, and parenting variables) in explaining the variation in the strength of neighbourhood effects.

Predicting ecosystem stability from community composition and biodiversity.

PubMed

de Mazancourt, Claire; Isbell, Forest; Larocque, Allen; Berendse, Frank; De Luca, Enrica; Grace, James B; Haegeman, Bart; Wayne Polley, H; Roscher, Christiane; Schmid, Bernhard; Tilman, David; van Ruijven, Jasper; Weigelt, Alexandra; Wilsey, Brian J; Loreau, Michel

2013-05-01

As biodiversity is declining at an unprecedented rate, an important current scientific challenge is to understand and predict the consequences of biodiversity loss. Here, we develop a theory that predicts the temporal variability of community biomass from the properties of individual component species in monoculture. Our theory shows that biodiversity stabilises ecosystems through three main mechanisms: (1) asynchrony in species' responses to environmental fluctuations, (2) reduced demographic stochasticity due to overyielding in species mixtures and (3) reduced observation error (including spatial and sampling variability). Parameterised with empirical data from four long-term grassland biodiversity experiments, our prediction explained 22-75% of the observed variability, and captured much of the effect of species richness. Richness stabilised communities mainly by increasing community biomass and reducing the strength of demographic stochasticity. Our approach calls for a re-evaluation of the mechanisms explaining the effects of biodiversity on ecosystem stability. © 2013 Blackwell Publishing Ltd/CNRS.

Predicting ecosystem stability from community composition and biodiversity

USGS Publications Warehouse

Mazancourt, Claire de; Isbell, Forest; Larocque, Allen; Berendse, Frank; De Luca, Enrica; Grace, James B.; Haegeman, Bart; Polley, H. Wayne; Roscher, Christiane; Schmid, Bernhard; Tilman, David; van Ruijven, Jasper; Weigelt, Alexandra; Wilsey, Brian J.; Loreau, Michel

2013-01-01

As biodiversity is declining at an unprecedented rate, an important current scientific challenge is to understand and predict the consequences of biodiversity loss. Here, we develop a theory that predicts the temporal variability of community biomass from the properties of individual component species in monoculture. Our theory shows that biodiversity stabilises ecosystems through three main mechanisms: (1) asynchrony in species’ responses to environmental fluctuations, (2) reduced demographic stochasticity due to overyielding in species mixtures and (3) reduced observation error (including spatial and sampling variability). Parameterised with empirical data from four long-term grassland biodiversity experiments, our prediction explained 22–75% of the observed variability, and captured much of the effect of species richness. Richness stabilised communities mainly by increasing community biomass and reducing the strength of demographic stochasticity. Our approach calls for a re-evaluation of the mechanisms explaining the effects of biodiversity on ecosystem stability.

Analysis of potential factors affecting microbiological cultures in tissue donors during procurement.

PubMed

Lannau, B; Van Geyt, C; Van Maele, G; Beele, H

2015-03-01

During the procurement of musculoskeletal grafts contamination may occur. As this might be detrimental for the acceptor, it is important to know which variables influence this occurrence and to alter procurement protocols accordingly. From 2004 to 2012 we gathered information on 6,428 allografts obtained from 291 donors. Using a multiple regression model we attempted to determine the factors that influence the contamination risk during procurement. We used the following variables: cause of death, type of hospital (i.e. university hospital vs. general hospital), previous blood vessel donation, previous organ donation, donor age, time between death and the start of the procurement, duration of the procurement, number of people attending the procurement and the number of procured grafts. The multiple regression model was only able to explain 5 % of the variability of the used outcome variable. None of the variables examined appear to have an important influence on the contamination risk.

Boosted Regression Tree Models to Explain Watershed ...

EPA Pesticide Factsheets

Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base-flow conditions. Factors that affect instream biological components, based on the Index of Biotic Integrity (IBI), were also analyzed. Seasonal BRT models at two spatial scales (watershed and riparian buffered area [RBA]) for nitrite-nitrate (NO2-NO3), total Kjeldahl nitrogen, and total phosphorus (TP) and annual models for the IBI score were developed. Two primary factors — location within the watershed (i.e., geographic position, stream order, and distance to a downstream confluence) and percentage of urban land cover (both scales) — emerged as important predictor variables. Latitude and longitude interacted with other factors to explain the variability in summer NO2-NO3 concentrations and IBI scores. BRT results also suggested that location might be associated with indicators of sources (e.g., land cover), runoff potential (e.g., soil and topographic factors), and processes not easily represented by spatial data indicators. Runoff indicators (e.g., Hydrological Soil Group D and Topographic Wetness Indices) explained a substantial portion of the variability in nutrient concentrations as did point sources for TP in the summer months. The results from our BRT approach can help prioritize areas for nutrient management in mixed-use and heavily impacted watershed

Similar Processes but Different Environmental Filters for Soil Bacterial and Fungal Community Composition Turnover on a Broad Spatial Scale

PubMed Central

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P. A.; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

PubMed

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Natural habitats matter: Determinants of spatial pattern in the composition of animal assemblages of the Czech Republic

NASA Astrophysics Data System (ADS)

Divíšek, Jan; Zelený, David; Culek, Martin; Št'astný, Karel

2014-08-01

Studies that explore species-environment relationships at a broad scale are usually limited by the availability of sufficient habitat description, which is often too coarse to differentiate natural habitat patches. Therefore, it is not well understood how the distribution of natural habitats affects broad-scale patterns in the distribution of animal species. In this study, we evaluate the role of field-mapped natural habitats, land-cover types derived from remote sensing and climate on the composition of assemblages of five distinct animal groups, namely non-volant mammals, birds, reptiles, amphibians and butterflies native to the Czech Republic. First, we used variation partitioning based on redundancy analysis to evaluate the extent to which the environmental variables and their spatial structure might underlie the observed spatial patterns in the composition of animal assemblages. Second, we partitioned variations explained by climate, natural habitats and land-cover to compare their relative importance. Finally, we tested the independent effects of each variable in order to evaluate the significance of their contributions to the environmental model. Our results showed that spatial patterns in the composition of assemblages of almost all the considered animal groups may be ascribed mostly to variations in the environment. Although the shared effects of climatic variables, natural habitats and land-cover types explained the largest proportion of variation in each animal group, the variation explained purely by natural habitats was always higher than the variation explained purely by climate or land-cover. We conclude that most spatial variation in the composition of assemblages of almost all animal groups probably arises from biological processes operating within a spatially structured environment and suggest that natural habitats are important to explain observed patterns because they often perform better than habitat descriptions based on remote sensing. This underlines the value of using appropriate habitat data, for which high-resolution and large-area field-mapping projects are necessary.

Virtual water trade patterns in relation to environmental and socioeconomic factors: a case study for Tunisia

NASA Astrophysics Data System (ADS)

Chouchane, Hatem; Krol, Maarten; Hoekstra, Arjen

2016-04-01

Water scarcity is among the main problems faced by many societies. Growing water demands put increasing pressure on local water resources, especially in water-short countries. Virtual water trade can play a key role in filling the gap between local demands and supply. This study aims to analyze the changes in virtual water trade of Tunisia in relation to environmental and socio-economic factors such as GDP, irrigated land, precipitation, population and water scarcity. The water footprint is estimated using Aquacrop for six crops over the period 1981-2010 at daily basis and a spatial resolution of 5 by 5 arc minutes. Virtual water trade is quantified at yearly basis. Regression models are used to investigate changes in virtual water trade in relation to various environmental and socio-economic factors. The explaining variables are selected in order to help understanding the trend and the inter-annual variability of the net virtual water import; GDP, population and irrigated land are hypothesized to explain the trend, and precipitation and water scarcity to explain variability. The selected crops are divided into three baskets. The first basket includes the two most imported crops, which are mainly rain-fed (wheat and barley). The second basket contains the two most exported crops, which are both irrigated and rain-fed (olives and dates). In the last basket we find the two highest economic blue water productive crops, which are mainly irrigated (tomatoes and potatoes). The results show the impact of each factor on net virtual water import of the selected crops during the period 1981-2010. Keywords: Virtual water, trade patterns, Aquacrop, Tunisia, water scarcity, water footprint.

The role of hydrodynamics in shaping the composition and architecture of epilithic biofilms in fluvial ecosystems.

PubMed

Risse-Buhl, Ute; Anlanger, Christine; Kalla, Katalin; Neu, Thomas R; Noss, Christian; Lorke, Andreas; Weitere, Markus

2017-12-15

Previous laboratory and on-site experiments have highlighted the importance of hydrodynamics in shaping biofilm composition and architecture. In how far responses to hydrodynamics can be found in natural flows under the complex interplay of environmental factors is still unknown. In this study we investigated the effect of near streambed turbulence in terms of turbulent kinetic energy (TKE) on the composition and architecture of biofilms matured in two mountainous streams differing in dissolved nutrient concentrations. Over both streams, TKE significantly explained 7% and 8% of the variability in biofilm composition and architecture, respectively. However, effects were more pronounced in the nutrient richer stream, where TKE significantly explained 12% and 3% of the variability in biofilm composition and architecture, respectively. While at lower nutrient concentrations seasonally varying factors such as stoichiometry of dissolved nutrients (N/P ratio) and light were more important and explained 41% and 6% of the variability in biofilm composition and architecture, respectively. Specific biofilm features such as elongated ripples and streamers, which were observed in response to the uniform and unidirectional flow in experimental settings, were not observed. Microbial biovolume and surface area covered by the biofilm canopy increased with TKE, while biofilm thickness and porosity where not affected or decreased. These findings indicate that under natural flows where near bed flow velocities and turbulence intensities fluctuate with time and space, biofilms became more compact. They spread uniformly on the mineral surface as a film of densely packed coccoid cells appearing like cobblestone pavement. The compact growth of biofilms seemed to be advantageous for resisting hydrodynamic shear forces in order to avoid displacement. Thus, near streambed turbulence can be considered as important factor shaping the composition and architecture of biofilms grown under natural flows. Copyright © 2017 Elsevier Ltd. All rights reserved.

Correlates of Injury-forced Work Reduction for Massage Therapists and Bodywork Practitioners.

PubMed

Blau, Gary; Monos, Christopher; Boyer, Ed; Davis, Kathleen; Flanagan, Richard; Lopez, Andrea; Tatum, Donna S

2013-01-01

Injury-forced work reduction (IFWR) has been acknowledged as an all-too-common occurrence for massage therapists and bodywork practitioners (M & Bs). However, little prior research has specifically investigated demographic, work attitude, and perceptual correlates of IFWR among M & Bs. To test two hypotheses, H1 and H2. H1 is that the accumulated cost variables set ( e.g., accumulated costs, continuing education costs) will account for a significant amount of IFWR variance beyond control/demographic (e.g., social desirability response bias, gender, years in practice, highest education level) and work attitude/perception variables (e.g., job satisfaction, affective occupation commitment, occupation identification, limited occupation alternatives) sets. H2 is that the two exhaustion variables (i.e., physical exhaustion, work exhaustion) set will account for significant IFWR variance beyond control/demographic, work attitude/perception, and accumulated cost variables sets. An online survey sample of 2,079 complete-data M & Bs was collected. Stepwise regression analysis was used to test the study hypotheses. The research design first controlled for control/demographic (Step1) and work attitude/perception variables sets (Step 2), before then testing for the successive incremental impact of two variable sets, accumulated costs (Step 3) and exhaustion variables (Step 4) for explaining IFWR. RESULTS SUPPORTED BOTH STUDY HYPOTHESES: accumulated cost variables set (H1) and exhaustion variables set (H2) each significantly explained IFWR after the control/demographic and work attitude/perception variables sets. The most important correlate for explaining IFWR was higher physical exhaustion, but work exhaustion was also significant. It is not just physical "wear and tear", but also "mental fatigue", that can lead to IFWR for M & Bs. Being female, having more years in practice, and having higher continuing education costs were also significant correlates of IFWR. Lower overall levels of work exhaustion, physical exhaustion, and IFWR were found in the present sample. However, since both types of exhaustion significantly and positively impact IFWR, taking sufficient time between massages and, if possible, varying one's massage technique to replenish one's physical and mental energy seem important. Failure to take required continuing education units, due to high costs, also increases risk for IFWR. Study limitations and future research issues are discussed.

Evaluating the importance of policy amenable factors in explaining influenza vaccination: a cross-sectional multinational study.

PubMed

Wheelock, Ana; Miraldo, Marisa; Thomson, Angus; Vincent, Charles; Sevdalis, Nick

2017-07-12

Despite continuous efforts to improve influenza vaccination coverage, uptake among high-risk groups remains suboptimal. We aimed to identify policy amenable factors associated with vaccination and to measure their importance in order to assist in the monitoring of vaccination sentiment and the design of communication strategies and interventions to improve vaccination rates. The USA, the UK and France. A total of 2412 participants were surveyed across the three countries. Self-reported influenza vaccination. Between March and April 2014, a stratified random sampling strategy was employed with the aim of obtaining nationally representative samples in the USA, the UK and France through online databases and random-digit dialling. Participants were asked about vaccination practices, perceptions and feelings. Multivariable logistic regression was used to identify factors associated with past influenza vaccination. The models were able to explain 64%-80% of the variance in vaccination behaviour. Overall, sociopsychological variables, which are inherently amenable to policy, were better at explaining past vaccination behaviour than demographic, socioeconomic and health variables. Explanatory variables included social influence (physician), influenza and vaccine risk perceptions and traumatic childhood experiences. Our results indicate that evidence-based sociopsychological items should be considered for inclusion into national immunisation surveys to gauge the public's views, identify emerging concerns and thus proactively and opportunely address potential barriers and harness vaccination drivers. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Shade tree spatial structure and pod production explain frosty pod rot intensity in cacao agroforests, Costa Rica.

PubMed

Gidoin, Cynthia; Avelino, Jacques; Deheuvels, Olivier; Cilas, Christian; Bieng, Marie Ange Ngo

2014-03-01

Vegetation composition and plant spatial structure affect disease intensity through resource and microclimatic variation effects. The aim of this study was to evaluate the independent effect and relative importance of host composition and plant spatial structure variables in explaining disease intensity at the plot scale. For that purpose, frosty pod rot intensity, a disease caused by Moniliophthora roreri on cacao pods, was monitored in 36 cacao agroforests in Costa Rica in order to assess the vegetation composition and spatial structure variables conducive to the disease. Hierarchical partitioning was used to identify the most causal factors. Firstly, pod production, cacao tree density and shade tree spatial structure had significant independent effects on disease intensity. In our case study, the amount of susceptible tissue was the most relevant host composition variable for explaining disease intensity by resource dilution. Indeed, cacao tree density probably affected disease intensity more by the creation of self-shading rather than by host dilution. Lastly, only regularly distributed forest trees, and not aggregated or randomly distributed forest trees, reduced disease intensity in comparison to plots with a low forest tree density. A regular spatial structure is probably crucial to the creation of moderate and uniform shade as recommended for frosty pod rot management. As pod production is an important service expected from these agroforests, shade tree spatial structure may be a lever for integrated management of frosty pod rot in cacao agroforests.

Environmental suitability for Lutzomyia longipalpis in a subtropical city with a recently established visceral leishmaniasis transmission cycle, Argentina.

PubMed

Berrozpe, Pablo; Lamattina, Daniela; Santini, María Soledad; Araujo, Analía Vanesa; Utgés, María Eugenia; Salomón, Oscar Daniel

2017-10-01

Visceral leishmaniasis (VL) is an endemic disease in northeastern Argentina including the Corrientes province, where the presence of the vector and canine cases of VL were recently confirmed in December 2008. The objective of this study was to assess the modelling of micro- and macro-habitat variables to evaluate the urban environmental suitability for the spatial distribution of Lutzomyia longipalpis presence and abundance in an urban scenario. Sampling of 45 sites distributed throughout Corrientes city (Argentina) was carried out using REDILA-BL minilight traps in December 2013. The sampled specimens were identified according to methods described by Galati (2003). The analysis of variables derived from the processing of satellite images (macro-habitat variables) and from the entomological sampling and surveys (micro-habitat variables) was performed using the statistical software R. Three generalised linear models were constructed composed of micro- and macro-habitat variables to explain the spatial distribution of the abundance of Lu. longipalpis and one composed of micro-habitat variables to explain the occurrence of the vector. A total of 609 phlebotominae belonging to five species were collected, of which 56% were Lu. longipalpis. In addition, the presence of Nyssomyia neivai and Migonemya migonei, which are vectors of tegumentary leishmaniasis, were also documented and represented 34.81% and 6.74% of the collections, respectively. The explanatory variable normalised difference vegetation index (NDVI) described the abundance distribution, whereas the presence of farmyard animals was important for explaining both the abundance and the occurrence of the vector. The results contribute to the identification of variables that can be used to establish priority areas for entomological surveillance and provide an efficient transfer tool for the control and prevention of vector-borne diseases.

Environmental suitability for Lutzomyia longipalpis in a subtropical city with a recently established visceral leishmaniasis transmission cycle, Argentina

PubMed Central

Berrozpe, Pablo; Lamattina, Daniela; Santini, María Soledad; Araujo, Analía Vanesa; Utgés, María Eugenia; Salomón, Oscar Daniel

2017-01-01

BACKGROUND Visceral leishmaniasis (VL) is an endemic disease in northeastern Argentina including the Corrientes province, where the presence of the vector and canine cases of VL were recently confirmed in December 2008. OBJECTIVES The objective of this study was to assess the modelling of micro- and macro-habitat variables to evaluate the urban environmental suitability for the spatial distribution of Lutzomyia longipalpis presence and abundance in an urban scenario. METHODS Sampling of 45 sites distributed throughout Corrientes city (Argentina) was carried out using REDILA-BL minilight traps in December 2013. The sampled specimens were identified according to methods described by Galati (2003). The analysis of variables derived from the processing of satellite images (macro-habitat variables) and from the entomological sampling and surveys (micro-habitat variables) was performed using the statistical software R. Three generalised linear models were constructed composed of micro- and macro-habitat variables to explain the spatial distribution of the abundance of Lu. longipalpis and one composed of micro-habitat variables to explain the occurrence of the vector. FINDINGS A total of 609 phlebotominae belonging to five species were collected, of which 56% were Lu. longipalpis. In addition, the presence of Nyssomyia neivai and Migonemya migonei, which are vectors of tegumentary leishmaniasis, were also documented and represented 34.81% and 6.74% of the collections, respectively. The explanatory variable normalised difference vegetation index (NDVI) described the abundance distribution, whereas the presence of farmyard animals was important for explaining both the abundance and the occurrence of the vector. MAIN CONCLUSIONS The results contribute to the identification of variables that can be used to establish priority areas for entomological surveillance and provide an efficient transfer tool for the control and prevention of vector-borne diseases. PMID:28953995

Mediating Factors Explaining the Association Between Sexual Minority Status and Dating Violence.

PubMed

Martin-Storey, Alexa; Fromme, Kim

2017-08-01

Dating violence presents a serious threat for individual health and well-being. A growing body of literature suggests that starting in adolescence, individuals with sexual minority identities (e.g., individuals who identify as gay, lesbian, or bisexual) may be at an increased risk for dating violence compared with heterosexuals. Research has not, however, identified the mechanisms that explain this vulnerability. Using a diverse sample of young adults ( n = 2,474), the current study explored how minority stress theory, revictimization theory, sex of sexual partners, and risky sexual behavior explained differences in dating violence between sexual minority and heterosexual young adults. Initial analyses suggested higher rates of dating violence among individuals who identified as bisexual, and individuals who identified as gay or lesbian when compared with heterosexuals, and further found that these associations failed to differ across gender. When mediating and control variables were included in the analyses, however, the association between both sexual minority identities and higher levels of dating violence became nonsignificant. Of particular interest was the role of discrimination, which mediated the association between bisexual identity and dating violence. Other factors, including sex and number of sexual partners, alcohol use, and childhood maltreatment, were associated with higher rates of dating violence but did not significantly explain vulnerability among sexual minority individuals compared with their heterosexual peers. These findings suggest the importance of minority stress theory in explaining vulnerability to dating violence victimization among bisexuals in particular, and generally support the importance of sexual-minority specific variables in understanding risk for dating violence within this vulnerable population.

Optical Properties of Three Beach Waters: Implications for Predictive Modeling of Enterococci

EPA Science Inventory

Sunlight plays an important role in the inactivation of fecal indicator bacteria in recreational waters. Solar radiation can explain temporal trends in bacterial counts and is commonly used as an explanatory variable in predictive models. Broadband surface radiation provides a ba...

The differential effect of the teacher-student interpersonal relationship on student outcomes for students with different ethnic backgrounds.

PubMed

den Brok, Perry; van Tartwijk, Jan; Wubbels, Theo; Veldman, Ietje

2010-06-01

The differential effectiveness of schools and teachers receives a growing interest, but few studies focused on the relevance of student ethnicity for this effectiveness and only a small number of these studies investigated teaching in terms of the teacher-student interpersonal relationship. Furthermore, the methodology employed often restricted researchers to investigating direct effects between variables across large samples of students. This study uses causal modelling to investigate associations between student background characteristics, students' perceptions of the teacher-student interpersonal relationship, and student outcomes, across and within several population subgroups in Dutch secondary multi-ethnic classes. Multi-group structural equation modelling was used to investigate causal paths between variables in four ethnic groups: Dutch (N=387), Turkish first- and second-generation immigrant students (N=267), Moroccan first and second generation (N=364), and Surinamese second-generation students (N=101). Different structural paths were necessary to explain associations between variables in the different (sub) groups. Different amounts of variance in student attitudes could be explained by these variables. The teacher-student interpersonal relationship is more important for students with a non-Dutch background than for students with a Dutch background. Results suggest that the teacher-student relationship is more important for second generation than for first-generation immigrant students. Multi-group causal model analyses can provide a better, more differentiated picture of the associations between student background variables, teacher behaviour, and student outcomes than do more traditional types of analyses.

Testing a theory of aircraft noise annoyance: a structural equation analysis.

PubMed

Kroesen, Maarten; Molin, Eric J E; van Wee, Bert

2008-06-01

Previous research has stressed the relevance of nonacoustical factors in the perception of aircraft noise. However, it is largely empirically driven and lacks a sound theoretical basis. In this paper, a theoretical model which explains noise annoyance based on the psychological stress theory is empirically tested. The model is estimated by applying structural equation modeling based on data from residents living in the vicinity of Amsterdam Airport Schiphol in The Netherlands. The model provides a good model fit and indicates that concern about the negative health effects of noise and pollution, perceived disturbance, and perceived control and coping capacity are the most important variables that explain noise annoyance. Furthermore, the model provides evidence for the existence of two reciprocal relationships between (1) perceived disturbance and noise annoyance and (2) perceived control and coping capacity and noise annoyance. Lastly, the model yielded two unexpected results. Firstly, the variables noise sensitivity and fear related to the noise source were unable to explain additional variance in the endogenous variables of the model and were therefore excluded from the model. And secondly, the size of the total effect of noise exposure on noise annoyance was relatively small. The paper concludes with some recommended directions for further research.

The Personal and Contextual Contributors to School Belongingness among Primary School Students

PubMed Central

Vaz, Sharmila; Falkmer, Marita; Ciccarelli, Marina; Passmore, Anne; Parsons, Richard; Tan, Tele; Falkmer, Torbjorn

2015-01-01

School belongingness has gained currency among educators and school health professionals as an important determinant of adolescent health. The current cross-sectional study presents the 15 most significant personal and contextual factors that collectively explain 66.4% (two-thirds) of the variability in 12-year old students’ perceptions of belongingness in primary school. The study is part of a larger longitudinal study investigating the factors associated with student adjustment in the transition from primary to secondary school. The study found that girls and students with disabilities had higher school belongingness scores than boys, and their typically developing counterparts respectively; and explained 2.5% of the variability in school belongingness. The majority (47.1% out of 66.4%) of the variability in school belongingness was explained by student personal factors, such as social acceptance, physical appearance competence, coping skills, and social affiliation motivation; followed by parental expectations (3% out of 66.4%), and school-based factors (13.9% out of 66.4%) such as, classroom involvement, task-goal structure, autonomy provision, cultural pluralism, and absence of bullying. Each of the identified contributors of primary school belongingness can be shaped through interventions, system changes, or policy reforms. PMID:25876074

Habitat characteristics affecting fish assemblages on a Hawaiian coral reef

USGS Publications Warehouse

Friedlander, A.M.; Parrish, J.D.

1998-01-01

Habitat characteristics of a reef were examined as potential influences on fish assemblage structure, using underwater visual census to estimate numbers and biomass of all fishes visible on 42 benthic transects and making quantitative measurements of 13 variables of the corresponding physical habitat and sessile biota. Fish assemblages in the diverse set of benthic habitats were grouped by detrended correspondence analysis, and associated with six major habitat types. Statistical differences were shown between a number of these habitat types for various ensemble variables of the fish assemblages. Overall, both for complete assemblages and for component major trophic and mobility guilds, these variables tended to have higher values where reef substratum was more structurally or topographically complex, and closer to reef edges. When study sites were separately divided into five depth strata, the deeper strata tended to have statistically higher values of ensemble variables for the fish assemblages. Patterns with depth varied among the various trophic and mobility guilds. Multiple linear regression models indicated that for the complete assemblages and for most trophic and mobility guilds, a large part of the variability for most ensemble variables was explained by measures of holes in the substratum, with important contributions from measured substratum rugosity and depth. A strong linear relationship found by regression of mean fish length on mean volume of holes in the reef surface emphasized the importance of shelter for fish assemblages. Results of this study may have practical applications in designing reserve areas as well as theoretical value in helping to explain the organization of reef fish assemblages.

Slowing down of North Pacific climate variability and its implications for abrupt ecosystem change.

PubMed

Boulton, Chris A; Lenton, Timothy M

2015-09-15

Marine ecosystems are sensitive to stochastic environmental variability, with higher-amplitude, lower-frequency--i.e., "redder"--variability posing a greater threat of triggering large ecosystem changes. Here we show that fluctuations in the Pacific Decadal Oscillation (PDO) index have slowed down markedly over the observational record (1900-present), as indicated by a robust increase in autocorrelation. This "reddening" of the spectrum of climate variability is also found in regionally averaged North Pacific sea surface temperatures (SSTs), and can be at least partly explained by observed deepening of the ocean mixed layer. The progressive reddening of North Pacific climate variability has important implications for marine ecosystems. Ecosystem variables that respond linearly to climate forcing will have become prone to much larger variations over the observational record, whereas ecosystem variables that respond nonlinearly to climate forcing will have become prone to more frequent "regime shifts." Thus, slowing down of North Pacific climate variability can help explain the large magnitude and potentially the quick succession of well-known abrupt changes in North Pacific ecosystems in 1977 and 1989. When looking ahead, despite model limitations in simulating mixed layer depth (MLD) in the North Pacific, global warming is robustly expected to decrease MLD. This could potentially reverse the observed trend of slowing down of North Pacific climate variability and its effects on marine ecosystems.

Predicting Pre-planting Risk of Stagonospora nodorum blotch in Winter Wheat Using Machine Learning Models.

PubMed

Mehra, Lucky K; Cowger, Christina; Gross, Kevin; Ojiambo, Peter S

2016-01-01

Pre-planting factors have been associated with the late-season severity of Stagonospora nodorum blotch (SNB), caused by the fungal pathogen Parastagonospora nodorum, in winter wheat (Triticum aestivum). The relative importance of these factors in the risk of SNB has not been determined and this knowledge can facilitate disease management decisions prior to planting of the wheat crop. In this study, we examined the performance of multiple regression (MR) and three machine learning algorithms namely artificial neural networks, categorical and regression trees, and random forests (RF), in predicting the pre-planting risk of SNB in wheat. Pre-planting factors tested as potential predictor variables were cultivar resistance, latitude, longitude, previous crop, seeding rate, seed treatment, tillage type, and wheat residue. Disease severity assessed at the end of the growing season was used as the response variable. The models were developed using 431 disease cases (unique combinations of predictors) collected from 2012 to 2014 and these cases were randomly divided into training, validation, and test datasets. Models were evaluated based on the regression of observed against predicted severity values of SNB, sensitivity-specificity ROC analysis, and the Kappa statistic. A strong relationship was observed between late-season severity of SNB and specific pre-planting factors in which latitude, longitude, wheat residue, and cultivar resistance were the most important predictors. The MR model explained 33% of variability in the data, while machine learning models explained 47 to 79% of the total variability. Similarly, the MR model correctly classified 74% of the disease cases, while machine learning models correctly classified 81 to 83% of these cases. Results show that the RF algorithm, which explained 79% of the variability within the data, was the most accurate in predicting the risk of SNB, with an accuracy rate of 93%. The RF algorithm could allow early assessment of the risk of SNB, facilitating sound disease management decisions prior to planting of wheat.

Hazard evaluation of ten organophosphorous insecticides against the midge, Chironomus riparius via QSAR

USGS Publications Warehouse

Landrum, Peter F.; Fisher, Susan W.; Hwang, Haejo; Hickey, James P.

1999-01-01

Toxicities of ten organophosphorus (OP) insecticides were measured against midge larvae (Chironomus riparius) under varying temperature (11, 18, and 25°C) and pH (6, 7, and 8) conditions and with and without sediment. Toxicity usually increased with increasing temperature and was greater in the absence of sediment. No trend was found with varying pH. A series of unidimensional parameters and multidimensional models were used to describe the changes in toxicity. Log Kow was able to explain about 40–60% of the variability in response data for aqueous exposures while molecular volume and aqueous solubility were less predictive. Likewise, the linear solvation energy relationship (LSER) model only explained 40–70% of the response variability, suggesting that factors other than solubility were most important for producing the observed response. Molecular connectivity was the most useful for describing the variability in the response. In the absence of sediment, 1χv and 3κ were best able to describe the variation in response among all compounds at each pH (70–90%). In the presence of sediment, even molecular connectivity could not describe the variability until the partitioning potential to sediment was accounted for by assuming equilibrium partitioning. After correcting for partitioning, the same molecular connectivity terms as in the aqueous exposures described most of the variability, 61–87%, except for the 11°C data where correlations were not significant. Molecular connectivity was a better tool than LSER or the unidimensional variables to explain the steric fitness of OP insecticides which was crucial to the toxicity.

Factors contributing to practice variation in post-stroke rehabilitation.

PubMed Central

Lee, A J; Huber, J H; Stason, W B

1997-01-01

OBJECTIVE: To analyze geographic variability in the utilization and cost of post-stroke medical care using multiple linear regression. DATA SOURCES/STUDY SETTING: A 20 percent random sample of Medicare beneficiaries with an admission to an acute care hospital for stroke during the first six months of 1991, supplemented by data from their Medicare claims and beneficiary records, the Medicare Cost Reports for hospitals and nursing homes, and the Area Resource File. STUDY DESIGN: Weighted least squares regression is used to analyze variations in post-stroke practice patterns across 151 MSAs (Metropolitan Statistical Areas). Average post-stroke costs, utilization rates, and facility lengths of stay are regressed on patient and market characteristics. DATA COLLECTION/EXTRACTION METHODS: For a six-month post-stroke interval, beneficiary-level post-stroke costs and service utilization are averaged by MSA. Variables describing market conditions are then added to these MSA-level records. PRINCIPAL FINDINGS: Patient variables rarely explain more than a third of practice variation, and often they explain substantially less than that. Market variables (with some exception) tend to be relatively less important. Finally, one-half to two-thirds of the practice variation across MSAs is unexplained by the patient and market factors measured in our data. CONCLUSIONS: A substantial portion of inter-MSA variability in utilization and intensity of post-stroke rehabilitation services cannot be explained by differences in patient characteristics. Given the large practice differences observed across MSAs, it seems unlikely that unmeasured patient differences can account for much more of the practice differences. PMID:9180616

Explaining variation in tropical plant community composition: influence of environmental and spatial data quality.

PubMed

Jones, Mirkka M; Tuomisto, Hanna; Borcard, Daniel; Legendre, Pierre; Clark, David B; Olivas, Paulo C

2008-03-01

The degree to which variation in plant community composition (beta-diversity) is predictable from environmental variation, relative to other spatial processes, is of considerable current interest. We addressed this question in Costa Rican rain forest pteridophytes (1,045 plots, 127 species). We also tested the effect of data quality on the results, which has largely been overlooked in earlier studies. To do so, we compared two alternative spatial models [polynomial vs. principal coordinates of neighbour matrices (PCNM)] and ten alternative environmental models (all available environmental variables vs. four subsets, and including their polynomials vs. not). Of the environmental data types, soil chemistry contributed most to explaining pteridophyte community variation, followed in decreasing order of contribution by topography, soil type and forest structure. Environmentally explained variation increased moderately when polynomials of the environmental variables were included. Spatially explained variation increased substantially when the multi-scale PCNM spatial model was used instead of the traditional, broad-scale polynomial spatial model. The best model combination (PCNM spatial model and full environmental model including polynomials) explained 32% of pteridophyte community variation, after correcting for the number of sampling sites and explanatory variables. Overall evidence for environmental control of beta-diversity was strong, and the main floristic gradients detected were correlated with environmental variation at all scales encompassed by the study (c. 100-2,000 m). Depending on model choice, however, total explained variation differed more than fourfold, and the apparent relative importance of space and environment could be reversed. Therefore, we advocate a broader recognition of the impacts that data quality has on analysis results. A general understanding of the relative contributions of spatial and environmental processes to species distributions and beta-diversity requires that methodological artefacts are separated from real ecological differences.

Seasonal and inter-annual variability of the net ecosystem CO2 exchange of a temperate mountain grassland: effects of climate and management.

PubMed

Wohlfahrt, Georg; Hammerle, Albin; Haslwanter, Alois; Bahn, Michael; Tappeiner, Ulrike; Cernusca, Alexander

2008-04-27

The role and relative importance of climate and cutting for the seasonal and inter-annual variability of the net ecosystem CO 2 (NEE) of a temperate mountain grassland was investigated. Eddy covariance CO 2 flux data and associated measurements of the green area index and the major environmental driving forces acquired during 2001-2006 at the study site Neustift (Austria) were analyzed. Driven by three cutting events per year which kept the investigated grassland in a stage of vigorous growth, the seasonal variability of NEE was primarily modulated by gross primary productivity (GPP). The role of environmental parameters in modulating the seasonal variability of NEE was obscured by the strong response of GPP to changes in the amount of green area, as well as the cutting-mediated decoupling of phenological development and the seasonal course of climate drivers. None of the climate and management metrics examined was able to explain the inter-annual variability of annual NEE. This is thought to result from (1) a high covariance between GPP and ecosystem respiration (R eco ) at the annual time scale which results in a comparatively small inter-annual variation of NEE, (2) compensating effects between carbon exchange during and outside the management period, and (3) changes in the biotic response to rather than the climate variables per se. GPP was more important in modulating inter-annual variations in NEE in spring and before the first and second cut, while R eco explained a larger fraction of the inter-annual variability of NEE during the remaining, in particular the post-cut, periods.

Examining the individual and perceived neighborhood associations of leisure-time physical activity in persons with spinal cord injury.

PubMed

Arbour-Nicitopoulos, Kelly P; Martin Ginis, Kathleen A; Wilson, Philip M

2010-05-01

Theory of Planned Behavior (TPB) constructs have been shown to be useful for explaining leisure-time physical activity (LTPA) in persons with spinal cord injury (SCI). However, other factors not captured by the TPB may also be important predictors of LTPA for this population. The purpose of this study is to examine the role of neighborhood perceptions within the context of the TPB for understanding LTPA in persons living with SCI. This is a cross-sectional analysis (n = 574) using structural equation modeling involving measures of the TPB constructs, perceived neighborhood esthetics and sidewalks, and LTPA. TPB constructs explained 57% of the variance in intentions and 12% of the variance in behavior. Inclusion of the neighborhood variables to the model resulted in an additional 1% of the variance explained in intentions, with esthetics exhibiting significant positive relationships with the TPB variables. Integrating perceived neighborhood esthetics into the TPB framework provides additional understanding of LTPA intentions in persons living with SCI.

Identification and detection of simple 3D objects with severely blurred vision.

PubMed

Kallie, Christopher S; Legge, Gordon E; Yu, Deyue

2012-12-05

Detecting and recognizing three-dimensional (3D) objects is an important component of the visual accessibility of public spaces for people with impaired vision. The present study investigated the impact of environmental factors and object properties on the recognition of objects by subjects who viewed physical objects with severely reduced acuity. The experiment was conducted in an indoor testing space. We examined detection and identification of simple convex objects by normally sighted subjects wearing diffusing goggles that reduced effective acuity to 20/900. We used psychophysical methods to examine the effect on performance of important environmental variables: viewing distance (from 10-24 feet, or 3.05-7.32 m) and illumination (overhead fluorescent and artificial window), and object variables: shape (boxes and cylinders), size (heights from 2-6 feet, or 0.61-1.83 m), and color (gray and white). Object identification was significantly affected by distance, color, height, and shape, as well as interactions between illumination, color, and shape. A stepwise regression analysis showed that 64% of the variability in identification could be explained by object contrast values (58%) and object visual angle (6%). When acuity is severely limited, illumination, distance, color, height, and shape influence the identification and detection of simple 3D objects. These effects can be explained in large part by the impact of these variables on object contrast and visual angle. Basic design principles for improving object visibility are discussed.

Attribution of declining Western U.S. Snowpack to human effects

USGS Publications Warehouse

Pierce, D.W.; Barnett, T.P.; Hidalgo, H.G.; Das, T.; Bonfils, Celine; Santer, B.D.; Bala, G.; Dettinger, M.D.; Cayan, D.R.; Mirin, A.; Wood, A.W.; Nozawa, T.

2008-01-01

Observations show snowpack has declined across much of the western United States over the period 1950-99. This reduction has important social and economic implications, as water retained in the snowpack from winter storms forms an important part of the hydrological cycle and water supply in the region. A formal model-based detection and attribution (D-A) study of these reductions is performed. The detection variable is the ratio of 1 April snow water equivalent (SWE) to water-year-to-date precipitation (P), chosen to reduce the effect of P variability on the results. Estimates of natural internal climate variability are obtained from 1600 years of two control simulations performed with fully coupled ocean-atmosphere climate models. Estimates of the SWE/P response to anthropogenic greenhouse gases, ozone, and some aerosols are taken from multiple-member ensembles of perturbation experiments run with two models. The D-A shows the observations and anthropogenically forced models have greater SWE/P reductions than can be explained by natural internal climate variability alone. Model-estimated effects of changes in solar and volcanic forcing likewise do not explain the SWE/P reductions. The mean model estimate is that about half of the SWE/P reductions observed in the west from 1950 to 1999 are the result of climate changes forced by anthropogenic greenhouse gases, ozone, and aerosols. ?? 2008 American Meteorological Society.

State legislative staff influence in health policy making.

PubMed

Weissert, C S; Weissert, W G

2000-12-01

State legislative staff may influence health policy by gathering intelligence, setting the agenda, and shaping the legislative proposals. But they may also be stymied in their roles by such institutional constraints as hiring practices and by turnover in committee leadership in the legislature. The intervening variable of trust between legislators and their support staff is also key to understanding influence and helps explain how staff-legislator relationships play an important role in designing state health policy. This study of legislative fiscal and health policy committee staff uses data from interviews with key actors in five states to model the factors important in explaining variation in the influence of committee staff on health policy.

Techno-Political Space Cooperation: A Longitudinal Analysis of NASA's Bilateral and Multilateral Agreements

NASA Technical Reports Server (NTRS)

Hudiburg, John J.

2004-01-01

NASA's international programs are both numerous and successful, with over two thousand international agreements forming a foundation of U.S. government cooperation that involved over half the United Nation's membership. Previous research, by the author, into these agreements has identified five variables underlying NASA's international cooperation efforts and these variables form a framework for explaining international cooperation behavior on a macro-level. This paper builds upon that research to effectively explain lower-level patterns of cooperation in NASA's experience. Two approaches for analyzing the space agency's history are used: aggregation of all agreements and a cluster (disaggregated) analysis of four key segments. While researchers of NASA's international cooperation often considered individual cases first, and then generalize to macro-level explanations. This study, in contrast, begins by considering all agreements together in order to explain as much as possible at the macro level before proceeding to lower tier explanations. These lower tier assessments are important to understanding regional and political influences on bilateral and multilateral cooperation. In order to accomplish this lower-tier analysis, the 2000 agreements are disaggregated into logical groupings enabling an analysis of important questions and clearer focus on key patterns concerning developing states, such as the role of international institutions or privatization on international cooperation in space technology.

Using the theory of planned behaviour and self-identity to explain chlamydia testing intentions in young people living in deprived areas.

PubMed

Booth, Amy R; Norman, Paul; Harris, Peter R; Goyder, Elizabeth

2014-02-01

The study sought to (1) explain intentions to get tested for chlamydia regularly in a group of young people living in deprived areas using the theory of planned behaviour (TPB); and (2) test whether self-identity explained additional variance in testing intentions. A cross-sectional design was used for this study. Participants (N = 278, 53% male; M = 17.05 years) living in deprived areas of a UK city were recruited from a vocational education setting. Participants completed a self-administered questionnaire, including measures of attitude, injunctive subjective norm, descriptive norm, perceived behavioural control, self-identity, intention and past behaviour in relation to getting tested for chlamydia regularly. The TPB explained 43% of the variance in chlamydia testing intentions with all variables emerging as significant predictors. However, self-identity explained additional variance in intentions (ΔR(2)  = .22) and emerged as the strongest predictor, even when controlling for past behaviour. The study identified the key determinants of intention to get tested for chlamydia regularly in a sample of young people living in areas of increased deprivation: a hard-to-reach, high-risk population. The findings indicate the key variables to target in interventions to promote motivation to get tested for chlamydia regularly in equivalent samples, amongst which self-identity is critical. What is already known on this subject? Young people living in deprived areas have been identified as an at-risk group for chlamydia. Qualitative research has identified several themes in relation to factors affecting the uptake of chlamydia testing, which fit well with the constructs of the Theory of Planned Behaviour (TPB). Identity concerns have also been identified as playing an important part in young people's chlamydia testing decisions. What does this study add? TPB explained 43% of the variance in chlamydia testing intentions and all variables were significant predictors. Self-identity explained additional 22% of the variance in intentions and emerged as the strongest predictor. Indicates key variables to target in interventions to promote regular chlamydia testing in deprived young people. © 2013 The British Psychological Society.

Habitat connectivity and in-stream vegetation control temporal variability of benthic invertebrate communities.

PubMed

Huttunen, K-L; Mykrä, H; Oksanen, J; Astorga, A; Paavola, R; Muotka, T

2017-05-03

One of the key challenges to understanding patterns of β diversity is to disentangle deterministic patterns from stochastic ones. Stochastic processes may mask the influence of deterministic factors on community dynamics, hindering identification of the mechanisms causing variation in community composition. We studied temporal β diversity (among-year dissimilarity) of macroinvertebrate communities in near-pristine boreal streams across 14 years. To assess whether the observed β diversity deviates from that expected by chance, and to identify processes (deterministic vs. stochastic) through which different explanatory factors affect community variability, we used a null model approach. We observed that at the majority of sites temporal β diversity was low indicating high community stability. When stochastic variation was unaccounted for, connectivity was the only variable explaining temporal β diversity, with weakly connected sites exhibiting higher community variability through time. After accounting for stochastic effects, connectivity lost importance, suggesting that it was related to temporal β diversity via random colonization processes. Instead, β diversity was best explained by in-stream vegetation, community variability decreasing with increasing bryophyte cover. These results highlight the potential of stochastic factors to dampen the influence of deterministic processes, affecting our ability to understand and predict changes in biological communities through time.

Influence of estuarine processes on spatiotemporal variation in bioavailable selenium

USGS Publications Warehouse

Stewart, Robin; Luoma, Samuel N.; Elrick, Kent A.; Carter, James L.; van der Wegen, Mick

2013-01-01

Dynamic processes (physical, chemical and biological) challenge our ability to quantify and manage the ecological risk of chemical contaminants in estuarine environments. Selenium (Se) bioavailability (defined by bioaccumulation), stable isotopes and molar carbon-tonitrogen ratios in the benthic clam Potamocorbula amurensis, an important food source for predators, were determined monthly for 17 yr in northern San Francisco Bay. Se concentrations in the clams ranged from a low of 2 to a high of 22 μg g-1 over space and time. Little of that variability was stochastic, however. Statistical analyses and preliminary hydrodynamic modeling showed that a constant mid-estuarine input of Se, which was dispersed up- and down-estuary by tidal currents, explained the general spatial patterns in accumulated Se among stations. Regression of Se bioavailability against river inflows suggested that processes driven by inflows were the primary driver of seasonal variability. River inflow also appeared to explain interannual variability but within the range of Se enrichment established at each station by source inputs. Evaluation of risks from Se contamination in estuaries requires the consideration of spatial and temporal variability on multiple scales and of the processes that drive that variability.

Use Level and Encounters: Important Variables of Perceived Crowding Among Nonspecialized Recreationists.

ERIC Educational Resources Information Center

Hammitt, William E.; And Others

1984-01-01

Use level, visual encounters, crowding expectations, and feelings were examined by regression techniques to explain perceived crowding among innertube floaters. Degree of user specialization and specificity for any given activity and place is offered as an explanation for the discrepancy from previous findings. (Author/DF)

Antecedents of Children's Comprehension of the Purpose of Television Advertising.

ERIC Educational Resources Information Center

Faber, Ronald J.; And Others

A study was conducted to compare the relative importance of several different variables from different theoretical perspectives in explaining how children understood the advertising on commercial television. Sixty-seven first and third grade students were interviewed individually to assess their current stage of logical operations and role taking,…

How Does School Climate Impact Academic Achievement? An Examination of Social Identity Processes

ERIC Educational Resources Information Center

Reynolds, Katherine J.; Lee, Eunro; Turner, Isobel; Bromhead, David; Subasic, Emina

2017-01-01

In explaining academic achievement, school climate and social belonging (connectedness, identification) emerge as important variables. However, both constructs are rarely explored in one model. In the current study, a social psychological framework based on the social identity perspective (Turner, Hogg, Oakes, Reicher, & Wetherell, 1987) is…

Commentary: Mediation Analysis, Causal Process, and Cross-Sectional Data

ERIC Educational Resources Information Center

Shrout, Patrick E.

2011-01-01

Maxwell, Cole, and Mitchell (2011) extended the work of Maxwell and Cole (2007), which raised important questions about whether mediation analyses based on cross-sectional data can shed light on longitudinal mediation process. The latest article considers longitudinal processes that can only be partially explained by an intervening variable, and…

77 FR 42314 - Agency Forms Undergoing Paperwork Reduction Act Review

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-18

... number of data items deemed important to explain variability in success rates across ART programs and... Survey......... 176 1 2/60 Kimberly S. Lane, Deputy Director, Office of Science Integrity, Office of the Associate Director for Science, Office of the Director, Centers for Disease Control and Prevention. [FR Doc...

Attitudes Vs. Cognitions: Explaining Long-Term Watergate Effects.

ERIC Educational Resources Information Center

Becker, Lee B.; Towers, Wayne M.

The political scandals known as Watergate provided an unusual opportunity to study the importance of attitudinal and cognitive variables in media research. In order to assess the impact of Watergate during the months preceding the 1974 Congressional elections, 339 personal interviews were conducted during October with a probability sample of…

On the explaining-away phenomenon in multivariate latent variable models.

PubMed

van Rijn, Peter; Rijmen, Frank

2015-02-01

Many probabilistic models for psychological and educational measurements contain latent variables. Well-known examples are factor analysis, item response theory, and latent class model families. We discuss what is referred to as the 'explaining-away' phenomenon in the context of such latent variable models. This phenomenon can occur when multiple latent variables are related to the same observed variable, and can elicit seemingly counterintuitive conditional dependencies between latent variables given observed variables. We illustrate the implications of explaining away for a number of well-known latent variable models by using both theoretical and real data examples. © 2014 The British Psychological Society.

Can we quantify the variability of soil moisture across scales using Electromagnetic Induction ?

NASA Astrophysics Data System (ADS)

Robinet, Jérémy; von Hebel, Christian; van der Kruk, Jan; Govers, Gerard; Vanderborght, Jan

2017-04-01

Soil moisture is a key variable in many natural processes. Therefore, technological and methodological advancements are of primary importance to provide accurate measurements of spatial and temporal variability of soil moisture. In that context, ElectroMagnetic Induction (EMI) instruments are often cited as a hydrogeophysical method with a large potential, through the measurement of the soil apparent electrical conductivity (ECa). To our knowledge, no studies have evaluated the potential of EMI to characterize variability of soil moisture on both agricultural and forested land covers in a (sub-) tropical environment. These differences in land use could be critical as differences in temperature, transpiration and root water uptake can have significant effect, notably on the electrical conductivity of the pore water. In this study, we used an EMI instrument to carry out a first assessment of the impact of deforestation and agriculture on soil moisture in a subtropical region in the south of Brazil. We selected slopes of different topographies (gentle vs. steep) and contrasting land uses (natural forest vs. agriculture) within two nearby catchments. At selected locations on the slopes, we measured simultaneously ECa using EMI and a depth-weighted average of the soil moisture using TDR probes installed within soil pits. We found that the temporal variability of the soil moisture could not be measured accurately with EMI, probably because of important temporal variations of the pore water electrical conductivity and the relatively small temporal variations in soil moisture content. However, we found that its spatial variability could be effectively quantified using a non-linear relationship, for both intra- and inter-slopes variations. Within slopes, the ECa could explained between 67 and 90% of the variability of the soil moisture, while a single non-linear model for all the slopes could explain 55% of the soil moisture variability. We eventually showed that combining a specific relationship for the most degraded slope (steep slope under agriculture) and a single relationship for all the other slopes, both non-linear relations, yielded the best results with an overall explained variance of 90%. We applied the latter model to measurements of the ECa along transects at the different slopes, which allowed us to highlight the strong control of topography on the soil moisture content. We also observed a significant impact of the land use with higher moisture content on the agricultural slopes, probably due to a reduced evapotranspiration.

Phylogenetic turnover along local environmental gradients in tropical forest communities.

PubMed

Baldeck, C A; Kembel, S W; Harms, K E; Yavitt, J B; John, R; Turner, B L; Madawala, S; Gunatilleke, N; Gunatilleke, S; Bunyavejchewin, S; Kiratiprayoon, S; Yaacob, A; Supardi, M N N; Valencia, R; Navarrete, H; Davies, S J; Chuyong, G B; Kenfack, D; Thomas, D W; Dalling, J W

2016-10-01

While the importance of local-scale habitat niches in shaping tree species turnover along environmental gradients in tropical forests is well appreciated, relatively little is known about the influence of phylogenetic signal in species' habitat niches in shaping local community structure. We used detailed maps of the soil resource and topographic variation within eight 24-50 ha tropical forest plots combined with species phylogenies created from the APG III phylogeny to examine how phylogenetic beta diversity (indicating the degree of phylogenetic similarity of two communities) was related to environmental gradients within tropical tree communities. Using distance-based redundancy analysis we found that phylogenetic beta diversity, expressed as either nearest neighbor distance or mean pairwise distance, was significantly related to both soil and topographic variation in all study sites. In general, more phylogenetic beta diversity within a forest plot was explained by environmental variables this was expressed as nearest neighbor distance versus mean pairwise distance (3.0-10.3 % and 0.4-8.8 % of variation explained among plots, respectively), and more variation was explained by soil resource variables than topographic variables using either phylogenetic beta diversity metric. We also found that patterns of phylogenetic beta diversity expressed as nearest neighbor distance were consistent with previously observed patterns of niche similarity among congeneric species pairs in these plots. These results indicate the importance of phylogenetic signal in local habitat niches in shaping the phylogenetic structure of tropical tree communities, especially at the level of close phylogenetic neighbors, where similarity in habitat niches is most strongly preserved.

Management practices associated with conception rate and service rate of lactating Holstein cows in large, commercial dairy herds.

PubMed

Schefers, J M; Weigel, K A; Rawson, C L; Zwald, N R; Cook, N B

2010-04-01

Data from lactating Holstein cows in herds that participate in a commercial progeny testing program were analyzed to explain management factors associated with herd-average conception and service rates on large commercial dairies. On-farm herd management software was used as the source of data related to production, reproduction, culling, and milk quality for 108 herds. Also, a survey regarding management, facilities, nutrition, and labor was completed on 86 farms. A total of 41 explanatory variables related to management factors and conditions that could affect conception and service rate were considered in this study. Models explaining conception and service rates were developed using a machine learning algorithm for constructing model trees. The most important explanatory variables associated with conception rate were the percentage of repeated inseminations between 4 and 17 d post-artificial insemination, stocking density in the breeding pen, length of the voluntary waiting period, days at pregnancy examination, and somatic cell score. The most important explanatory variables associated with service rate were the number of lactating cows per breeding technician, use of a resynchronization program, utilization of soakers in the holding area during the summer, and bunk space per cow in the breeding pen. The aforementioned models explained 35% and 40% of the observed variation in conception rate and service rate, respectively, and underline the association of herd-level management factors not strictly related to reproduction with herd reproductive performance. Copyright (c) 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Human influence on California fire regimes.

PubMed

Syphard, Alexandra D; Radeloff, Volker C; Keeley, Jon E; Hawbaker, Todd J; Clayton, Murray K; Stewart, Susan I; Hammer, Roger B

2007-07-01

Periodic wildfire maintains the integrity and species composition of many ecosystems, including the mediterranean-climate shrublands of California. However, human activities alter natural fire regimes, which can lead to cascading ecological effects. Increased human ignitions at the wildland-urban interface (WUI) have recently gained attention, but fire activity and risk are typically estimated using only biophysical variables. Our goal was to determine how humans influence fire in California and to examine whether this influence was linear, by relating contemporary (2000) and historic (1960-2000) fire data to both human and biophysical variables. Data for the human variables included fine-resolution maps of the WUI produced using housing density and land cover data. Interface WUI, where development abuts wildland vegetation, was differentiated from intermix WUI, where development intermingles with wildland vegetation. Additional explanatory variables included distance to WUI, population density, road density, vegetation type, and ecoregion. All data were summarized at the county level and analyzed using bivariate and multiple regression methods. We found highly significant relationships between humans and fire on the contemporary landscape, and our models explained fire frequency (R2 = 0.72) better than area burned (R2 = 0.50). Population density, intermix WUI, and distance to WUI explained the most variability in fire frequency, suggesting that the spatial pattern of development may be an important variable to consider when estimating fire risk. We found nonlinear effects such that fire frequency and area burned were highest at intermediate levels of human activity, but declined beyond certain thresholds. Human activities also explained change in fire frequency and area burned (1960-2000), but our models had greater explanatory power during the years 1960-1980, when there was more dramatic change in fire frequency. Understanding wildfire as a function of the spatial arrangement of ignitions and fuels on the landscape, in addition to nonlinear relationships, will be important to fire managers and conservation planners because fire risk may be related to specific levels of housing density that can be accounted for in land use planning. With more fires occurring in close proximity to human infrastructure, there may also be devastating ecological impacts if development continues to grow farther into wildland vegetation.

Human influence on California fire regimes

USGS Publications Warehouse

Syphard, A.D.; Radeloff, V.C.; Keeley, J.E.; Hawbaker, T.J.; Clayton, M.K.; Stewart, S.I.; Hammer, R.B.

2007-01-01

Periodic wildfire maintains the integrity and species composition of many ecosystems, including the mediterranean-climate shrublands of California. However, human activities alter natural fire regimes, which can lead to cascading ecological effects. Increased human ignitions at the wildland-urban interface (WUI) have recently gained attention, but fire activity and risk are typically estimated using only biophysical variables. Our goal was to determine how humans influence fire in California and to examine whether this influence was linear, by relating contemporary (2000) and historic (1960-2000) fire data to both human and biophysical variables. Data for the human variables included fine-resolution maps of the WUI produced using housing density and land cover data. Interface WUI, where development abuts wildland vegetation, was differentiated from intermix WUI, where development intermingles with wildland vegetation. Additional explanatory variables included distance to WUI, population density, road density, vegetation type, and ecoregion. All data were summarized at the county level and analyzed using bivariate and multiple regression methods. We found highly significant relationships between humans and fire on the contemporary landscape, and our models explained fire frequency (R2 = 0.72) better than area burned (R2 = 0.50). Population density, intermix WUI, and distance to WUI explained the most variability in fire frequency, suggesting that the spatial pattern of development may be an important variable to consider when estimating fire risk. We found nonlinear effects such that fire frequency and area burned were highest at intermediate levels of human activity, but declined beyond certain thresholds. Human activities also explained change in fire frequency and area burned (1960-2000), but our models had greater explanatory power during the years 1960-1980, when there was more dramatic change in fire frequency. Understanding wildfire as a function of the spatial arrangement of ignitions and fuels on the landscape, in addition to nonlinear relationships, will be important to fire managers and conservation planners because fire risk may be related to specific levels of housing density that can be accounted for in land use planning. With more fires occurring in close proximity to human infrastructure, there may also be devastating ecological impacts if development continues to grow farther into wildland vegetation. ?? 2007 by the Ecological Society of America.

Species interactions may help explain the erratic periodicity of whooping cough dynamics.

PubMed

Bhattacharyya, Samit; Ferrari, Matthew J; Bjørnstad, Ottar N

2017-12-14

Incidence of whooping cough exhibits variable dynamics across time and space. The periodicity of this disease varies from annual to five years in different geographic regions in both developing and developed countries. Many hypotheses have been put forward to explain this variability such as nonlinearity and seasonality, stochasticity, variable recruitment of susceptible individuals via birth, immunization, and immune boosting. We propose an alternative hypothesis to describe the variability in periodicity - the intricate dynamical variability of whooping cough may arise from interactions between its dominant etiological agents of Bordetella pertussis and Bordetella parapertussis. We develop a two-species age-structured model, where two pathogens are allowed to interact by age-dependent convalescence of individuals with severe illness from infections. With moderate strength of interactions, the model exhibits multi-annual coexisting attractors that depend on the R 0 of the two pathogens. We also examine how perturbation from case importation and noise in transmission may push the system from one dynamical regime to another. The coexistence of multi-annual cycles and the behavior of switching between attractors suggest that variable dynamics of whopping cough could be an emergent property of its multi-agent etiology. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Methodological development for selection of significant predictors explaining fatal road accidents.

PubMed

Dadashova, Bahar; Arenas-Ramírez, Blanca; Mira-McWilliams, José; Aparicio-Izquierdo, Francisco

2016-05-01

Identification of the most relevant factors for explaining road accident occurrence is an important issue in road safety research, particularly for future decision-making processes in transport policy. However model selection for this particular purpose is still an ongoing research. In this paper we propose a methodological development for model selection which addresses both explanatory variable and adequate model selection issues. A variable selection procedure, TIM (two-input model) method is carried out by combining neural network design and statistical approaches. The error structure of the fitted model is assumed to follow an autoregressive process. All models are estimated using Markov Chain Monte Carlo method where the model parameters are assigned non-informative prior distributions. The final model is built using the results of the variable selection. For the application of the proposed methodology the number of fatal accidents in Spain during 2000-2011 was used. This indicator has experienced the maximum reduction internationally during the indicated years thus making it an interesting time series from a road safety policy perspective. Hence the identification of the variables that have affected this reduction is of particular interest for future decision making. The results of the variable selection process show that the selected variables are main subjects of road safety policy measures. Published by Elsevier Ltd.

Relation of agronomic and multispectral reflectance characteristics of spring wheat canopies

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Ahlrichs, J. S.

1982-01-01

The relationships between crop canopy variables such as leaf area index (LAI) and their multispectral reflectance properties were investigated along with the potential for estimating canopy variables from remotely sensed reflectance measurements. Reflectance spectra over the 0.4 to 2.5 micron wavelength range were acquired during each of the major development stages of spring wheat canopies at Williston, North Dakota, during three seasons. Treatments included planting date, N fertilization, cultivar, and soil moisture. Agronomic measurements included development stage, biomass, LAI, and percent soil cover. High correlations were found between reflectance and percent cover, LAI, and biomass. A near infrared wavelength band, 0.76 to 0.90 microns, was most important in explaining variation in LAI and percent cover, while a middle infrared band, 2.08 to 2.35 microns, explained the most variation in biomass and plant water content. Transformations, including the near infrared/red reflectance ratio and greenness index, were also highly correlated to canopy variables. The relationship of canopy variables to reflectance decreased as the crop began to ripen. the canopy variables could be accurately predicted using measurements from three to five wavelength bands. The wavelength bands proposed for the thematic mapper sensor were more strongly related to the canopy variables than the LANDSAT MSS bands.

On the implications of the period distributions of subclasses of cataclysmic variables

NASA Astrophysics Data System (ADS)

Verbunt, Frank

1997-09-01

The period distributions of dwarf novae and nova-like variables above the period gap are different if the VY Scl systems are classed with the nova-like variables, but the same when the VY Scl phenomenon is classed with the dwarf nova outbursts. For the remaining nova-like variables, the period gap is no longer significant. Classification of the VY Scl phenomenon with dwarf novae suggests that dwarf nova outbursts are caused by variation in mass transfer from the donor. Absence of the period gap obviates the need for models explaining it, and invalidates one piece of evidence for the importance of magnetic braking for the evolution of cataclysmic variables and of low-mass binaries in general.

Long-term trends of bloater (Coregonus hoyi) recruitment in Lake Michigan: evidence for the effect of sex ratio

USGS Publications Warehouse

Bunnell, David B.; Madenjian, Charles P.; Croley, Thomas E.

2006-01-01

Long-term population trends are generally explained by factors extrinsic (e.g., climate, predation) rather than intrinsic (e.g., genetics, maternal effects) to the population. We sought to understand the long-term population dynamics of an important native Lake Michigan prey fish, the bloaterCoregonus hoyi. Over a 38-year time series, three 10- to 15-year phases occurred (poor, excellent, and then poor recruitment) without high interannual variability within a particular phase. We used dynamic linear models to determine whether extrinsic (winter and spring temperature, alewife predator densities) or intrinsic factors (population egg production, adult condition, adult sex ratio) explained variation in recruitment. Models that included population egg production, sex ratio, winter and spring temperature, and adult bloater condition explained the most variation. Of these variables, sex ratio, which ranged from 47% to 97% female across the time series, consistently had the greatest effect: recruitment declined with female predominance. Including biomass of adult alewife predators in the models did not explain additional variation. Overall our results indicated that bloater recruitment is linked to its sex ratio, but understanding the underlying mechanisms will require additional efforts.

Race-ethnicity is a strong correlate of circulating fat-soluble nutrient concentrations in a representative sample of the U.S. population.

PubMed

Schleicher, Rosemary L; Sternberg, Maya R; Pfeiffer, Christine M

2013-06-01

Sociodemographic and lifestyle factors exert important influences on nutritional status; however, information on their association with biomarkers of fat-soluble nutrients is limited, particularly in a representative sample of adults. Serum or plasma concentrations of vitamin A, vitamin E, carotenes, xanthophylls, 25-hydroxyvitamin D [25(OH)D], SFAs, MUFAs, PUFAs, and total fatty acids (tFAs) were measured in adults (aged ≥ 20 y) during all or part of NHANES 2003-2006. Simple and multiple linear regression models were used to assess 5 sociodemographic variables (age, sex, race-ethnicity, education, and income) and 5 lifestyle behaviors (smoking, alcohol consumption, BMI, physical activity, and supplement use) and their relation to biomarker concentrations. Adjustment for total serum cholesterol and lipid-altering drug use was added to the full regression model. Adjustment for latitude and season was added to the full model for 25(OH)D. Based on simple linear regression, race-ethnicity, BMI, and supplement use were significantly related to all fat-soluble biomarkers. Sociodemographic variables as a group explained 5-17% of biomarker variability, whereas together, sociodemographic and lifestyle variables explained 22-23% [25(OH)D, vitamin E, xanthophylls], 17% (vitamin A), 15% (MUFAs), 10-11% (SFAs, carotenes, tFAs), and 6% (PUFAs) of biomarker variability. Although lipid adjustment explained additional variability for all biomarkers except for 25(OH)D, it appeared to be largely independent of sociodemographic and lifestyle variables. After adjusting for sociodemographic, lifestyle, and lipid-related variables, major differences in biomarkers were associated with race-ethnicity (from -44 to 57%), smoking (up to -25%), supplement use (up to 21%), and BMI (up to -15%). Latitude and season attenuated some race-ethnicity differences. Of the sociodemographic and lifestyle variables examined, with or without lipid adjustment, most fat-soluble nutrient biomarkers were significantly associated with race-ethnicity.

Continental water recycling and H2(18)-O concentrations

NASA Technical Reports Server (NTRS)

Koster, Randal D.; De Valpine, D. Perry; Jouzel, Jean

1993-01-01

Using a General Circulation Model (GCM) fitted with tracer diagnostics, we examine how continental moisture recycling affects the stable water isotope content of precipitation, focusing on its contribution to the 'noise' in the well-established relationship between temperature and delta O-18. On a global basis, for temperatures between -30 and 15 C, continental recycling explains more than a third of the variability in annual delta O-18 that is not explained by temperature. Recycling appears almost as important as temperature in defining delta O-18 distributions during northern hemisphere summer.

Spatial Distribution of Dorylaimid and Mononchid Nematodes from the Southeast Iberian Peninsula: Environmental Characterization of Chorotypes

PubMed Central

Liébanas, G.; Guerrero, P.; Martín-García, J.-M.; Peña-Santiago, R.

2004-01-01

The aim of this study was to determine the incidence of 18 environmental variables in the spatial distribution of 30 chorotypes (species groups with significantly similar distribution patterns) of dorylaimid and mononchid nematodes by means of logistic regression in a natural area in the southeastern Iberian Peninsula. Six variables (elevation, color chroma, clay content, nitrogen content, CaCO₃, and plant community associated) were the most important environmental factors that helped explain the distribution of chorotypes. The distribution of most chorotypes was characterized by some (one to three) environmental variables; only two chorotypes were characterized by five or more variables, and four have not been characterized. PMID:19262795

Multilevel analyses of school and children's characteristics associated with physical activity.

PubMed

Gomes, Thayse Natacha; dos Santos, Fernanda K; Zhu, Weimo; Eisenmann, Joey; Maia, José A R

2014-10-01

Children spend most of their awake time at school, and it is important to identify individual and school-level correlates of their physical activity (PA) levels. This study aimed to identify the between-school variability in Portuguese children PA and to investigate student and school PA correlates using multilevel modeling. The sample included 1075 Portuguese children of both sexes, aged 6-10 years, from 24 schools. Height and weight were measured and body mass index (BMI) was estimated. Physical activity was estimated using the Godin and Shephard questionnaire (total PA score was used); cardiorespiratory fitness was estimated with the 1-mile run/walk test. A structured inventory was used to access information about the school environment. A multilevel analysis (level-1: student-level; level-2: school-level) was used. Student-level variables (age, sex, 1-mile run/walk test) explained 7% of the 64% variance fraction of the individual-level PA; however, school context explained approximately 36% of the total PA variance. Variables included in the model (school size, school setting, playground area, frequency and duration of physical education class, and qualification of physical education teacher) are responsible for 80% of the context variance. School environment is an important correlate of PA among children, enhancing children's opportunities for being active and healthy. © 2014, American School Health Association.

Cataclysmic Variable Stars

NASA Astrophysics Data System (ADS)

Hellier, Coel

2001-01-01

Cataclysmic variable stars are the most variable stars in the night sky, fluctuating in brightness continually on timescales from seconds to hours to weeks to years. The changes can be recorded using amateur telescopes, yet are also the subject of intensive study by professional astronomers. That study has led to an understanding of cataclysmic variables as binary stars, orbiting so closely that material transfers from one star to the other. The resulting process of accretion is one of the most important in astrophysics. This book presents the first account of cataclysmic variables at an introductory level. Assuming no previous knowledge of the field, it explains the basic principles underlying the variability, while providing an extensive compilation of cataclysmic variable light curves. Aimed at amateur astronomers, undergraduates, and researchers, the main text is accessible to those with no mathematical background, while supplementary boxes present technical details and equations.

Kinematic measures of Arm-trunk movements during unilateral and bilateral reaching predict clinically important change in perceived arm use in daily activities after intensive stroke rehabilitation.

PubMed

Chen, Hao-ling; Lin, Keh-chung; Liing, Rong-jiuan; Wu, Ching-yi; Chen, Chia-ling

2015-09-21

Kinematic analysis has been used to objectively evaluate movement patterns, quality, and strategies during reaching tasks. However, no study has investigated whether kinematic variables during unilateral and bilateral reaching tasks predict a patient's perceived arm use during activities of daily living (ADL) after an intensive intervention. Therefore, this study investigated whether kinematic measures during unilateral and bilateral reaching tasks before an intervention can predict clinically meaningful improvement in perceived arm use during ADL after intensive poststroke rehabilitation. The study was a secondary analysis of 120 subjects with chronic stroke who received 90-120 min of intensive intervention every weekday for 3-4 weeks. Reaching kinematics during unilateral and bilateral tasks and the Motor Activity Log (MAL) were evaluated before and after the intervention. Kinematic variables explained 22 and 11 % of the variance in actual amount of use (AOU) and quality of movement (QOM), respectively, of MAL improvement during unilateral reaching tasks. Kinematic variables also explained 21 and 31 % of the variance in MAL-AOU and MAL-QOM, respectively, during bilateral reaching tasks. Selected kinematic variables, including endpoint variables, trunk involvement, and joint recruitment and interjoint coordination, were significant predictors for improvement in perceived arm use during ADL (P < 0.05). Arm-trunk kinematics may be used to predict clinically meaningful improvement in perceived arm use during ADL after intensive rehabilitation. Involvement of interjoint coordination and trunk control variables as predictors in bilateral reaching models indicates that a high level of motor control (i.e., multijoint coordination) and trunk stability may be important in obtaining treatment gains in arm use, especially for bilateral daily activities, in intensive rehabilitation after stroke.

Development of a microscale land use regression model for predicting NO2 concentrations at a heavy trafficked suburban area in Auckland, NZ.

PubMed

Weissert, L F; Salmond, J A; Miskell, G; Alavi-Shoshtari, M; Williams, D E

2018-04-01

Land use regression (LUR) analysis has become a key method to explain air pollutant concentrations at unmeasured sites at city or country scales, but little is known about the applicability of LUR at microscales. We present a microscale LUR model developed for a heavy trafficked section of road in Auckland, New Zealand. We also test the within-city transferability of LUR models developed at different spatial scales (local scale and city scale). Nitrogen dioxide (NO 2 ) was measured during summer at 40 sites and a LUR model was developed based on standard criteria. The results showed that LUR models are able to capture the microscale variability with the model explaining 66% of the variability in NO 2 concentrations. Predictor variables identified at this scale were street width, distance to major road, presence of awnings and number of bus stops, with the latter three also being important determinants at the local scale. This highlights the importance of street and building configurations for individual exposure at the street level. However, within-city transferability was limited with the number of bus stops being the only significant predictor variable at all spatial scales and locations tested, indicating the strong influence of diesel emissions related to bus traffic. These findings show that air quality monitoring is necessary at a high spatial density within cities in capturing small-scale variability in NO 2 concentrations at the street level and assessing individual exposure to traffic related air pollutants. Copyright © 2017. Published by Elsevier B.V.

Effects of land use, climate, topography and soil properties on regional soil organic carbon and total nitrogen in the upstream watershed of Miyun Reservoir, North China.

PubMed

Wang, Shufang; Wang, Xiaoke; Ouyang, Zhiyun

2012-01-01

Soil organic carbon (SOC) and total nitrogen (TN) contents as well as their relationships with site characteristics are of profound importance in assessing current regional, continental and global soil C and N stocks and potentials for C sequestration and N conservation to offset anthropogenic emissions of greenhouse gases. This study investigated contents and distribution of SOC and TN under different land uses, and the quantitative relationships between SOC or TN and site characteristics in the Upstream Watershed of Miyun Reservoir, North China. Overall, both SOC and TN contents in natural secondary forests and grasslands were much higher than in plantations and croplands. Land use alone explained 37.2% and 38.4% of variations in SOC and TN contents, respectively. The optimal models for SOC and TN, achieved by multiple regression analysis combined with principal component analysis (PCA) to remove the multicollinearity among site variables, showed that elevation, slope, soil clay and water contents were the most significant factors controlling SOC and TN contents, jointly explaining 70.3% of SOC and 67.1% of TN contents variability. Only does additional 1.9% and 3% increase in the interpretations of SOC and TN contents variability respectively when land use was added to regressions, probably due to environment factors determine land use. Therefore, environmental variables were more important for SOC and TN variability than land use in the study area, and should be taken into consideration in properly evaluating effects of future land use changes on SOC and TN on a regional scale.

A regional modeling framework of phosphorus sources and transport in streams of the southeastern United States

USGS Publications Warehouse

Garcia, Ana Maria.; Hoos, Anne B.; Terziotti, Silvia

2011-01-01

We applied the SPARROW model to estimate phosphorus transport from catchments to stream reaches and subsequent delivery to major receiving water bodies in the Southeastern United States (U.S.). We show that six source variables and five land-to-water transport variables are significant (p < 0.05) in explaining 67% of the variability in long-term log-transformed mean annual phosphorus yields. Three land-to-water variables are a subset of landscape characteristics that have been used as transport factors in phosphorus indices developed by state agencies and are identified through experimental research as influencing land-to-water phosphorus transport at field and plot scales. Two land-to-water variables – soil organic matter and soil pH – are associated with phosphorus sorption, a significant finding given that most state-developed phosphorus indices do not explicitly contain variables for sorption processes. Our findings for Southeastern U.S. streams emphasize the importance of accounting for phosphorus present in the soil profile to predict attainable instream water quality. Regional estimates of phosphorus associated with soil-parent rock were highly significant in explaining instream phosphorus yield variability. Model predictions associate 31% of phosphorus delivered to receiving water bodies to geology and the highest total phosphorus yields in the Southeast were catchments with already high background levels that have been impacted by human activity.

Linking crop yield anomalies to large-scale atmospheric circulation in Europe.

PubMed

Ceglar, Andrej; Turco, Marco; Toreti, Andrea; Doblas-Reyes, Francisco J

2017-06-15

Understanding the effects of climate variability and extremes on crop growth and development represents a necessary step to assess the resilience of agricultural systems to changing climate conditions. This study investigates the links between the large-scale atmospheric circulation and crop yields in Europe, providing the basis to develop seasonal crop yield forecasting and thus enabling a more effective and dynamic adaptation to climate variability and change. Four dominant modes of large-scale atmospheric variability have been used: North Atlantic Oscillation, Eastern Atlantic, Scandinavian and Eastern Atlantic-Western Russia patterns. Large-scale atmospheric circulation explains on average 43% of inter-annual winter wheat yield variability, ranging between 20% and 70% across countries. As for grain maize, the average explained variability is 38%, ranging between 20% and 58%. Spatially, the skill of the developed statistical models strongly depends on the large-scale atmospheric variability impact on weather at the regional level, especially during the most sensitive growth stages of flowering and grain filling. Our results also suggest that preceding atmospheric conditions might provide an important source of predictability especially for maize yields in south-eastern Europe. Since the seasonal predictability of large-scale atmospheric patterns is generally higher than the one of surface weather variables (e.g. precipitation) in Europe, seasonal crop yield prediction could benefit from the integration of derived statistical models exploiting the dynamical seasonal forecast of large-scale atmospheric circulation.

Characteristics explaining performance in downhill mountain biking.

PubMed

Chidley, Joel B; MacGregor, Alexandra L; Martin, Caoimhe; Arthur, Calum A; Macdonald, Jamie H

2015-03-01

To identify physiological, psychological, and skill characteristics that explain performance in downhill (DH) mountain-bike racing. Four studies were used to (1) identify factors potentially contributing to DH performance (using an expert focus group), (2) develop and validate a measure of rider skill (using video analysis and expert judge evaluation), (3) evaluate whether physiological, psychological, and skill variables contribute to performance at a DH competition, and (4) test the specific contribution of aerobic capacity to DH performance. STUDY 1 identified aerobic capacity, handgrip endurance, anaerobic power, rider skill, and self-confidence as potentially important for DH. In study 2 the rider-skill measure displayed good interrater reliability. Study 3 found that rider skill and handgrip endurance were significantly related to DH ride time (β=-0.76 and -0.14, respectively; R2=.73), with exploratory analyses suggesting that DH ride time may also be influenced by self-confidence and aerobic capacity. Study 4 confirmed aerobic capacity as an important variable influencing DH performance (for a DH ride, mean oxygen uptake was 49±5 mL·kg(-1)·min(-1), and 90% of the ride was completed above the 1st ventilatory threshold). In order of importance, rider skill, handgrip endurance, self-confidence, and aerobic capacity were identified as variables influencing DH performance. Practically, this study provides a novel assessment of rider skill that could be used by coaches to monitor training and identify talent. Novel intervention targets to enhance DH performance were also identified, including self-confidence and aerobic capacity.

Perceived exercise self-efficacy as a predictor of exercise behavior in individuals aging with spinal cord injury.

PubMed

Kroll, Thilo; Kratz, Anna; Kehn, Matthew; Jensen, Mark P; Groah, Suzanne; Ljungberg, Inger H; Molton, Ivan R; Bombardier, Charles

2012-08-01

The purpose of this study was to test the hypothesized association between exercise self-efficacy and exercise behavior, controlling for demographic variables and clinical characteristics, in a sample of individuals with spinal cord injuries. A cross-sectional national survey of 612 community-dwelling adults with spinal cord injury in the United States ranging from 18 to 89 yrs of age was conducted. Sample consisted of 63.1% men with a mean (SD) duration of 15.8 (12.79) yrs postinjury; 86.3% reported using a wheelchair. Self-efficacy was the only independent variable that consistently predicted all four exercise outcomes. Self-efficacy beliefs were significantly related to frequency and intensity of resistance training (R(2) change = 0.08 and 0.03, respectively; P < 0.01 for all) and aerobic training (R(2) change = 0.07 and 0.05, respectively; P < 0.01 for all), thus explaining between 3% and 8% of the variance. Hierarchical linear regression analysis revealed that controlling for other demographic and physical capability variables, the age-related variables made statistically significant contributions and explained between 1% and 3% of the variance in aerobic exercise frequency and intensity (R(2) change = 0.01 and 0.03, respectively; P < 0.01 for all). Clinical functional characteristics but not demographic variables explained participation in resistance exercise. Self-efficacy beliefs play an important role as predictors of exercise. Variations in exercise intensity along the age continuum have implications for exercise prescription and composition. Future research should replicate findings with objective activity measures.

The effects of landscape position on plant species density: Evidence of past environmental effects in a coastal wetland

USGS Publications Warehouse

Grace, J.B.; Guntenspergen, G.R.

1999-01-01

Here we propose that an important cause of variation in species density may be prior environmental conditions that continue to influence current patterns. In this paper we investigated the degree to which species density varies with location within the landscape, independent of contemporaneous environmental conditions. The area studied was a coastal marsh landscape subject to periodic storm events. To evaluate the impact of historical effects, it was assumed that the landscape position of a plot relative to the river's mouth ('distance from sea') and to the edge of a stream channel ('distance from shore') would correlate with the impact of prior storm events, an assumption supported by previous studies. To evaluate the importance of spatial location on species density, data were collected from five sites located at increasing distances from the river's mouth along the Middle Pearl River in Louisiana. At each site, plots were established systematically along transects perpendicular to the shoreline. For each of the 175 Plots, we measured elevation, soil salinity, percent of plot recently disturbed, percent of sunlight captured by the plant canopy (as a measure of plant abundance), and plant species density. Structural equation analysis ascertained the degree to which landscape position variables explained variation in species density that could not be explained by current environmental indicators. Without considering landscape variables, 54% of the variation in species density could be explained by the effects of salinity, flooding, and plant abundance. When landscape variables were included, distance from shore was unimportant but distance from sea explained an additional 12% of the variance in species density (R2 of final model = 66%). Based on these results it appears that at least some of the otherwise unexplained variation in species density can be attributed to landscape position, and presumably previous storm events. We suggest that future studies may gain additional insight into the factors controlling current patterns of species density by examining the effects of position within the landscape.

Emotional state and psychological flexibility in breast cancer survivors.

PubMed

González-Fernández, Sonia; Fernández-Rodríguez, Concepción; Mota-Alonso, María Jesús; García-Teijido, Paula; Pedrosa, Ignacio; Pérez-Álvarez, Marino

2017-10-01

This study analyses the premise that less time spent carrying out valuable activities and inflexible avoidance of thoughts, feelings and memories related to the oncological process may play an important role in the emotional problems of cancer survivors. Emotional state was evaluated, as was quality of life and psychological flexibility in a sample of 122 breast cancer survivors (M age  = 52.40; SD age  = 7.26). The analysis was carried out using a cross-sectional predictive study. Approximately half of those in the sample suffered from clinically significant emotional distress. The predictor variables selected explained a high percentage of the variability in emotional problems and quality of life (51.10-77.10%). Avoidance explained a high percentage of the variance in anxiety, depression and general distress. A lower degree of participation in valuable activities contributed, more specifically, to explaining variability in depression. The quantity and availability of environmental reinforcement was closely related to quality of life. A decisive contribution towards promoting emotional well-being and quality of life can be made by nursing action aimed at diminishing those avoidance strategies related to the oncological experience which may distance patients from daily activities which are gratifying and congruent with their values. Copyright © 2017 Elsevier Ltd. All rights reserved.

Substantive Nonadditivity in Rural Sociological Research: A Note on Induced Collinearity and Measurement and Testing of Effects.

ERIC Educational Resources Information Center

Miller, Michael K.; Farmer, Frank L.

Theories employed to explain regularities in social behavior often contain explicit or implicit reference to the presence of nonlinear and/or nonadditive (i.e., multiplicative) relationships among germane variables. While such nonadditive features are theoretically important, the inclusion of quadratic or multiplicative terms in structural…

Faculty Members' Intentions to Leave: A National Study on Their Worklife and Satisfaction

ERIC Educational Resources Information Center

Rosser, Vicki J.

2004-01-01

Despite the importance of faculty retention, there is little understanding of how demographic variables, professional and institutional worklife issues, and satisfaction interact to explain faculty intentions to leave at a national level. Using the National Study of Postsecondary Faculty (NSOPF:1999) database, this study proposes (a) to extend our…

Improving Primary School Prospective Teachers' Understanding of the Mathematics Modeling Process

ERIC Educational Resources Information Center

Bal, Aytgen Pinar; Doganay, Ahmet

2014-01-01

The development of mathematical thinking plays an important role on the solution of problems faced in daily life. Determining the relevant variables and necessary procedural steps in order to solve problems constitutes the essence of mathematical thinking. Mathematical modeling provides an opportunity for explaining thoughts in real life by making…

Effects of transgene-encoded high-molecular weight glutenin proteins in wheat flour blends and sponge and dough baking

USDA-ARS?s Scientific Manuscript database

HMW glutenin subunits are the most important determinants of wheat (Triticum aestivum L.) bread-making quality, and subunit composition explains a large percentage of the variability observed between genotypes. Experiments were designed to elevate expression of a key native HMW glutenin subunit (1D...

Portrayal of Religion in Prime-Time Television Drama.

ERIC Educational Resources Information Center

Virts, Paul H.; Keeler, John D.

In order to stimulate scholars to investigate systematically and fully the religious dimension of dramatic television content, the first part of this paper develops a basic framework for such study. After establishing the importance of this kind of research, it defines and explains the four basic variables that would have to be examined: general…

Variability in Stepping Direction Explains the Veering Behavior of Blind Walkers

ERIC Educational Resources Information Center

Kallie, Christopher S.; Schrater, Paul R.; Legge, Gordon E.

2007-01-01

Walking without vision results in veering, an inability to maintain a straight path that has important consequences for blind pedestrians. In this study, the authors addressed whether the source of veering in the absence of visual and auditory feedback is better attributed to errors in perceptual encoding or undetected motor error. Three…

Groundwater level responses to precipitation variability in Mediterranean insular aquifers

NASA Astrophysics Data System (ADS)

Lorenzo-Lacruz, Jorge; Garcia, Celso; Morán-Tejeda, Enrique

2017-09-01

Groundwater is one of the largest and most important sources of fresh water on many regions under Mediterranean climate conditions, which are exposed to large precipitation variability that includes frequent meteorological drought episodes, and present high evapotranspiration rates and water demand during the dry season. The dependence on groundwater increases in those areas with predominant permeable lithologies, contributing to aquifer recharge and the abundance of ephemeral streams. The increasing pressure of tourism on water resources in many Mediterranean coastal areas, and uncertainty related to future precipitation and water availability, make it urgent to understand the spatio-temporal response of groundwater bodies to precipitation variability, if sustainable use of the resource is to be achieved. We present an assessment of the response of aquifers to precipitation variability based on correlations between the Standardized Precipitation Index (SPI) at various time scales and the Standardized Groundwater Index (SGI) across a Mediterranean island. We detected three main responses of aquifers to accumulated precipitation anomalies: (i) at short time scales of the SPI (<6 months); (ii) at medium time scales (6-24 months); and at long time scales (>24 months). The differing responses were mainly explained by differences in lithology and the percentage of highly permeable rock strata in the aquifer recharge areas. We also identified differences in the months and seasons when aquifer storages are more dependent on precipitation; these were related to climate seasonality and the degree of aquifer exploitation or underground water extraction. The recharge of some aquifers, especially in mountainous areas, is related to precipitation variability within a limited spatial extent, whereas for aquifers located in the plains, precipitation variability influence much larger areas; the topography and geological structure of the island explain these differences. Results indicate large spatial variability in the response of aquifers to precipitation in a very small area, highlighting the importance of having high spatial resolution hydro-climatic databases available to enable full understanding of the effects of climate variability on scarce water resources.

Physical and psychosocial prerequisites of functioning in relation to work ability and general subjective well-being among office workers.

PubMed

Sjögren-Rönkä, Tuulikki; Ojanen, Markku T; Leskinen, Esko K; Tmustalampi, Sirpa; Mälkiä, Esko A

2002-06-01

The purpose of the study was to investigate the physical and psychological prerequisites of functioning, as well as the social environment at work and personal factors, in relation to work ability and general subjective well-being in a group of office workers. The study was a descriptive cross-sectional investigation, using path analysis, of office workers. The subjects comprised 88 volunteers, 24 men and 64 women, from the same workplace [mean age 45.7 (SD 8.6) years]. The independent variables were measured using psychosocial and physical questionnaires and physical measurements. The first dependent variable, work ability, was measured by a work ability index. The second dependent variable, general subjective well-being, was assessed by life satisfaction and meaning of life. The variables were structured according to a modified version of the International Classification of Functioning, Disability and Health. Forward flexion of the spine, intensity of musculoskeletal symptoms, self-confidence, and mental stress at work explained 58% of work ability and had indirect effects on general subjective well-being. Self-confidence, mood, and work ability had a direct effect on general subjective well-being. The model developed explained 68% of general subjective well-being. Age played a significant role in this study population. The prerequisites of physical functioning are important in maintaining work ability, particularly among aging workers, and psychological prerequisites of functioning are of even greater importance in maintaining general subjective well-being.

The complex roles of space and environment in structuring functional, taxonomic and phylogenetic beta diversity of frogs in the Atlantic Forest

PubMed Central

Luiz, Amom Mendes; Sawaya, Ricardo J.

2018-01-01

Ecological communities are complex entities that can be maintained and structured by niche-based processes such as environmental conditions, and spatial processes such as dispersal. Thus, diversity patterns may be shaped simultaneously at different spatial scales by very distinct processes. Herein we assess whether and how functional, taxonomic, and phylogenetic beta diversities of frog tadpoles are explained by environmental and/or spatial predictors. We implemented a distance–based redundancy analysis to explore variation in components of beta diversity explained by pure environmental and pure spatial predictors, as well as their interactions, at both fine and broad spatial scales. Our results indicated important but complex roles of spatial and environmental predictors in structuring phylogenetic, taxonomic and functional beta diversities. The pure fine-scales spatial fraction was more important in structuring all beta diversity components, especially to functional and taxonomical spatial turnover. Environmental variables such as canopy cover and vegetation structure were important predictors of all components, but especially to functional and taxonomic beta diversity. We emphasize that distinct factors related to environment and space are affecting distinct components of beta diversity in different ways. Although weaker, phylogenetic beta diversity, which is structured more on biogeographical scales, and thus can be represented by spatially structured processes, was more related to broad spatial processes than other components. However, selected fine-scale spatial predictors denoted negative autocorrelation, which may be revealing the existence of differences in unmeasured habitat variables among samples. Although overall important, local environmental-based processes explained better functional and taxonomic beta diversity, as these diversity components carry an important ecological value. We highlight the importance of assessing different components of diversity patterns at different scales by spatially explicit models in order to improve our understanding of community structure and help to unravel the complex nature of biodiversity. PMID:29672575

[Soil and forest structure in the Colombian Amazon].

PubMed

Calle-Rendón, Bayron R; Moreno, Flavio; Cárdenas López, Dairon

2011-09-01

Forests structural differences could result of environmental variations at different scales. Because soils are an important component of plant's environment, it is possible that edaphic and structural variables are associated and that, in consequence, spatial autocorrelation occurs. This paper aims to answer two questions: (1) are structural and edaphic variables associated at local scale in a terra firme forest of Colombian Amazonia? and (2) are these variables regionalized at the scale of work? To answer these questions we analyzed the data of a 6ha plot established in a terra firme forest of the Amacayacu National Park. Structural variables included basal area and density of large trees (diameter > or = 10cm) (Gdos and Ndos), basal area and density of understory individuals (diameter < 10cm) (Gsot and Nsot) and number of species of large trees (sp). Edaphic variables included were pH, organic matter, P, Mg, Ca, K, Al, sand, silt and clay. Structural and edaphic variables were reduced through a principal component analysis (PCA); then, the association between edaphic and structural components from PCA was evaluated by multiple regressions. The existence of regionalization of these variables was studied through isotropic variograms, and autocorrelated variables were spatially mapped. PCA found two significant components for structure, corresponding to the structure of large trees (G, Gdos, Ndos and sp) and of small trees (N, Nsot and Gsot), which explained 43.9% and 36.2% of total variance, respectively. Four components were identified for edaphic variables, which globally explained 81.9% of total variance and basically represent drainage and soil fertility. Regression analyses were significant (p < 0.05) and showed that the structure of both large and small trees is associated with greater sand contents and low soil fertility, though they explained a low proportion of total variability (R2 was 4.9% and 16.5% for the structure of large trees and small tress, respectively). Variables with spatial autocorrelation were the structure of small trees, Al, silt, and sand. Among them, Nsot and sand content showed similar patterns of spatial distribution inside the plot.

Determinants of energy efficiency across countries

NASA Astrophysics Data System (ADS)

Yao, Guolin

With economic development, environmental concerns become more important. Economies cannot be developed without energy consumption, which is the major source of greenhouse gas emissions. Higher energy efficiency is one means of reducing emissions, but what determines energy efficiency? In this research we attempt to find answers to this question by using cross-sectional country data; that is, we examine a wide range of possible determinants of energy efficiency at the country level in an attempt to find the most important causal factors. All countries are divided into three income groups: high-income countries, middle-income countries, and low-income countries. Energy intensity is used as a measurement of energy efficiency. All independent variables belong to two categories: quantitative and qualitative. Quantitative variables are measures of the economic conditions, development indicators and energy usage situations. Qualitative variables mainly measure political, societal and economic strengths of a country. The three income groups have different economic and energy attributes. Each group has different sets of variables to explain energy efficiency. Energy prices and winter temperature are both important in high-income and middle-income countries. No qualitative variables appear in the model of high-income countries. Basic economic factors, such as institutions, political stability, urbanization level, population density, are important in low-income countries. Besides similar variables, such as macroeconomic stability and index of rule of law, the hydroelectricity share in total electric generation is also a driver of energy efficiency in middle-income countries. These variables have different policy implications for each group of countries.

Can Sap Flow Help Us to Better Understand Transpiration Patterns in Landscapes?

NASA Astrophysics Data System (ADS)

Hassler, S. K.; Weiler, M.; Blume, T.

2017-12-01

Transpiration is a key process in the hydrological cycle and a sound understanding and quantification of transpiration and its spatial variability is essential for management decisions and for improving the parameterisation of hydrological and soil-vegetation-atmosphere transfer models. At the tree scale, transpiration is commonly estimated by measuring sap flow. Besides evaporative demand and water availability, tree-specific characteristics such as species, size or social status, stand-specific characteristics such as basal area or stand density and site-specific characteristics such as geology, slope position or aspect control sap flow of individual trees. However, little is known about the relative importance or the dynamic interplay of these controls. We studied these influences with multiple linear regression models to explain the variability of sap velocity measurements in 61 beech and oak trees, located at 24 sites spread over a 290 km²-catchment in Luxembourg. For each of 132 consecutive days of the growing season of 2014 we applied linear models to the daily spatial pattern of sap velocity and determined the importance of the different predictors. By upscaling sap velocities to the tree level with the help of species-dependent empirical estimates for sapwood area we also examined patterns of sap flow as a more direct representation of transpiration. Results indicate that a combination of mainly tree- and site-specific factors controls sap velocity patterns in this landscape, namely tree species, tree diameter, geology and aspect. For sap flow, the site-specific predictors provided the largest contribution to the explained variance, however, in contrast to the sap velocity analysis, geology was more important than aspect. Spatial variability of atmospheric demand and soil moisture explained only a small fraction of the variance. However, the temporal dynamics of the explanatory power of the tree-specific characteristics, especially species, were correlated to the temporal dynamics of potential evaporation. We conclude that spatial representation of transpiration in models could benefit from including patterns according to tree and site characteristics.

Temporal variability in the importance of hydrologic, biotic, and climatic descriptors of dissolved oxygen dynamics in a shallow tidal-marsh creek

NASA Astrophysics Data System (ADS)

Nelson, N.; Munoz-Carpena, R.; Neale, P.; Tzortziou, M.; Megonigal, P.

2017-12-01

Due to strong abiotic forcing, dissolved oxygen (DO) in shallow tidal creeks often disobeys the conventional explanation of general aquatic DO cycling as biologically-regulated. In the present work, we seek to quantify the relative importance of abiotic (hydrologic and climatic), and biotic (primary productivity as represented by chlorophyll-a) descriptors of tidal creek DO. By fitting multiple linear regression models of DO to hourly chlorophyll-a, water quality, hydrology, and weather data collected in a tidal creek of a Chesapeake Bay marsh (Maryland, USA), temporal shifts (summer - early winter) in the relative importance of tidal creek DO descriptors were uncovered. Moreover, this analysis identified an alternative approach to evaluating tidal stage as a driver of DO by dividing stage into two DO-relevant variables: stage above and below bankfull depth. Within the hydrologic variable class, stage below bankfull depth dominated as an important descriptor, thus highlighting the role of pore water drainage and mixing as influential processes forcing tidal creek DO. Study findings suggest that tidal creek DO dynamics are explained by a balance of hydrologic, climatic, and biotic descriptors during warmer seasons due to many of these variables (i.e., chlorophyll-a, water temperature) acting as tracers of estuarine-marsh water mixing; conversely, in early winter months when estuarine and marsh waters differ less distinctly, hydrologic variables increase in relative importance as descriptors of tidal creek DO. These findings underline important distinctions in the underlying mechanisms dictating DO variability in shallow tidal marsh-creek environments relative to open water estuarine systems.

Temporal variability in the importance of hydrologic, biotic, and climatic descriptors of dissolved oxygen dynamics in a shallow tidal-marsh creek

NASA Astrophysics Data System (ADS)

Nelson, Natalie G.; Muñoz-Carpena, Rafael; Neale, Patrick J.; Tzortziou, Maria; Megonigal, J. Patrick

2017-08-01

Due to strong abiotic forcing, dissolved oxygen (DO) in shallow tidal creeks often disobeys the conventional explanation of general aquatic DO cycling as biologically regulated. In the present work, we seek to quantify the relative importance of abiotic (hydrologic and climatic), and biotic (primary productivity as represented by chlorophyll-a) descriptors of tidal creek DO. By fitting multiple linear regression models of DO to hourly chlorophyll-a, water quality, hydrology, and weather data collected in a tidal creek of a Chesapeake Bay marsh (Maryland, USA), temporal shifts (summer-early winter) in the relative importance of tidal creek DO descriptors were uncovered. Moreover, this analysis identified an alternative approach to evaluating tidal stage as a driver of DO by dividing stage into two DO-relevant variables: stage above and below bankfull depth. Within the hydrologic variable class, stage below bankfull depth dominated as an important descriptor, thus highlighting the role of pore water drainage and mixing as influential processes forcing tidal creek DO. Study findings suggest that tidal creek DO dynamics are explained by a balance of hydrologic, climatic, and biotic descriptors during warmer seasons due to many of these variables (i.e., chlorophyll-a, water temperature) acting as tracers of estuarine-marsh water mixing; conversely, in early winter months when estuarine and marsh waters differ less distinctly, hydrologic variables increase in relative importance as descriptors of tidal creek DO. These findings underline important distinctions in the underlying mechanisms dictating DO variability in shallow tidal marsh-creek environments relative to open water estuarine systems.

Testing Bergmann's rule and the Rosenzweig hypothesis with craniometric studies of the South American sea lion.

PubMed

Sepúlveda, Maritza; Oliva, Doris; Duran, L René; Urra, Alejandra; Pedraza, Susana N; Majluf, Patrícia; Goodall, Natalie; Crespo, Enrique A

2013-04-01

We tested the validity of Bergmann's rule and Rosenzweig's hypothesis through an analysis of the geographical variation of the skull size of Otaria flavescens along the entire distribution range of the species (except Brazil). We quantified the sizes of 606 adult South American sea lion skulls measured in seven localities of Peru, Chile, Uruguay, Argentina, and the Falkland/Malvinas Islands. Geographical and environmental variables included latitude, longitude, and monthly minimum, maximum, and mean air and ocean temperatures. We also included information on fish landings as a proxy for productivity. Males showed a positive relationship between condylobasal length (CBL) and latitude, and between CBL and the six temperature variables. By contrast, females showed a negative relationship between CBL and the same variables. Finally, female skull size showed a significant and positive correlation with fish landings, while males did not show any relationship with this variable. The body size of males conformed to Bergmann's rule, with larger individuals found in southern localities of South America. Females followed the converse of Bergmann's rule at the intraspecific level, but showed a positive relationship with the proxy for productivity, thus supporting Rosenzweig's hypothesis. Differences in the factors that drive body size in females and males may be explained by their different life-history strategies. Our analyses demonstrate that latitude and temperature are not the only factors that explain spatial variation in body size: others such as food availability are also important for explaining the ecogeographical patterns found in O. flavescens.

Modeling variability in air pollution-related health damages from individual airport emissions.

PubMed

Penn, Stefani L; Boone, Scott T; Harvey, Brian C; Heiger-Bernays, Wendy; Tripodis, Yorghos; Arunachalam, Sarav; Levy, Jonathan I

2017-07-01

In this study, we modeled concentrations of fine particulate matter (PM 2.5 ) and ozone (O 3 ) attributable to precursor emissions from individual airports in the United States, developing airport-specific health damage functions (deaths per 1000t of precursor emissions) and physically-interpretable regression models to explain variability in these functions. We applied the Community Multiscale Air Quality model using the Decoupled Direct Method to isolate PM 2.5 - or O 3 -related contributions from precursor pollutants emitted by 66 individual airports. We linked airport- and pollutant-specific concentrations with population data and literature-based concentration-response functions to create health damage functions. Deaths per 1000t of primary PM 2.5 emissions ranged from 3 to 160 across airports, with variability explained by population patterns within 500km of the airport. Deaths per 1000t of precursors for secondary PM 2.5 varied across airports from 0.1 to 2.7 for NOx, 0.06 to 2.9 for SO 2 , and 0.06 to 11 for VOCs, with variability explained by population patterns and ambient concentrations influencing particle formation. Deaths per 1000t of O 3 precursors ranged from -0.004 to 1.0 for NOx and 0.03 to 1.5 for VOCs, with strong seasonality and influence of ambient concentrations. Our findings reinforce the importance of location- and source-specific health damage functions in design of health-maximizing emissions control policies. Copyright © 2017 Elsevier Inc. All rights reserved.

Intersexual and temporal variation in foraging ecology of prothonotary warblers during the breeding season

USGS Publications Warehouse

Petit, L.J.; Petit, D.R.; Petit, K.E.; Fleming, W.J.

1990-01-01

We studied foraging ecology of Prothonotary Warblers (Protonotaria citrea) over four breeding seasons to determine if this species exhibited sex-specific or temporal variation in foraging behavior. Significant differences between sexes during the prenestling period were found for foraging height and substrate height (foraging method, plant species/substrate, perch diameter, horizontal location from trunk, and prey location were not significantly different). During the nestling period, this divergence between sexes was evident for foraging height, substrate height, substrate / tree species, and prey location. Additionally, male warblers significantly altered their behavior for all seven foraging variables between the two periods, whereas females exhibited changes similar to those of males for five of the foraging variables. This parallel shift suggests a strong behavioral response by both sexes to proximate factors (such as vegetation structure, and prey abundance and distribution) that varied throughout the breeding season. Sex-specific foraging behavior during the prenestling period was best explained by differences in reproductive responsibilities rather than by the theory of intersexual competition for limited resources. During the nestling period, neither hypothesis by itself explained foraging divergences adequately. However, when integrated with the temporal responses of the warblers to changes in prey availability, reproductive responsibilities seemed to be of primary importance in explaining intersexual niche partitioning during the nestling period. We emphasize the importance of considering both intersexual and intraseasonal variation when quantifying a species' foraging ecology.

Contribution of atmospheric circulation to recent off-shore sea-level variations in the Baltic Sea and the North Sea

NASA Astrophysics Data System (ADS)

Karabil, Sitar; Zorita, Eduardo; Hünicke, Birgit

2018-01-01

The main purpose of this study is to quantify the contribution of atmospheric factors to recent off-shore sea-level variability in the Baltic Sea and the North Sea on interannual timescales. For this purpose, we statistically analysed sea-level records from tide gauges and satellite altimetry and several climatic data sets covering the last century. Previous studies had concluded that the North Atlantic Oscillation (NAO) is the main pattern of atmospheric variability affecting sea level in the Baltic Sea and the North Sea in wintertime. However, we identify a different atmospheric circulation pattern that is more closely connected to sea-level variability than the NAO. This circulation pattern displays a link to sea level that remains stable through the 20th century, in contrast to the much more variable link between sea level and the NAO. We denote this atmospheric variability mode as the Baltic Sea and North Sea Oscillation (BANOS) index. The sea-level pressure (SLP) BANOS pattern displays an SLP dipole with centres of action located over (5° W, 45° N) and (20° E, 70° N) and this is distinct from the standard NAO SLP pattern in wintertime. In summertime, the discrepancy between the SLP BANOS and NAO patterns becomes clearer, with centres of action of the former located over (30° E, 45° N) and (20° E, 60° N). This index has a stronger connection to off-shore sea-level variability in the study area than the NAO in wintertime for the period 1993-2013, explaining locally up to 90 % of the interannual sea-level variance in winter and up to 79 % in summer. The eastern part of the Gulf of Finland is the area where the BANOS index is most sensitive to sea level in wintertime, whereas the Gulf of Riga is the most sensitive region in summertime. In the North Sea region, the maximum sea-level sensitivity to the BANOS pattern is located in the German Bight for both winter and summer seasons. We investigated, and when possible quantified, the contribution of several physical mechanisms which may explain the link between the sea-level variability and the atmospheric pattern described by the BANOS index. These mechanisms include the inverse barometer effect (IBE), freshwater balance, net energy surface flux and wind-induced water transport. We found that the most important mechanism is the IBE in both wintertime and summertime. Assuming a complete equilibration of seasonal sea level to the SLP gradients over this region, the IBE can explain up to 88 % of the sea-level variability attributed to the BANOS index in wintertime and 34 % in summertime. The net energy flux at the surface is found to be an important factor for the variation of sea level, explaining 35 % of sea-level variance in wintertime and a very small amount in summer. The freshwater flux could only explain 27 % of the variability in summertime and a negligible part in winter. In contrast to the NAO, the direct wind forcing associated with the SLP BANOS pattern does not lead to transport of water from the North Sea into the Baltic Sea in wintertime.

The relationship between species richness and ecosystem variability is shaped by the mechanism of coexistence.

PubMed

Tredennick, Andrew T; Adler, Peter B; Adler, Frederick R

2017-08-01

Theory relating species richness to ecosystem variability typically ignores the potential for environmental variability to promote species coexistence. Failure to account for fluctuation-dependent coexistence may explain deviations from the expected negative diversity-ecosystem variability relationship, and limits our ability to predict the consequences of increases in environmental variability. We use a consumer-resource model to explore how coexistence via the temporal storage effect and relative nonlinearity affects ecosystem variability. We show that a positive, rather than negative, diversity-ecosystem variability relationship is possible when ecosystem function is sampled across a natural gradient in environmental variability and diversity. We also show how fluctuation-dependent coexistence can buffer ecosystem functioning against increasing environmental variability by promoting species richness and portfolio effects. Our work provides a general explanation for variation in observed diversity-ecosystem variability relationships and highlights the importance of conserving regional species pools to help buffer ecosystems against predicted increases in environmental variability. © 2017 John Wiley & Sons Ltd/CNRS.

Linking the variability of atmospheric carbon monoxide to climate modes in the Southern Hemisphere

NASA Astrophysics Data System (ADS)

Buchholz, Rebecca; Monks, Sarah; Hammerling, Dorit; Worden, Helen; Deeter, Merritt; Emmons, Louisa; Edwards, David

2017-04-01

Biomass burning is a major driver of atmospheric carbon monoxide (CO) variability in the Southern Hemisphere. The magnitude of emissions, such as CO, from biomass burning is connected to climate through both the availability and dryness of fuel. We investigate the link between CO and climate using satellite measured CO and climate indices. Observations of total column CO from the satellite instrument MOPITT are used to build a record of interannual variability in CO since 2001. Four biomass burning regions in the Southern Hemisphere are explored. Data driven relationships are determined between CO and climate indices for the climate modes: El Niño Southern Oscillation (ENSO); the Indian Ocean Dipole (IOD); the Tropical Southern Atlantic (TSA); and the Southern Annular Mode (SAM). Stepwise forward and backward regression is used to select the best statistical model from combinations of lagged indices. We find evidence for the importance of first-order interaction terms of the climate modes when explaining CO variability. Implications of the model results are discussed for the Maritime Southeast Asia and Australasia regions. We also draw on the chemistry-climate model CAM-chem to explain the source contribution as well as the relative contributions of emissions and meteorology to CO variability.

Role of Updraft Velocity in Temporal Variability of Global Cloud Hydrometeor Number

NASA Technical Reports Server (NTRS)

Sullivan, Sylvia C.; Lee, Dong Min; Oreopoulos, Lazaros; Nenes, Athanasios

2016-01-01

Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.

Role of updraft velocity in temporal variability of global cloud hydrometeor number

DOE PAGES

Sullivan, Sylvia C.; Lee, Dongmin; Oreopoulos, Lazaros; ...

2016-05-16

Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Communitymore » Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Finally, coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.« less

Role of updraft velocity in temporal variability of global cloud hydrometeor number

NASA Astrophysics Data System (ADS)

Sullivan, Sylvia C.; Lee, Dongmin; Oreopoulos, Lazaros; Nenes, Athanasios

2016-05-01

Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.

Childhood Depression: Relation to Adaptive, Clinical and Predictor Variables

PubMed Central

Garaigordobil, Maite; Bernarás, Elena; Jaureguizar, Joana; Machimbarrena, Juan M.

2017-01-01

The study had two goals: (1) to explore the relations between self-assessed childhood depression and other adaptive and clinical variables (2) to identify predictor variables of childhood depression. Participants were 420 students aged 7–10 years old (53.3% boys, 46.7% girls). Results revealed: (1) positive correlations between depression and clinical maladjustment, school maladjustment, emotional symptoms, internalizing and externalizing problems, problem behaviors, emotional reactivity, and childhood stress; and (2) negative correlations between depression and personal adaptation, global self-concept, social skills, and resilience (sense of competence and affiliation). Linear regression analysis including the global dimensions revealed 4 predictors of childhood depression that explained 50.6% of the variance: high clinical maladjustment, low global self-concept, high level of stress, and poor social skills. However, upon introducing the sub-dimensions, 9 predictor variables emerged that explained 56.4% of the variance: many internalizing problems, low family self-concept, high anxiety, low responsibility, low personal self-assessment, high social stress, few aggressive behaviors toward peers, many health/psychosomatic problems, and external locus of control. The discussion addresses the importance of implementing prevention programs for childhood depression at early ages. PMID:28572787

Social determinants of childhood asthma symptoms: an ecological study in urban Latin America.

PubMed

Fattore, Gisel L; Santos, Carlos A T; Barreto, Mauricio L

2014-04-01

Asthma is an important public health problem in urban Latin America. This study aimed to analyze the role of socioeconomic and environmental factors as potential determinants of asthma symptoms prevalence in children from Latin American (LA) urban centers. We selected 31 LA urban centers with complete data, and an ecological analysis was performed. According to our theoretical framework, the explanatory variables were classified in three levels: distal, intermediate, and proximate. The association between variables in the three levels and prevalence of asthma symptoms was examined by bivariate and multivariate linear regression analysis weighed by sample size. In a second stage, we fitted several linear regression models introducing sequentially the variables according to the predefined hierarchy. In the final hierarchical model Gini Index, crowding, sanitation, variation in infant mortality rates and homicide rates, explained great part of the variance in asthma prevalence between centers (R(2) = 75.0 %). We found a strong association between socioeconomic and environmental variables and prevalence of asthma symptoms in LA urban children, and according to our hierarchical framework and the results found we suggest that social inequalities (measured by the Gini Index) is a central determinant to explain high prevalence of asthma in LA.

Reproductive success and contaminant associations in tree swallows (Tachycineta bicolor) used to assess a Beneficial Use Impairment in U.S. and Binational Great Lakes’ Areas of Concern

USGS Publications Warehouse

Custer, Christine M.; Custer, Thomas W.; Etterson, Matthew A.; Dummer, Paul; Goldberg, Diana R.; Franson, J. Christian

2018-01-01

During 2010-2014, tree swallow (Tachycineta bicolor) reproductive success was monitored at 68 sites across all 5 Great Lakes, including 58 sites located within Great Lakes Areas of Concern (AOCs) and 10 non-AOCs. Sample eggs were collected from tree swallow clutches and analyzed for contaminants including polychlorinated biphenyls (PCBs), dioxins and furans, polybrominated diphenyl ethers, and 34 other organic compounds. Contaminant data were available for 360 of the clutches monitored. Markov chain multistate modeling was used to assess the importance of 5 ecological variables and 11 of the dominant contaminants in explaining the pattern of egg and nestling failure rates. Four of 5 ecological variables (Female Age, Date within season, Year, and Site) were important explanatory variables. Of the 11 contaminants, only total dioxin and furan toxic equivalents (TEQs) explained a significant amount of the egg failure probabilities. Neither total PCBs nor PCB TEQs explained the variation in egg failure rates. In a separate analysis, polycyclic aromatic hydrocarbon exposure in nestling diet, used as a proxy for female diet during egg laying, was significantly correlated with the daily probability of egg failure. The 8 sites within AOCs which had poorer reproduction when compared to 10 non-AOC sites, the measure of impaired reproduction as defined by the Great Lakes Restoration Initiative, were associated with exposure to dioxins and furan TEQs, PAHs, or depredation. Only 2 sites had poorer reproduction than the poorest performing non-AOC. Using a classic (non-modeling) approach to estimating reproductive success, 82% of nests hatched at least 1 egg, and 75% of eggs laid, excluding those collected for contaminant analyses, hatched.

Reproductive success and contaminant associations in tree swallows (Tachycineta bicolor) used to assess a Beneficial Use Impairment in U.S. and Binational Great Lakes' Areas of Concern.

PubMed

Custer, Christine M; Custer, Thomas W; Etterson, Matthew A; Dummer, Paul M; Goldberg, Diana; Franson, J Christian

2018-05-01

During 2010-2014, tree swallow (Tachycineta bicolor) reproductive success was monitored at 68 sites across all 5 Great Lakes, including 58 sites located within Great Lakes Areas of Concern (AOCs) and 10 non-AOCs. Sample eggs were collected from tree swallow clutches and analyzed for contaminants including polychlorinated biphenyls (PCBs), dioxins and furans, polybrominated diphenyl ethers, and 34 other organic compounds. Contaminant data were available for 360 of the clutches monitored. Markov chain multistate modeling was used to assess the importance of 5 ecological variables and 11 of the dominant contaminants in explaining the pattern of egg and nestling failure rates. Four of 5 ecological variables (Female Age, Date within season, Year, and Site) were important explanatory variables. Of the 11 contaminants, only total dioxin and furan toxic equivalents (TEQs) explained a significant amount of the egg failure probabilities. Neither total PCBs nor PCB TEQs explained the variation in egg failure rates. In a separate analysis, polycyclic aromatic hydrocarbon exposure in nestling diet, used as a proxy for female diet during egg laying, was significantly correlated with the daily probability of egg failure. The 8 sites within AOCs which had poorer reproduction when compared to 10 non-AOC sites, the measure of impaired reproduction as defined by the Great Lakes Restoration Initiative, were associated with exposure to dioxins and furan TEQs, PAHs, or depredation. Only 2 sites had poorer reproduction than the poorest performing non-AOC. Using a classic (non-modeling) approach to estimating reproductive success, 82% of nests hatched at least 1 egg, and 75% of eggs laid, excluding those collected for contaminant analyses, hatched.

Environmental factors affecting feed intake of steers in different housing systems in the summer

NASA Astrophysics Data System (ADS)

Koknaroglu, H.; Otles, Z.; Mader, T.; Hoffman, M. P.

2008-07-01

A total of 188 yearling steers of predominantly Angus and Hereford breeds, with mean body weight of 299 kg, were used in this study, which started on 8 April and finished on 3 October, to assess the effects of environmental factors on feed intake of steers in various housing systems. Housing consisted of outside lots with access to overhead shelter, outside lots with no overhead shelter and a cold confinement building. Ad libitum corn, 2.27 kg of 35% dry matter whole plant sorghum silage and 0.68 kg of a 61% protein-vitamin-mineral supplement was offered. Feed that was not consumed was measured to determine feed intake. The temperature data were recorded by hygro-thermographs. Hourly temperatures and humidity were used to develop weather variables. Regression analysis was used and weather variables were regressed on dry matter intake (DMI). When addition of a new variable did not improve R 2 more than one unit, then the number of variables in the model was truncated. Cattle in confinement had lower DMI than those in open lots and those in open lots with access to an overhead shelter ( P < 0.05). Cattle in outside lots with access to overhead shelter had similar DMI compared to those in open lots ( P = 0.065). Effect of heat was predominantly displayed in August in the three housing systems. In terms of explaining variation in DMI, in outside lots with access to overhead shelter, average and daytime temperatures were important factors, whereas in open lots, nocturnal, peak and average temperatures were important factors. In confinement buildings, the previous day’s temperature and humidity index were the most important factors explaining variation in DMI. Results show the effect of housing and weather variables on DMI in summer and when considering these results, cattle producers wishing to improve cattle feedlot performance should consider housing conditions providing less stress or more comfort.

Effect of Game Management on Wild Red-Legged Partridge Abundance

PubMed Central

Díaz-Fernández, Silvia; Arroyo, Beatriz; Casas, Fabián; Martinez-Haro, Monica; Viñuela, Javier

2013-01-01

The reduction of game and fish populations has increased investment in management practices. Hunting and fishing managers use several tools to maximize harvest. Managers need to know the impact their management has on wild populations. This issue is especially important to improve management efficacy and biodiversity conservation. We used questionnaires and field bird surveys in 48 hunting estates to assess whether red-legged partridge Alectoris rufa young/adult ratio and summer abundance were related to the intensity of management (provision of supplementary food and water, predator control and releases of farm-bred partridges), harvest intensity or habitat in Central Spain. We hypothesized that partridge abundance would be higher where management practices were applied more intensively. Variation in young/adult ratio among estates was best explained by habitat, year and some management practices. Density of feeders and water points had a positive relationship with this ratio, while the density of partridges released and magpies controlled were negatively related to it. The variables with greatest relative importance were feeders, releases and year. Variations in post-breeding red-legged partridge abundance among estates were best explained by habitat, year, the same management variables that influenced young/adult ratio, and harvest intensity. Harvest intensity was negatively related to partridge abundance. The other management variables had the same type of relationship with abundance as with young/adult ratio, except magpie control. Variables with greatest relative importance were habitat, feeders, water points, releases and harvest intensity. Our study suggests that management had an overall important effect on post-breeding partridge abundance. However, this effect varied among tools, as some had the desired effect (increase in partridge abundance), whereas others did not or even had a negative relationship (such as release of farm-reared birds) and can be thus considered inefficient or even detrimental. We advise reconsidering their use from both ecological and economical points of view. PMID:23840515

Large-Scale Effects of Timber Harvesting on Stream Systems in the Ouachita Mountains, Arkansas, USA

NASA Astrophysics Data System (ADS)

Williams, Lance R.; Taylor, Christopher M.; Warren, Melvin L., Jr.; Clingenpeel, J. Alan

2002-01-01

Using Basin Area Stream Survey (BASS) data from the United States Forest Service, we evaluated how timber harvesting influenced patterns of variation in physical stream features and regional fish and macroinvertebrate assemblages. Data were collected for three years (1990-1992) from six hydrologically variable streams in the Ouachita Mountains, Arkansas, USA that were paired by management regime within three drainage basins. Specifically, we used multivariate techniques to partition variability in assemblage structure (taxonomic and trophic) that could be explained by timber harvesting, drainage basin differences, year-to-year variability, and their shared variance components. Most of the variation in fish assemblages was explained by drainage basin differences, and both basin and year-of-sampling influenced macroinvertebrate assemblages. All three factors modeled, including interactions between drainage basins and timber harvesting, influenced variability in physical stream features. Interactions between timber harvesting and drainage basins indicated that differences in physical stream features were important in determining the effects of logging within a basin. The lack of a logging effect on the biota contradicts predictions for these small, hydrologically variable streams. We believe this pattern is related to the large scale of this study and the high levels of natural variability in the streams. Alternatively, there may be time-specific effects we were unable to detect with our sampling design and analyses.

[Winter wheat yield gap between field blocks based on comparative performance analysis].

PubMed

Chen, Jian; Wang, Zhong-Yi; Li, Liang-Tao; Zhang, Ke-Feng; Yu, Zhen-Rong

2008-09-01

Based on a two-year household survey data, the yield gap of winter wheat in Quzhou County of Hebei Province, China in 2003-2004 was studied through comparative performance analysis (CPA). The results showed that there was a greater yield gap (from 4.2 to 7.9 t x hm(-2)) between field blocks, with a variation coefficient of 0.14. Through stepwise forward linear multiple regression, it was found that the yield model with 8 selected variables could explain 63% variability of winter wheat yield. Among the variables selected, soil salinity, soil fertility, and irrigation water quality were the most important limiting factors, accounting for 52% of the total yield gap. Crop variety was another important limiting factor, accounting for 14%; while planting date, fertilizer type, disease and pest, and water press accounted for 7%, 14%, 10%, and 3%, respectively. Therefore, besides soil and climate conditions, management practices occupied the majority of yield variability in Quzhou County, suggesting that the yield gap could be reduced significantly through optimum field management.

Conifer density within lake catchments predicts fish mercury concentrations in remote subalpine lakes

USGS Publications Warehouse

Eagles-Smith, Collin A.; Herring, Garth; Johnson, Branden L.; Graw, Rick

2016-01-01

Remote high-elevation lakes represent unique environments for evaluating the bioaccumulation of atmospherically deposited mercury through freshwater food webs, as well as for evaluating the relative importance of mercury loading versus landscape influences on mercury bioaccumulation. The increase in mercury deposition to these systems over the past century, coupled with their limited exposure to direct anthropogenic disturbance make them useful indicators for estimating how changes in mercury emissions may propagate to changes in Hg bioaccumulation and ecological risk. We evaluated mercury concentrations in resident fish from 28 high-elevation, sub-alpine lakes in the Pacific Northwest region of the United States. Fish total mercury (THg) concentrations ranged from 4 to 438 ng/g wet weight, with a geometric mean concentration (±standard error) of 43 ± 2 ng/g ww. Fish THg concentrations were negatively correlated with relative condition factor, indicating that faster growing fish that are in better condition have lower THg concentrations. Across the 28 study lakes, mean THg concentrations of resident salmonid fishes varied as much as 18-fold among lakes. We used a hierarchal statistical approach to evaluate the relative importance of physiological, limnological, and catchment drivers of fish Hg concentrations. Our top statistical model explained 87% of the variability in fish THg concentrations among lakes with four key landscape and limnological variables: catchment conifer density (basal area of conifers within a lake's catchment), lake surface area, aqueous dissolved sulfate, and dissolved organic carbon. Conifer density within a lake's catchment was the most important variable explaining fish THg concentrations across lakes, with THg concentrations differing by more than 400 percent across the forest density spectrum. These results illustrate the importance of landscape characteristics in controlling mercury bioaccumulation in fish.

Conifer density within lake catchments predicts fish mercury concentrations in remote subalpine lakes.

PubMed

Eagles-Smith, Collin A; Herring, Garth; Johnson, Branden; Graw, Rick

2016-05-01

Remote high-elevation lakes represent unique environments for evaluating the bioaccumulation of atmospherically deposited mercury through freshwater food webs, as well as for evaluating the relative importance of mercury loading versus landscape influences on mercury bioaccumulation. The increase in mercury deposition to these systems over the past century, coupled with their limited exposure to direct anthropogenic disturbance make them useful indicators for estimating how changes in mercury emissions may propagate to changes in Hg bioaccumulation and ecological risk. We evaluated mercury concentrations in resident fish from 28 high-elevation, sub-alpine lakes in the Pacific Northwest region of the United States. Fish total mercury (THg) concentrations ranged from 4 to 438 ng/g wet weight, with a geometric mean concentration (±standard error) of 43 ± 2 ng/g ww. Fish THg concentrations were negatively correlated with relative condition factor, indicating that faster growing fish that are in better condition have lower THg concentrations. Across the 28 study lakes, mean THg concentrations of resident salmonid fishes varied as much as 18-fold among lakes. We used a hierarchal statistical approach to evaluate the relative importance of physiological, limnological, and catchment drivers of fish Hg concentrations. Our top statistical model explained 87% of the variability in fish THg concentrations among lakes with four key landscape and limnological variables: catchment conifer density (basal area of conifers within a lake's catchment), lake surface area, aqueous dissolved sulfate, and dissolved organic carbon. Conifer density within a lake's catchment was the most important variable explaining fish THg concentrations across lakes, with THg concentrations differing by more than 400 percent across the forest density spectrum. These results illustrate the importance of landscape characteristics in controlling mercury bioaccumulation in fish. Published by Elsevier Ltd.

A Comparative Study on Perceived Effects of Communication Networks in Acquiring International Orientations.

ERIC Educational Resources Information Center

Haavelsrud, Magnus

A study was designed to test the hypothesis that different communication stages between nations--primitive, traditional, modern, and neomodern--provide important variables for explaining differences in pre-adults' conception of war in different countries. Although the two samples used in the study were drawn from two cultures which fall into the…

Predicting Item Difficulty of Science National Curriculum Tests: The Case of Key Stage 2 Assessments

ERIC Educational Resources Information Center

El Masri, Yasmine H.; Ferrara, Steve; Foltz, Peter W.; Baird, Jo-Anne

2017-01-01

Predicting item difficulty is highly important in education for both teachers and item writers. Despite identifying a large number of explanatory variables, predicting item difficulty remains a challenge in educational assessment with empirical attempts rarely exceeding 25% of variance explained. This paper analyses 216 science items of key stage…

Incorporating remotely sensed tree canopy cover data into broad scale assessments of wildlife habitat distribution and conservation

Treesearch

Sebastian Martinuzzi; Lee A. Vierling; William A. Gould; Kerri T. Vierling; Andrew T. Hudak

2009-01-01

Remote sensing provides critical information for broad scale assessments of wildlife habitat distribution and conservation. However, such efforts have been typically unable to incorporate information about vegetation structure, a variable important for explaining the distribution of many wildlife species. We evaluated the consequences of incorporating remotely sensed...

The Role of Personality in Adolescent Career Planning and Exploration: A Social Cognitive Perspective

ERIC Educational Resources Information Center

Rogers, Mary E.; Creed, Peter A.; Glendon, A. Ian

2008-01-01

Social cognitive career theory (SCCT) recognises the importance of individual differences and contextual influences in the career decision-making process. In extending the SCCT choice model, this study tested the role of personality, social supports, and the SCCT variables of self-efficacy, outcome expectations and goals in explaining the career…

Testing Gender Effects on the Mechanisms Explaining the Association between Post-Traumatic Stress Symptoms and Substance Use Frequency

PubMed Central

Bornovalova, Marina A.; Ouimette, Paige; Crawford, Aaron V.; Levy, Roy

2009-01-01

The present study examines gender differences in the mechanisms that explain the association between PTSD symptoms and substance use frequency in a sample of 182 urban substance users. Specifically, the current study examined gender differences in the role of two potential explanatory variables, namely, difficulties controlling impulsive behavior when distressed (IMP), and a lack of emotional awareness and clarity (AW/CLAR). Multiple-group path modeling (across males and females) was used to examine gender differences in the path coefficients from PTSD symptoms to IMP and AW/CLAR, and from these latter variables to drug use frequency. Results indicated that PTSD symptoms were associated with IMP and AW/CLAR, and these path coefficients did not vary by gender. However, gender differences emerged when considering the path coefficients from AW/CLAR and IMP to substance use frequency. Specifically, for women, the association between PTSD and substance use was partially explained by IMP, whereas for men, the association between PTSD and substance use was partially explained by AW/CLAR. The current study is the first to examine gender differences in mechanisms accounting for the association between PTSD and substance use frequency, and these results also support the value and importance of examining gender differences in mechanisms underlying PTSD-SUD comorbidity. PMID:19423233

Cardinal features of involuntary force variability can arise from the closed-loop control of viscoelastic afferented muscles

PubMed Central

Laine, Christopher M.; Valero-Cuevas, Francisco J.

2018-01-01

Involuntary force variability below 15 Hz arises from, and is influenced by, many factors including descending neural drive, proprioceptive feedback, and mechanical properties of muscles and tendons. However, their potential interactions that give rise to the well-structured spectrum of involuntary force variability are not well understood due to a lack of experimental techniques. Here, we investigated the generation, modulation, and interactions among different sources of force variability using a physiologically-grounded closed-loop simulation of an afferented muscle model. The closed-loop simulation included a musculotendon model, muscle spindle, Golgi tendon organ (GTO), and a tracking controller which enabled target-guided force tracking. We demonstrate that closed-loop control of an afferented musculotendon suffices to replicate and explain surprisingly many cardinal features of involuntary force variability. Specifically, we present 1) a potential origin of low-frequency force variability associated with co-modulation of motor unit firing rates (i.e.,‘common drive’), 2) an in-depth characterization of how proprioceptive feedback pathways suffice to generate 5-12 Hz physiological tremor, and 3) evidence that modulation of those feedback pathways (i.e., presynaptic inhibition of Ia and Ib afferents, and spindle sensitivity via fusimotor drive) influence the full spectrum of force variability. These results highlight the previously underestimated importance of closed-loop neuromechanical interactions in explaining involuntary force variability during voluntary ‘isometric’ force control. Furthermore, these results provide the basis for a unifying theory that relates spinal circuitry to various manifestations of altered involuntary force variability in fatigue, aging and neurological disease. PMID:29309405

Cardinal features of involuntary force variability can arise from the closed-loop control of viscoelastic afferented muscles.

PubMed

Nagamori, Akira; Laine, Christopher M; Valero-Cuevas, Francisco J

2018-01-01

Involuntary force variability below 15 Hz arises from, and is influenced by, many factors including descending neural drive, proprioceptive feedback, and mechanical properties of muscles and tendons. However, their potential interactions that give rise to the well-structured spectrum of involuntary force variability are not well understood due to a lack of experimental techniques. Here, we investigated the generation, modulation, and interactions among different sources of force variability using a physiologically-grounded closed-loop simulation of an afferented muscle model. The closed-loop simulation included a musculotendon model, muscle spindle, Golgi tendon organ (GTO), and a tracking controller which enabled target-guided force tracking. We demonstrate that closed-loop control of an afferented musculotendon suffices to replicate and explain surprisingly many cardinal features of involuntary force variability. Specifically, we present 1) a potential origin of low-frequency force variability associated with co-modulation of motor unit firing rates (i.e.,'common drive'), 2) an in-depth characterization of how proprioceptive feedback pathways suffice to generate 5-12 Hz physiological tremor, and 3) evidence that modulation of those feedback pathways (i.e., presynaptic inhibition of Ia and Ib afferents, and spindle sensitivity via fusimotor drive) influence the full spectrum of force variability. These results highlight the previously underestimated importance of closed-loop neuromechanical interactions in explaining involuntary force variability during voluntary 'isometric' force control. Furthermore, these results provide the basis for a unifying theory that relates spinal circuitry to various manifestations of altered involuntary force variability in fatigue, aging and neurological disease.

Climate, streamflow, and legacy effects on growth of riparian Populus angustifolia in the arid San Luis Valley, Colorado

USGS Publications Warehouse

Andersen, Douglas

2016-01-01

Knowledge of the factors affecting the vigor of desert riparian trees is important for their conservation and management. I used multiple regression to assess effects of streamflow and climate (12–14 years of data) or climate alone (up to 60 years of data) on radial growth of clonal narrowleaf cottonwood (Populus angustifolia), a foundation species in the arid, Closed Basin portion of the San Luis Valley, Colorado. I collected increment cores from trees (14–90 cm DBH) at four sites along each of Sand and Deadman creeks (total N = 85), including both perennial and ephemeral reaches. Analyses on trees <110 m from the stream channel explained 33–64% of the variation in standardized growth index (SGI) over the period having discharge measurements. Only 3 of 7 models included a streamflow variable; inclusion of prior-year conditions was common. Models for trees farther from the channel or over a deep water table explained 23–71% of SGI variability, and 4 of 5 contained a streamflow variable. Analyses using solely climate variables over longer time periods explained 17–85% of SGI variability, and 10 of 12 included a variable indexing summer precipitation. Three large, abrupt shifts in recent decades from wet to dry conditions (indexed by a seasonal Palmer Drought Severity Index) coincided with dramatically reduced radial growth. Each shift was presumably associated with branch dieback that produced a legacy effect apparent in many SGI series: uncharacteristically low SGI in the year following the shift. My results suggest trees in locations distant from the active channel rely on the regional shallow unconfined aquifer, summer rainfall, or both to meet water demands. The landscape-level differences in the water supplies sustaining these trees imply variable effects from shifts in winter-versus monsoon-related precipitation, and from climate change versus streamflow or groundwater management.

Dietary supplement use and smoking are important correlates of biomarkers of water-soluble vitamin status after adjusting for sociodemographic and lifestyle variables in a representative sample of US adults1,2,3

PubMed Central

Pfeiffer, Christine M.; Sternberg, Maya R.; Schleicher, Rosemary L.; Rybak, Michael E.

2016-01-01

Biochemical indicators of water-soluble vitamin (WSV) status have been measured in a nationally representative sample of the US population in NHANES 2003–2006. To examine whether demographic differentials in nutritional status were related to and confounded by certain variables, we assessed the association of sociodemographic (age, sex, race-ethnicity, education, income) and lifestyle variables (dietary supplement use, smoking, alcohol consumption, BMI, physical activity) with biomarkers of WSV status in adults (≥20 y): serum and RBC folate, serum pyridoxal-5′-phosphate (PLP), serum 4-pyridoxic acid, serum total cobalamin (B-12), plasma total homocysteine (tHcy), plasma methylmalonic acid (MMA), and serum ascorbic acid. Age (except for PLP) and smoking (except for MMA) were generally the strongest significant correlates of these biomarkers (|r| ≤0.43) and together with supplement use explained more of the variability as compared to the other covariates in bivariate analysis. In multiple regression models, sociodemographic and lifestyle variables together explained from 7% (B-12) to 29% (tHcy) of the biomarker variability. We observed significant associations for most biomarkers (≥6 out of 8) with age, sex, race-ethnicity, supplement use, smoking, and BMI; and for some biomarkers with PIR (5/8), education (1/8), alcohol consumption (4/8), and physical activity (5/8). We noted large estimated percent changes in biomarker concentrations between race-ethnic groups (from −24% to 20%), between supplement users and nonusers (from −12% to 104%), and between smokers and nonsmokers (from −28% to 8%). In summary, age, sex, and race-ethnic differentials in biomarker concentrations remained significant after adjusting for sociodemographic and lifestyle variables. Supplement use and smoking were important correlates of biomarkers of WSV status. PMID:23576641

Dietary supplement use and smoking are important correlates of biomarkers of water-soluble vitamin status after adjusting for sociodemographic and lifestyle variables in a representative sample of U.S. adults.

PubMed

Pfeiffer, Christine M; Sternberg, Maya R; Schleicher, Rosemary L; Rybak, Michael E

2013-06-01

Biochemical indicators of water-soluble vitamin (WSV) status were measured in a nationally representative sample of the U.S. population in NHANES 2003-2006. To examine whether demographic differentials in nutritional status were related to and confounded by certain variables, we assessed the association of sociodemographic (age, sex, race-ethnicity, education, income) and lifestyle (dietary supplement use, smoking, alcohol consumption, BMI, physical activity) variables with biomarkers of WSV status in adults (aged ≥ 20 y): serum and RBC folate, serum pyridoxal-5'-phosphate (PLP), serum 4-pyridoxic acid, serum total cobalamin (vitamin B-12), plasma total homocysteine (tHcy), plasma methylmalonic acid (MMA), and serum ascorbic acid. Age (except for PLP) and smoking (except for MMA) were generally the strongest significant correlates of these biomarkers (|r| ≤ 0.43) and together with supplement use explained more of the variability compared with the other covariates in bivariate analysis. In multiple regression models, sociodemographic and lifestyle variables together explained from 7 (vitamin B-12) to 29% (tHcy) of the biomarker variability. We observed significant associations for most biomarkers (≥ 6 of 8) with age, sex, race-ethnicity, supplement use, smoking, and BMI and for some biomarkers with PIR (5 of 8), education (1 of 8), alcohol consumption (4 of 8), and physical activity (5 of 8). We noted large estimated percentage changes in biomarker concentrations between race-ethnic groups (from -24 to 20%), between supplement users and nonusers (from -12 to 104%), and between smokers and nonsmokers (from -28 to 8%). In summary, age, sex, and race-ethnic differentials in biomarker concentrations remained significant after adjusting for sociodemographic and lifestyle variables. Supplement use and smoking were important correlates of biomarkers of WSV status.

Workers' compensation costs among construction workers: a robust regression analysis.

PubMed

Friedman, Lee S; Forst, Linda S

2009-11-01

Workers' compensation data are an important source for evaluating costs associated with construction injuries. We describe the characteristics of injured construction workers filing claims in Illinois between 2000 and 2005 and the factors associated with compensation costs using a robust regression model. In the final multivariable model, the cumulative percent temporary and permanent disability-measures of severity of injury-explained 38.7% of the variance of cost. Attorney costs explained only 0.3% of the variance of the dependent variable. The model used in this study clearly indicated that percent disability was the most important determinant of cost, although the method and uniformity of percent impairment allocation could be better elucidated. There is a need to integrate analytical methods that are suitable for skewed data when analyzing claim costs.

Fire danger index efficiency as a function of fuel moisture and fire behavior.

PubMed

Torres, Fillipe Tamiozzo Pereira; Romeiro, Joyce Machado Nunes; Santos, Ana Carolina de Albuquerque; de Oliveira Neto, Ricardo Rodrigues; Lima, Gumercindo Souza; Zanuncio, José Cola

2018-08-01

Assessment of the performance of forest fire hazard indices is important for prevention and management strategies, such as planning prescribed burnings, public notifications and firefighting resource allocation. The objective of this study was to evaluate the performance of fire hazard indices considering fire behavior variables and susceptibility expressed by the moisture of combustible material. Controlled burns were carried out at different times and information related to meteorological conditions, characteristics of combustible material and fire behavior variables were recorded. All variables analyzed (fire behavior and fuel moisture content) can be explained by the prediction indices. The Brazilian EVAP/P showed the best performance, both at predicting moisture content of the fuel material and fire behavior variables, and the Canadian system showed the best performance to predicting the rate of spread. The coherence of the correlations between the indices and the variables analyzed makes the methodology, which can be applied anywhere, important for decision-making in regions with no records or with only unreliable forest fire data. Copyright © 2018 Elsevier B.V. All rights reserved.

A global synthesis of plant extinction rates in urban areas.

PubMed

Hahs, Amy K; McDonnell, Mark J; McCarthy, Michael A; Vesk, Peter A; Corlett, Richard T; Norton, Briony A; Clemants, Steven E; Duncan, Richard P; Thompson, Ken; Schwartz, Mark W; Williams, Nicholas S G

2009-11-01

Plant extinctions from urban areas are a growing threat to biodiversity worldwide. To minimize this threat, it is critical to understand what factors are influencing plant extinction rates. We compiled plant extinction rate data for 22 cities around the world. Two-thirds of the variation in plant extinction rates was explained by a combination of the city's historical development and the current proportion of native vegetation, with the former explaining the greatest variability. As a single variable, the amount of native vegetation remaining also influenced extinction rates, particularly in cities > 200 years old. Our study demonstrates that the legacies of landscape transformations by agrarian and urban development last for hundreds of years, and modern cities potentially carry a large extinction debt. This finding highlights the importance of preserving native vegetation in urban areas and the need for mitigation to minimize potential plant extinctions in the future.

Stress appraisal, coping, and work engagement among police recruits: an exploratory study.

PubMed

Kaiseler, Mariana; Queirós, Cristina; Passos, Fernando; Sousa, Pedro

2014-04-01

This study investigated the influence of stress appraisal and coping on work engagement levels (Absorption, Vigour, and Dedication) of police recruits. Participants were 387 men, ages 20 to 33 yr. (M = 24.1, SD = 2.4), in their last month of academy training before becoming police officers. Partially in support of predictions, work engagement was associated with Stressor control perceived, but not Stress intensity experienced over a self-selected stressor. Although the three dimensions of work engagement were explained by Stressor control and coping, Absorption was the dimension better explained by these variables. Police recruits reporting higher Absorption, Vigour, and Dedication reported using more Active coping and less Behavioural disengagement. Results showed that stress appraisal and coping are important variables influencing work engagement among police recruits. Findings suggested that future applied interventions fostering work engagement among police recruits should reinforce perceptions of control over a stressor as well as Active coping strategies.

Single- and Dual-Process Models of Biased Contingency Detection.

PubMed

Vadillo, Miguel A; Blanco, Fernando; Yarritu, Ion; Matute, Helena

2016-01-01

Decades of research in causal and contingency learning show that people's estimations of the degree of contingency between two events are easily biased by the relative probabilities of those two events. If two events co-occur frequently, then people tend to overestimate the strength of the contingency between them. Traditionally, these biases have been explained in terms of relatively simple single-process models of learning and reasoning. However, more recently some authors have found that these biases do not appear in all dependent variables and have proposed dual-process models to explain these dissociations between variables. In the present paper we review the evidence for dissociations supporting dual-process models and we point out important shortcomings of this literature. Some dissociations seem to be difficult to replicate or poorly generalizable and others can be attributed to methodological artifacts. Overall, we conclude that support for dual-process models of biased contingency detection is scarce and inconclusive.

Influence of the Bermuda High on interannual variability of summertime ozone in the Houston-Galveston-Brazoria region

NASA Astrophysics Data System (ADS)

Wang, Yuxuan; Jia, Beixi; Wang, Sing-Chun; Estes, Mark; Shen, Lu; Xie, Yuanyu

2016-12-01

The Bermuda High (BH) quasi-permanent pressure system is the key large-scale circulation pattern influencing summertime weather over the eastern and southern US. Here we developed a multiple linear regression (MLR) model to characterize the effect of the BH on year-to-year changes in monthly-mean maximum daily 8 h average (MDA8) ozone in the Houston-Galveston-Brazoria (HGB) metropolitan region during June, July, and August (JJA). The BH indicators include the longitude of the BH western edge (BH-Lon) and the BH intensity index (BHI) defined as the pressure gradient along its western edge. Both BH-Lon and BHI are selected by MLR as significant predictors (p < 0.05) of the interannual (1990-2015) variability of the HGB-mean ozone throughout JJA, while local-scale meridional wind speed is selected as an additional predictor for August only. Local-scale temperature and zonal wind speed are not identified as important factors for any summer month. The best-fit MLR model can explain 61-72 % of the interannual variability of the HGB-mean summertime ozone over 1990-2015 and shows good performance in cross-validation (R2 higher than 0.48). The BH-Lon is the most important factor, which alone explains 38-48 % of such variability. The location and strength of the Bermuda High appears to control whether or not low-ozone maritime air from the Gulf of Mexico can enter southeastern Texas and affect air quality. This mechanism also applies to other coastal urban regions along the Gulf Coast (e.g., New Orleans, LA, Mobile, AL, and Pensacola, FL), suggesting that the BH circulation pattern can affect surface ozone variability through a large portion of the Gulf Coast.

Drivers of metacommunity structure diverge for common and rare Amazonian tree species.

PubMed

Bispo, Polyanna da Conceição; Balzter, Heiko; Malhi, Yadvinder; Slik, J W Ferry; Dos Santos, João Roberto; Rennó, Camilo Daleles; Espírito-Santo, Fernando D; Aragão, Luiz E O C; Ximenes, Arimatéa C; Bispo, Pitágoras da Conceição

2017-01-01

We analysed the flora of 46 forest inventory plots (25 m x 100 m) in old growth forests from the Amazonian region to identify the role of environmental (topographic) and spatial variables (obtained using PCNM, Principal Coordinates of Neighbourhood Matrix analysis) for common and rare species. For the analyses, we used multiple partial regression to partition the specific effects of the topographic and spatial variables on the univariate data (standardised richness, total abundance and total biomass) and partial RDA (Redundancy Analysis) to partition these effects on composition (multivariate data) based on incidence, abundance and biomass. The different attributes (richness, abundance, biomass and composition based on incidence, abundance and biomass) used to study this metacommunity responded differently to environmental and spatial processes. Considering standardised richness, total abundance (univariate) and composition based on biomass, the results for common species differed from those obtained for all species. On the other hand, for total biomass (univariate) and for compositions based on incidence and abundance, there was a correspondence between the data obtained for the total community and for common species. Our data also show that in general, environmental and/or spatial components are important to explain the variability in tree communities for total and common species. However, with the exception of the total abundance, the environmental and spatial variables measured were insufficient to explain the attributes of the communities of rare species. These results indicate that predicting the attributes of rare tree species communities based on environmental and spatial variables is a substantial challenge. As the spatial component was relevant for several community attributes, our results demonstrate the importance of using a metacommunities approach when attempting to understand the main ecological processes underlying the diversity of tropical forest communities.

Relationships between reef fish communities and remotely sensed rugosity measurements in Biscayne National Park, Florida, USA

USGS Publications Warehouse

Kuffner, Ilsa B.; Brock, John C.; Grober-Dunsmore, Rikki; Bonito, Victor E.; Hickey, T. Donald; Wright, C. Wayne

2007-01-01

The realization that coral reef ecosystem management must occur across multiple spatial scales and habitat types has led scientists and resource managers to seek variables that are easily measured over large areas and correlate well with reef resources. Here we investigate the utility of new technology in airborne laser surveying (NASA Experimental Advanced Airborne Research Lidar (EAARL)) in assessing topographical complexity (rugosity) to predict reef fish community structure on shallow (n = 10–13 per reef). Rugosity at each station was assessed in situ by divers using the traditional chain-transect method (10-m scale), and remotely using the EAARL submarine topography data at multiple spatial scales (2, 5, and 10 m). The rugosity and biological datasets were analyzed together to elucidate the predictive power of EAARL rugosity in describing the variance in reef fish community variables and to assess the correlation between chain-transect and EAARL rugosity. EAARL rugosity was not well correlated with chain-transect rugosity, or with species richness of fishes (although statistically significant, the amount of variance explained by the model was very low). Variance in reef fish community attributes was better explained in reef-by-reef variability than by physical variables. However, once the reef-by-reef variability was taken into account in a two-way analysis of variance, the importance of rugosity could be seen on individual reefs. Fish species richness and abundance were statistically higher at high rugosity stations compared to medium and low rugosity stations, as predicted by prior ecological research. The EAARL shows promise as an important mapping tool for reef resource managers as they strive to inventory and protect coral reef resources.

A Regional Modeling Framework of Phosphorus Sources and Transport in Streams of the Southeastern United States

USGS Publications Warehouse

Garcia, A.M.; Hoos, A.B.; Terziotti, S.

2011-01-01

We applied the SPARROW model to estimate phosphorus transport from catchments to stream reaches and subsequent delivery to major receiving water bodies in the Southeastern United States (U.S.). We show that six source variables and five land-to-water transport variables are significant (p<0.05) in explaining 67% of the variability in long-term log-transformed mean annual phosphorus yields. Three land-to-water variables are a subset of landscape characteristics that have been used as transport factors in phosphorus indices developed by state agencies and are identified through experimental research as influencing land-to-water phosphorus transport at field and plot scales. Two land-to-water variables - soil organic matter and soil pH - are associated with phosphorus sorption, a significant finding given that most state-developed phosphorus indices do not explicitly contain variables for sorption processes. Our findings for Southeastern U.S. streams emphasize the importance of accounting for phosphorus present in the soil profile to predict attainable instream water quality. Regional estimates of phosphorus associated with soil-parent rock were highly significant in explaining instream phosphorus yield variability. Model predictions associate 31% of phosphorus delivered to receiving water bodies to geology and the highest total phosphorus yields in the Southeast were catchments with already high background levels that have been impacted by human activity. ?? 2011 American Water Resources Association. This article is a US Government work and is in the public domain in the USA.

Determinants of virtual water flows in the Mediterranean.

PubMed

Fracasso, Andrea; Sartori, Martina; Schiavo, Stefano

2016-02-01

The aim of the paper is to investigate the main determinants of the bilateral virtual water (water used in the production of a commodity or service) flows associated with international trade in agricultural goods across the Mediterranean basin. We consider the bilateral gross flows of virtual water in the area and study what export-specific and import-specific factors are significantly associated with virtual water flows. We follow a sequential approach. Through a gravity model of trade, we obtain a "refined" version of the variable we aim to explain, one that is free of the amount of flows due to pair-specific factors affecting bilateral trade flows and that fully reflects the impact of country-specific determinants of virtual water trade. A number of country-specific potential explanatory variables, ranging from water endowments to trade barriers, from per capita GDP to irrigation prices, is presented and tested. To identify the variables that help to explain the bilateral flows of virtual water, we adopt a model selection procedure based on model averaging. Our findings confirm one of the main controversial results in the literature: larger water endowments do not necessarily lead to a larger 'export' of virtual water, as one could expect. We also find some evidence that higher water irrigation prices reduce (increase) virtual water 'exports' ('imports'). Copyright © 2015 Elsevier B.V. All rights reserved.

Microhabitat and Climatic Niche Change Explain Patterns of Diversification among Frog Families.

PubMed

Moen, Daniel S; Wiens, John J

2017-07-01

A major goal of ecology and evolutionary biology is to explain patterns of species richness among clades. Differences in rates of net diversification (speciation minus extinction over time) may often explain these patterns, but the factors that drive variation in diversification rates remain uncertain. Three important candidates are climatic niche position (e.g., whether clades are primarily temperate or tropical), rates of climatic niche change among species within clades, and microhabitat (e.g., aquatic, terrestrial, arboreal). The first two factors have been tested separately in several studies, but the relative importance of all three is largely unknown. Here we explore the correlates of diversification among families of frogs, which collectively represent ∼88% of amphibian species. We assemble and analyze data on phylogeny, climate, and microhabitat for thousands of species. We find that the best-fitting phylogenetic multiple regression model includes all three types of variables: microhabitat, rates of climatic niche change, and climatic niche position. This model explains 67% of the variation in diversification rates among frog families, with arboreal microhabitat explaining ∼31%, niche rates ∼25%, and climatic niche position ∼11%. Surprisingly, we show that microhabitat can have a much stronger influence on diversification than climatic niche position or rates of climatic niche change.

Identification of Urinary Polyphenol Metabolite Patterns Associated with Polyphenol-Rich Food Intake in Adults from Four European Countries.

PubMed

Noh, Hwayoung; Freisling, Heinz; Assi, Nada; Zamora-Ros, Raul; Achaintre, David; Affret, Aurélie; Mancini, Francesca; Boutron-Ruault, Marie-Christine; Flögel, Anna; Boeing, Heiner; Kühn, Tilman; Schübel, Ruth; Trichopoulou, Antonia; Naska, Androniki; Kritikou, Maria; Palli, Domenico; Pala, Valeria; Tumino, Rosario; Ricceri, Fulvio; Santucci de Magistris, Maria; Cross, Amanda; Slimani, Nadia; Scalbert, Augustin; Ferrari, Pietro

2017-07-25

We identified urinary polyphenol metabolite patterns by a novel algorithm that combines dimension reduction and variable selection methods to explain polyphenol-rich food intake, and compared their respective performance with that of single biomarkers in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. The study included 475 adults from four European countries (Germany, France, Italy, and Greece). Dietary intakes were assessed with 24-h dietary recalls (24-HDR) and dietary questionnaires (DQ). Thirty-four polyphenols were measured by ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS-MS) in 24-h urine. Reduced rank regression-based variable importance in projection (RRR-VIP) and least absolute shrinkage and selection operator (LASSO) methods were used to select polyphenol metabolites. Reduced rank regression (RRR) was then used to identify patterns in these metabolites, maximizing the explained variability in intake of pre-selected polyphenol-rich foods. The performance of RRR models was evaluated using internal cross-validation to control for over-optimistic findings from over-fitting. High performance was observed for explaining recent intake (24-HDR) of red wine ( r = 0.65; AUC = 89.1%), coffee ( r = 0.51; AUC = 89.1%), and olives ( r = 0.35; AUC = 82.2%). These metabolite patterns performed better or equally well compared to single polyphenol biomarkers. Neither metabolite patterns nor single biomarkers performed well in explaining habitual intake (as reported in the DQ) of polyphenol-rich foods. This proposed strategy of biomarker pattern identification has the potential of expanding the currently still limited list of available dietary intake biomarkers.

Environmental Predictors of Diversity in Recent Planktonic Foraminifera as Recorded in Marine Sediments

PubMed Central

Pearson, Paul N.; Dunkley Jones, Tom; Purvis, Andy

2016-01-01

Global diversity patterns are thought to result from a combination of environmental and historical factors. This study tests the set of ecological and evolutionary hypotheses proposed to explain the global variation in present-day coretop diversity in the macroperforate planktonic foraminifera, a clade with an exceptional fossil record. Within this group, marine surface sediment assemblages are thought to represent an accurate, although centennial to millennial time-averaged, representation of recent diversity patterns. Environmental variables chosen to capture ocean temperature, structure, productivity and seasonality were used to model a range of diversity measures across the world’s oceans. Spatial autoregressive models showed that the same broad suite of environmental variables were important in shaping each of the four largely independent diversity measures (rarefied species richness, Simpson’s evenness, functional richness and mean evolutionary age). Sea-surface temperature explains the largest portion of diversity in all four diversity measures, but not in the way predicted by the metabolic theory of ecology. Vertical structure could be linked to increased diversity through the strength of stratification, but not through the depth of the mixed layer. There is limited evidence that seasonal turnover explains diversity patterns. There is evidence for functional redundancy in the low-latitude sites. The evolutionary mechanism of deep-time stability finds mixed support whilst there is relatively little evidence for an out-of-the-tropics model. These results suggest the diversity patterns of planktonic foraminifera cannot be explained by any one environmental variable or proposed mechanism, but instead reflect multiple processes acting in concert. PMID:27851751

Environmental Predictors of Diversity in Recent Planktonic Foraminifera as Recorded in Marine Sediments.

PubMed

Fenton, Isabel S; Pearson, Paul N; Dunkley Jones, Tom; Purvis, Andy

2016-01-01

Global diversity patterns are thought to result from a combination of environmental and historical factors. This study tests the set of ecological and evolutionary hypotheses proposed to explain the global variation in present-day coretop diversity in the macroperforate planktonic foraminifera, a clade with an exceptional fossil record. Within this group, marine surface sediment assemblages are thought to represent an accurate, although centennial to millennial time-averaged, representation of recent diversity patterns. Environmental variables chosen to capture ocean temperature, structure, productivity and seasonality were used to model a range of diversity measures across the world's oceans. Spatial autoregressive models showed that the same broad suite of environmental variables were important in shaping each of the four largely independent diversity measures (rarefied species richness, Simpson's evenness, functional richness and mean evolutionary age). Sea-surface temperature explains the largest portion of diversity in all four diversity measures, but not in the way predicted by the metabolic theory of ecology. Vertical structure could be linked to increased diversity through the strength of stratification, but not through the depth of the mixed layer. There is limited evidence that seasonal turnover explains diversity patterns. There is evidence for functional redundancy in the low-latitude sites. The evolutionary mechanism of deep-time stability finds mixed support whilst there is relatively little evidence for an out-of-the-tropics model. These results suggest the diversity patterns of planktonic foraminifera cannot be explained by any one environmental variable or proposed mechanism, but instead reflect multiple processes acting in concert.

Young adults' social drinking as explained by an augmented theory of planned behaviour: the roles of prototypes, willingness, and gender.

PubMed

Zimmermann, Friederike; Sieverding, Monika

2010-09-01

This study focused on young adults' alcohol consumption in social contexts. A dual-process model (including reasoned action and social reaction) was applied by combining the theory of planned behaviour (TPB) and the prototype/willingness model. A key question was whether willingness and actor and abstainer prototype variables would augment the TPB by increasing explained variance. Participants completed questionnaires prior to spending an evening socializing over the weekend (Time 1). Behavioural data were obtained by telephone interviews a few days after the social drinking occasion (Time 2). N=300 people (mean age 25 years) took part in the study. The outcome measure of pure alcohol in grams was calculated based on participants' reports about their consumed drinks. Multigroup path analyses were conducted because of sex differences on behavioural and psychological variables. The TPB explained 35% of the variance in men's and 41% in women's alcohol consumption. Augmentation with prototype perception and willingness contributed significantly to the prediction of intention (DeltaR(2)=.07) and alcohol consumption for men (DeltaR(2)=.14). A significant interaction implied that willingness led to heavy drinking particularly among those men who made negative evaluations of the abstainer prototype. Women's alcohol consumption is explained by TPB variables via a more controlled reasoned-action path only, whereas additional processes (e.g., pursuing the actor image intentionally, rejecting the abstainer image more intuitively) are important for men. The moderating role of gender is discussed in light of traditional gender roles and recent trends in alcohol consumption.

Health impacts of large releases of radionuclides. Mental health, stress and risk perception: insights from psychological research.

PubMed

Renn, O

1997-01-01

Risk perceptions are only slightly correlated with the expected values of a probability distribution for negative health impacts. Psychometric studies have documented that context variables such as dread or personal control are important predictors for the perceived seriousness of risk. Studies about cultural patterns of risk perceptions emphasize different response sets to risk information, depending on cultural priorities such as social justice versus personal freedom. This chapter reports the major psychological research results pertaining to the factors that govern individual risk perception and discusses the psychometric effects due to people's risk perception and the experience of severe stress. The relative importance of the psychometric context variables, the signals pertaining to each health risks and symbolic beliefs are explained.

Hydrological and environmental variables outperform spatial factors in structuring species, trait composition, and beta diversity of pelagic algae.

PubMed

Wu, Naicheng; Qu, Yueming; Guse, Björn; Makarevičiūtė, Kristė; To, Szewing; Riis, Tenna; Fohrer, Nicola

2018-03-01

There has been increasing interest in algae-based bioassessment, particularly, trait-based approaches are increasingly suggested. However, the main drivers, especially the contribution of hydrological variables, of species composition, trait composition, and beta diversity of algae communities are less studied. To link species and trait composition to multiple factors (i.e., hydrological variables, local environmental variables, and spatial factors) that potentially control species occurrence/abundance and to determine their relative roles in shaping species composition, trait composition, and beta diversities of pelagic algae communities, samples were collected from a German lowland catchment, where a well-proven ecohydrological modeling enabled to predict long-term discharges at each sampling site. Both trait and species composition showed significant correlations with hydrological, environmental, and spatial variables, and variation partitioning revealed that the hydrological and local environmental variables outperformed spatial variables. A higher variation of trait composition (57.0%) than species composition (37.5%) could be explained by abiotic factors. Mantel tests showed that both species and trait-based beta diversities were mostly related to hydrological and environmental heterogeneity with hydrological contributing more than environmental variables, while purely spatial impact was less important. Our findings revealed the relative importance of hydrological variables in shaping pelagic algae community and their spatial patterns of beta diversities, emphasizing the need to include hydrological variables in long-term biomonitoring campaigns and biodiversity conservation or restoration. A key implication for biodiversity conservation was that maintaining the instream flow regime and keeping various habitats among rivers are of vital importance. However, further investigations at multispatial and temporal scales are greatly needed.

Habitat characteristics promoting high density and condition of juvenile flatfish at nursery grounds on the west coast of Ireland

NASA Astrophysics Data System (ADS)

De Raedemaecker, F.; Brophy, D.; O'Connor, I.; Comerford, S.

2012-10-01

Coastal zones are essential nursery habitats for most juvenile flatfish species. Understanding the habitat requirements promoting high abundance and growth of juvenile flatfish is important for evaluating nursery habitat quality. The present study aimed to assess nursery ground quality for the most common flatfish species: dab (Limanda limanda) and plaice (Pleuronectes platessa), in Galway Bay, on the west coast of Ireland. Monthly surveys were carried out in the period after peak settlement over two years. Variability in flatfish density and Fulton's K condition was explained in relation to biotic and abiotic habitat characteristics, differing within and between distinct nursery grounds. Dab were concentrated in deeper waters, were negatively associated with shrimp densities and salinity and their abundance showed a decrease from June to September combined with interannual variation. Plaice densities were highly associated with shallower depths and high polychaete and shrimp densities and were negatively related with increased macroalgal cover and organic content. Most of the variability in Fulton's condition was explained by the same set of variables for both species; year and densities of crab and malacostracans. This analysis revealed important ecological mechanisms allowing the co-existence of two flatfish species in nursery grounds. However, high quality nursery grounds for dab and plaice differed and anthropogenic and climatic impacts on flatfish nurseries are likely to have a different impact on plaice and dab populations. Knowledge gained about the quality of nursery habitat for commercially important fish species provides a basis for mapping essential flatfish habitats to inform management plans for coastal areas.

Stressful environments induce novel phenotypic variation: hierarchical reaction norms for sperm performance of a pervasive invader

PubMed Central

Purchase, Craig F; Moreau, Darek T R

2012-01-01

Genetic variation for phenotypic plasticity is ubiquitous and important. However, the scale of such variation including the relative variability present in reaction norms among different hierarchies of biological organization (e.g., individuals, populations, and closely related species) is unknown. Complicating interpretation is a trade-off in environmental scale. As plasticity can only be inferred over the range of environments tested, experiments focusing on fine tuned responses to normal or benign conditions may miss cryptic phenotypic variation expressed under novel or stressful environments. Here, we sought to discern the presence and shape of plasticity in the performance of brown trout sperm as a function of optimal to extremely stressful river pH, and demarcate if the reaction norm varies among genotypes. Our overarching goal was to determine if deteriorating environmental quality increases expressed variation among individuals. A more applied aim was to ascertain whether maintaining sperm performance over a wide pH range could help explain how brown trout are able to invade diverse river systems when transplanted outside of their native range. Individuals differed in their reaction norms of phenotypic expression of an important trait in response to environmental change. Cryptic variation was revealed under stressful conditions, evidenced through increasing among-individual variability. Importantly, data on population averages masked this variability in plasticity. In addition, canalized reaction norms in sperm swimming velocities of many individuals over a very large range in water chemistry may help explain why brown trout are able to colonize a wide variety of habitats. PMID:23145341

Factors significantly related to science achievement of Malaysian middle school students: An analysis of TIMSS 1999 data

NASA Astrophysics Data System (ADS)

Mokshein, Siti Eshah

The importance of science and technology in the global economy has led to growing emphasis on math and science achievement all over the world. In this study, I seek to identify variables at the student-level and school-level that account for the variation in science achievement of the eighth graders in Malaysia. Using the Third International Math and Science Study (TIMSS) 1999 for Malaysia, a series of HLM analysis was performed. Results indicate that (1) variation in overall science achievement is greater between schools than within schools; (2) both the selected student-level and school-level factors are Important in explaining the variation in the eight graders' achievement In science; (3) the selected student-level variables explain about 13% of the variation in students' achievement within schools, but as an aggregate, they account for a much larger proportion of the between-school variance; (4) the selected school-level variables account for about 55% of the variation between schools; (5) within schools, the effects of self-concept In science, awareness of the social implications of science, gender, and home educational resources are significantly related to achievement; (6) the effects of self-concept in science and awareness of social implications of science are significant even after controlling for the effects of SES; (7) between schools, the effects of the mean of home educational resources, mean of parents' education, mean of awareness of the social implications of science, and emphasis on conducting experiments are significantly related to achievement; (8) the effects of SES variables explain about 50% of the variation in the school means achievement; and (9) the effects of emphasis on conducting experiments on achievement are significant even after controlling for the effects of SES. Since it is hard to change the society, it is recommended that efforts to Improve science achievement be focused more at the school-level, concentrating on variables that can be changed. This includes Increasing students' awareness of the social Implications of science and improving students' self-concepts In science, strengthening evaluation systems, and finding ways to compensate for the lack of home educational resources among disadvantaged students. The study further suggests that emphasis be given to proper implementation of science experiments. Besides, the prominent effects of SES variables on the school mean achievement is something worthwhile to be further researched.

Nursing Assistant Burnout and the Cognitively Impaired Elderly.

ERIC Educational Resources Information Center

Novak, Mark; Chappell, Neena L.

1994-01-01

Examined burnout among nursing assistants (n=245). Found that both stressor and appraisal variables influenced feelings of burnout. Stressor variable, frequency of disturbing patient behaviors, best explained feelings of reduced Personal Accomplishment. Appraisal variable, reaction to patient behaviors, best explained Emotional Exhaustion. Found…

The relative importance of physicochemical factors to stream biological condition in urbanizing basins: Evidence from multimodel inference

USGS Publications Warehouse

Carlisle, Daren M.; Bryant, Wade L.

2011-01-01

Many physicochemical factors potentially impair stream ecosystems in urbanizing basins, but few studies have evaluated their relative importance simultaneously, especially in different environmental settings. We used data collected in 25 to 30 streams along a gradient of urbanization in each of 6 metropolitan areas (MAs) to evaluate the relative importance of 11 physicochemical factors on the condition of algal, macroinvertebrate, and fish assemblages. For each assemblage, biological condition was quantified using 2 separate metrics, nonmetric multidimensional scaling ordination site scores and the ratio of observed/expected taxa, both derived in previous studies. Separate linear regression models with 1 or 2 factors as predictors were developed for each MA and assemblage metric. Model parsimony was evaluated based on Akaike’s Information Criterion for small sample size (AICc) and Akaike weights, and variable importance was estimated by summing the Akaike weights across models containing each stressor variable. Few of the factors were strongly correlated (Pearson |r| > 0.7) within MAs. Physicochemical factors explained 17 to 81% of variance in biological condition. Most (92 of 118) of the most plausible models contained 2 predictors, and generally more variance could be explained by the additive effects of 2 factors than by any single factor alone. None of the factors evaluated was universally important for all MAs or biological assemblages. The relative importance of factors varied for different measures of biological condition, biological assemblages, and MA. Our results suggest that the suite of physicochemical factors affecting urban stream ecosystems varies across broad geographic areas, along gradients of urban intensity, and among basins within single MAs.

Virtual water trade patterns in relation to environmental and socioeconomic factors: A case study for Tunisia.

PubMed

Chouchane, Hatem; Krol, Maarten S; Hoekstra, Arjen Y

2018-02-01

Growing water demands put increasing pressure on local water resources, especially in water-short countries. Virtual water trade can play a key role in filling the gap between local demand and supply of water-intensive commodities. This study aims to analyse the dynamics in virtual water trade of Tunisia in relation to environmental and socio-economic factors such as GDP, irrigated land, precipitation, population and water scarcity. The water footprint of crop production is estimated using AquaCrop for six crops over the period 1981-2010. Net virtual water import (NVWI) is quantified at yearly basis. Regression models are used to investigate dynamics in NVWI in relation to the selected factors. The results show that NVWI during the study period for the selected crops is not influenced by blue water scarcity. NVWI correlates in two alternative models to either population and precipitation (model I) or to GDP and irrigated area (model II). The models are better in explaining NVWI of staple crops (wheat, barley, potatoes) than NVWI of cash crops (dates, olives, tomatoes). Using model I, we are able to explain both trends and inter-annual variability for rain-fed crops. Model II performs better for irrigated crops and is able to explain trends significantly; no significant relation is found, however, with variables hypothesized to represent inter-annual variability. Copyright © 2017 Elsevier B.V. All rights reserved.

Thermal barriers constrain microbial elevational range size via climate variability.

PubMed

Wang, Jianjun; Soininen, Janne

2017-08-01

Range size is invariably limited and understanding range size variation is an important objective in ecology. However, microbial range size across geographical gradients remains understudied, especially on mountainsides. Here, the patterns of range size of stream microbes (i.e., bacteria and diatoms) and macroorganisms (i.e., macroinvertebrates) along elevational gradients in Asia and Europe were examined. In bacteria, elevational range size showed non-significant phylogenetic signals. In all taxa, there was a positive relationship between niche breadth and species elevational range size, driven by local environmental and climatic variables. No taxa followed the elevational Rapoport's rule. Climate variability explained the most variation in microbial mean elevational range size, whereas local environmental variables were more important for macroinvertebrates. Seasonal and annual climate variation showed negative effects, while daily climate variation had positive effects on community mean elevational range size for all taxa. The negative correlation between range size and species richness suggests that understanding the drivers of range is key for revealing the processes underlying diversity. The results advance the understanding of microbial species thermal barriers by revealing the importance of seasonal and diurnal climate variation, and highlight that aquatic and terrestrial biota may differ in their response to short- and long-term climate variability. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

The nature of solar brightness variations

NASA Astrophysics Data System (ADS)

Shapiro, A. I.; Solanki, S. K.; Krivova, N. A.; Cameron, R. H.; Yeo, K. L.; Schmutz, W. K.

2017-09-01

Determining the sources of solar brightness variations1,2, often referred to as solar noise3, is important because solar noise limits the detection of solar oscillations3, is one of the drivers of the Earth's climate system4,5 and is a prototype of stellar variability6,7—an important limiting factor for the detection of extrasolar planets. Here, we model the magnetic contribution to solar brightness variability using high-cadence8,9 observations from the Solar Dynamics Observatory (SDO) and the Spectral And Total Irradiance REconstruction (SATIRE)10,11 model. The brightness variations caused by the constantly evolving cellular granulation pattern on the solar surface were computed with the Max Planck Institute for Solar System Research (MPS)/University of Chicago Radiative Magnetohydrodynamics (MURaM)12 code. We found that the surface magnetic field and granulation can together precisely explain solar noise (that is, solar variability excluding oscillations) on timescales from minutes to decades, accounting for all timescales that have so far been resolved or covered by irradiance measurements. We demonstrate that no other sources of variability are required to explain the data. Recent measurements of Sun-like stars by the COnvection ROtation and planetary Transits (CoRoT)13 and Kepler14 missions uncovered brightness variations similar to that of the Sun, but with a much wider variety of patterns15. Our finding that solar brightness variations can be replicated in detail with just two well-known sources will greatly simplify future modelling of existing CoRoT and Kepler as well as anticipated Transiting Exoplanet Survey Satellite16 and PLAnetary Transits and Oscillations of stars (PLATO)17 data.

The Relationship between Social Capital in Hospitals and Physician Job Satisfaction

PubMed Central

Ommen, Oliver; Driller, Elke; Köhler, Thorsten; Kowalski, Christoph; Ernstmann, Nicole; Neumann, Melanie; Steffen, Petra; Pfaff, Holger

2009-01-01

Background Job satisfaction in the hospital is an important predictor for many significant management ratios. Acceptance in professional life or high workload are known as important predictors for job satisfaction. The influence of social capital in hospitals on job satisfaction within the health care system, however, remains to be determined. Thus, this article aimed at analysing the relationship between overall job satisfaction of physicians and social capital in hospitals. Methods The results of this study are based upon questionnaires sent by mail to 454 physicians working in the field of patient care in 4 different German hospitals in 2002. 277 clinicians responded to the poll, for a response rate of 61%. Analysis was performed using three linear regression models with physician overall job satisfaction as the dependent variable and age, gender, professional experience, workload, and social capital as independent variables. Results The first regression model explained nearly 9% of the variance of job satisfaction. Whereas job satisfaction increased slightly with age, gender and professional experience were not identified as significant factors to explain the variance. Setting up a second model with the addition of subjectively-perceived workload to the analysis, the explained variance increased to 18% and job satisfaction decreased significantly with increasing workload. The third model including social capital in hospital explained 36% of the variance with social capital, professional experience and workload as significant factors. Conclusion This analysis demonstrated that the social capital of an organisation, in addition to professional experience and workload, represents a significant predictor of overall job satisfaction of physicians working in the field of patient care. Trust, mutual understanding, shared aims, and ethical values are qualities of social capital that unify members of social networks and communities and enable them to act cooperatively. PMID:19445692

The Importance of Form in Skinner's Analysis of Verbal Behavior and a Further Step

PubMed Central

Vargas, E. A.

2013-01-01

A series of quotes from B. F. Skinner illustrates the importance of form in his analysis of verbal behavior. In that analysis, form plays an important part in contingency control. Form and function complement each other. Function, the array of variables that control a verbal utterance, dictates the meaning of a specified form; form, as stipulated by a verbal community, indicates that meaning. The mediational actions that shape verbal utterances do not necessarily encounter their controlling variables. These are inferred from the form of the verbal utterance. Form carries the burden of implied meaning and underscores the importance of the verbal community in the expression of all the forms of language. Skinner's analysis of verbal behavior and the importance of form within that analysis provides the foundation by which to investigate language. But a further step needs to be undertaken to examine and to explain the abstractions of language as an outcome of action at an aggregate level. PMID:23814376

What are the most crucial soil factors for predicting the distribution of alpine plant species?

NASA Astrophysics Data System (ADS)

Buri, A.; Pinto-Figueroa, E.; Yashiro, E.; Guisan, A.

2017-12-01

Nowadays the use of species distribution models (SDM) is common to predict in space and time the distribution of organisms living in the critical zone. The realized environmental niche concept behind the development of SDM imply that many environmental factors must be accounted for simultaneously to predict species distributions. Climatic and topographic factors are often primary included, whereas soil factors are frequently neglected, mainly due to the paucity of soil information available spatially and temporally. Furthermore, among existing studies, most included soil pH only, or few other soil parameters. In this study we aimed at identifying what are the most crucial soil factors for explaining alpine plant distributions and, among those identified, which ones further improve the predictive power of plant SDMs. To test the relative importance of the soil factors, we performed plant SDMs using as predictors 52 measured soil properties of various types such as organic/inorganic compounds, chemical/physical properties, water related variables, mineral composition or grain size distribution. We added them separately to a standard set of topo-climatic predictors (temperature, slope, solar radiation and topographic position). We used ensemble forecasting techniques combining together several predictive algorithms to model the distribution of 116 plant species over 250 sites in the Swiss Alps. We recorded the variable importance for each model and compared the quality of the models including different soil proprieties (one at a time) as predictors to models having only topo-climatic variables as predictors. Results show that 46% of the soil proprieties tested become the second most important variable, after air temperature, to explain spatial distribution of alpine plants species. Moreover, we also assessed that addition of certain soil factors, such as bulk soil water density, could improve over 80% the quality of some plant species models. We confirm that soil pH remains one of the most important soil factor for predicting plant species distributions, closely followed by water, organic and inorganic carbon related properties. Finally, we were able to extract three main categories of important soil properties for plant species distributions: grain size distribution, acidity and water in the soil.

Climate and Physiography Predict Mercury Concentrations in Game Fish Species in Quebec Lakes Better than Anthropogenic Disturbances.

PubMed

Lucotte, Marc; Paquet, Serge; Moingt, Matthieu

2016-05-01

The fluctuations of mercury levels (Hg) in fish consumed by sport fishers in North-Eastern America depend upon a plethora of interrelated biological and abiological factors. To identify the dominant factors ultimately controlling fish Hg concentrations, we compiled mercury levels (Hg) during the 1976-2010 period in 90 large natural lakes in Quebec (Canada) for two major game species: northern pike (Esox lucius) and walleye (Sander vitreus). Our statistical analysis included 28 geographic information system variables and 15 climatic variables, including sulfate deposition. Higher winter temperatures explained 36% of the variability in higher walleye growth rates, in turn accounting for 54% of the variability in lower Hg concentrations. For northern pike, the dominance of a flat topography in the watershed explained 31% of the variability in lower Hg concentrations. Higher mean annual temperatures explained 27% of the variability in higher pike Hg concentrations. Pelagic versus littoral preferred habitats for walleye and pike respectively could explain the contrasted effect of temperature between the two species. Heavy logging could only explain 2% of the increase in walleye Hg concentrations. The influence of mining on fish Hg concentrations appeared to be masked by climatic effects.

Climate variation explains a third of global crop yield variability

PubMed Central

Ray, Deepak K.; Gerber, James S.; MacDonald, Graham K.; West, Paul C.

2015-01-01

Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. PMID:25609225

Does children's energy intake at one meal influence their intake at subsequent meals? Or do we just think it does?

PubMed

Hanley, James A; Hutcheon, Jennifer A

2010-05-01

It is widely believed that young children are able to adjust their energy intake across successive meals to compensate for higher or lower intakes at a given meal. This conclusion is based on past observations that although children's intake at individual meals is highly variable, total daily intakes are relatively constant. We investigated how much of this reduction in variability could be explained by the statistical phenomenon of the variability of individual components (each meal) always being relatively larger than the variability of their sum (total daily intake), independent of any physiological compensatory mechanism. We calculated, theoretically and by simulation, how variable a child's daily intake would be if there was no correlation between intakes at individual meals. We simulated groups of children with meal/snack intakes and variability in meal/snack intakes based on previously published values. Most importantly, we assumed that there was no correlation between intakes on successive meals. In both approaches, the coefficient of variation of the daily intakes was roughly 15%, considerably less than the 34% for individual meals. Thus, most of the reduction in variability found in past studies was explained without positing strong 'compensation'. Although children's daily energy intakes are indeed considerably less variable than their individual components, this phenomenon was observed even when intakes at each meal were simulated to be totally independent. We conclude that the commonly held belief that young children have a strong physiological compensatory mechanism to adjust intake at one meal based on intake at prior meals is likely to be based on flawed statistical reasoning.

Women's empowerment and domestic violence: the role of sociocultural determinants in maternal and child undernutrition in tribal and rural communities in South India.

PubMed

Sethuraman, Kavita; Lansdown, Richard; Sullivan, Keith

2006-06-01

Moderate malnutrition continues to affect 46% of children under five years of age and 47% of rural women in India. Women's lack of empowerment is believed to be an important factor in the persistent prevalence of malnutrition. In India, women's empowerment often varies by community, with tribes sometimes being the most progressive. To explore the relationship between women's empowerment, maternal nutritional status, and the nutritional status of their children aged 6 to 24 months in rural and tribal communities. This study in rural Karnataka, India, included tribal and rural subjects and used both qualitative and quantitative methods of data collection. Structured interviews with mothers were performed and anthropometric measurements were obtained for 820 mother-child pairs. The data were analyzed by multivariate and logistic regression. Some degree of malnutrition was seen in 83.5% of children and 72.4% of mothers in the sample. Biological variables explained most of the variance in nutritional status, followed by health-care seeking and women's empowerment variables; socioeconomic variables explained the least amount of variance. Women's empowerment variables were significantly associated with child nutrition and explained 5.6% of the variance in the sample. Maternal experience of psychological abuse and sexual coercion increased the risk of malnutrition in mothers and children. Domestic violence was experienced by 34% of mothers in the sample. In addition to the known investments needed to reduce malnutrition, improving women's nutrition, promoting gender equality, empowering women, and ending violence against women could further reduce the prevalence of malnutrition in this segment of the Indian population.

Variation patterns in individual fish responses to chemical stress among estuaries, seasons and genders: the case of the European flounder (Platichthys flesus) in the Bay of Biscay.

PubMed

Laroche, Jean; Gauthier, Olivier; Quiniou, Louis; Devaux, Alain; Bony, Sylvie; Evrard, Estérine; Cachot, Jérôme; Chérel, Yan; Larcher, Thibaut; Riso, Ricardo; Pichereau, Vianney; Devier, Marie Hélène; Budzinski, Hélène

2013-02-01

The objective was to describe and model variation patterns in individual fish responses to contaminants among estuaries, season and gender. Two hundred twenty-seven adult European flounders were collected in two seasons (winter and summer) in four estuaries along the Bay of Biscay (South West France), focusing on a pristine system (the Ster), vs. three estuaries displaying contrasted levels of contaminants (the Vilaine, Loire and Gironde). Twenty-three variables were measured by fish, considering the load of contaminants (liver metals, liver and muscle persistent organic pollutants, muscle polycyclic aromatic hydrocarbons); the gene expression (Cyt C oxydase, ATPase, BHMT, Cyt P450 1A1, ferritin); the blood genotoxicity (Comet test); and liver histology (foci of cellular alteration-tumour, steatosis, inflammation, abnormal glycogen storage). Canonical redundancy analysis (RDA) was used to model these variables using gender, season and estuary of origin as explanatory variables. The results underlined the homogeneity of fish responses within the pristine site (Ster) and more important seasonal variability within the three contaminated systems. The complete model RDA was significant and explained 35 % of total variance. Estuary and season respectively explained 30 and 5 % of the total independent variation components, whilst gender was not a significant factor. The first axis of the RDA explains nearly 27 % of the total variance and mostly represents a gradient of contamination. The links between the load of contaminants, the expression of several genes and the biomarkers were analysed considering different levels of chemical stress and a possible multi-stress, particularly in the Vilaine estuary.

Future hotspots of increasing temperature variability in tropical countries

NASA Astrophysics Data System (ADS)

Bathiany, S.; Dakos, V.; Scheffer, M.; Lenton, T. M.

2017-12-01

Resolving how climate variability will change in future is crucial to determining how challenging it will be for societies and ecosystems to adapt to climate change. We show that the largest increases in temperature variability - that are robust between state-of-the art climate models - are concentrated in tropical countries. On average, temperature variability increases by 15% per degree of global warming in Amazonia and Southern Africa during austral summer, and by up to 10% °C-1 in the Sahel, India and South East Asia. Southern hemisphere changes can be explained by drying soils, whereas shifts in atmospheric structure play a more important role in the Northern hemisphere. These robust regional changes in variability are associated with monthly timescale events, whereas uncertain changes in inter-annual modes of variability make the response of global temperature variability uncertain. Our results suggest that regional changes in temperature variability will create new inequalities in climate change impacts between rich and poor nations.

The Importance of Distance to Resources in the Spatial Modelling of Bat Foraging Habitat

PubMed Central

Rainho, Ana; Palmeirim, Jorge M.

2011-01-01

Many bats are threatened by habitat loss, but opportunities to manage their habitats are now increasing. Success of management depends greatly on the capacity to determine where and how interventions should take place, so models predicting how animals use landscapes are important to plan them. Bats are quite distinctive in the way they use space for foraging because (i) most are colonial central-place foragers and (ii) exploit scattered and distant resources, although this increases flying costs. To evaluate how important distances to resources are in modelling foraging bat habitat suitability, we radio-tracked two cave-dwelling species of conservation concern (Rhinolophus mehelyi and Miniopterus schreibersii) in a Mediterranean landscape. Habitat and distance variables were evaluated using logistic regression modelling. Distance variables greatly increased the performance of models, and distance to roost and to drinking water could alone explain 86 and 73% of the use of space by M. schreibersii and R. mehelyi, respectively. Land-cover and soil productivity also provided a significant contribution to the final models. Habitat suitability maps generated by models with and without distance variables differed substantially, confirming the shortcomings of maps generated without distance variables. Indeed, areas shown as highly suitable in maps generated without distance variables proved poorly suitable when distance variables were also considered. We concluded that distances to resources are determinant in the way bats forage across the landscape, and that using distance variables substantially improves the accuracy of suitability maps generated with spatially explicit models. Consequently, modelling with these variables is important to guide habitat management in bats and similarly mobile animals, particularly if they are central-place foragers or depend on spatially scarce resources. PMID:21547076

Population size influences amphibian detection probability: implications for biodiversity monitoring programs.

PubMed

Tanadini, Lorenzo G; Schmidt, Benedikt R

2011-01-01

Monitoring is an integral part of species conservation. Monitoring programs must take imperfect detection of species into account in order to be reliable. Theory suggests that detection probability may be determined by population size but this relationship has not yet been assessed empirically. Population size is particularly important because it may induce heterogeneity in detection probability and thereby cause bias in estimates of biodiversity. We used a site occupancy model to analyse data from a volunteer-based amphibian monitoring program to assess how well different variables explain variation in detection probability. An index to population size best explained detection probabilities for four out of six species (to avoid circular reasoning, we used the count of individuals at a previous site visit as an index to current population size). The relationship between the population index and detection probability was positive. Commonly used weather variables best explained detection probabilities for two out of six species. Estimates of site occupancy probabilities differed depending on whether the population index was or was not used to model detection probability. The relationship between the population index and detectability has implications for the design of monitoring and species conservation. Most importantly, because many small populations are likely to be overlooked, monitoring programs should be designed in such a way that small populations are not overlooked. The results also imply that methods cannot be standardized in such a way that detection probabilities are constant. As we have shown here, one can easily account for variation in population size in the analysis of data from long-term monitoring programs by using counts of individuals from surveys at the same site in previous years. Accounting for variation in population size is important because it can affect the results of long-term monitoring programs and ultimately the conservation of imperiled species.

Individual Movement Variability Magnitudes Are Explained by Cortical Neural Variability.

PubMed

Haar, Shlomi; Donchin, Opher; Dinstein, Ilan

2017-09-13

Humans exhibit considerable motor variability even across trivial reaching movements. This variability can be separated into specific kinematic components such as extent and direction that are thought to be governed by distinct neural processes. Here, we report that individual subjects (males and females) exhibit different magnitudes of kinematic variability, which are consistent (within individual) across movements to different targets and regardless of which arm (right or left) was used to perform the movements. Simultaneous fMRI recordings revealed that the same subjects also exhibited different magnitudes of fMRI variability across movements in a variety of motor system areas. These fMRI variability magnitudes were also consistent across movements to different targets when performed with either arm. Cortical fMRI variability in the posterior-parietal cortex of individual subjects explained their movement-extent variability. This relationship was apparent only in posterior-parietal cortex and not in other motor system areas, thereby suggesting that individuals with more variable movement preparation exhibit larger kinematic variability. We therefore propose that neural and kinematic variability are reliable and interrelated individual characteristics that may predispose individual subjects to exhibit distinct motor capabilities. SIGNIFICANCE STATEMENT Neural activity and movement kinematics are remarkably variable. Although intertrial variability is rarely studied, here, we demonstrate that individual human subjects exhibit distinct magnitudes of neural and kinematic variability that are reproducible across movements to different targets and when performing these movements with either arm. Furthermore, when examining the relationship between cortical variability and movement variability, we find that cortical fMRI variability in parietal cortex of individual subjects explained their movement extent variability. This enabled us to explain why some subjects performed more variable movements than others based on their cortical variability magnitudes. Copyright © 2017 the authors 0270-6474/17/379076-10$15.00/0.

Uncertainty Reduction using Bayesian Inference and Sensitivity Analysis: A Sequential Approach to the NASA Langley Uncertainty Quantification Challenge

NASA Technical Reports Server (NTRS)

Sankararaman, Shankar

2016-01-01

This paper presents a computational framework for uncertainty characterization and propagation, and sensitivity analysis under the presence of aleatory and epistemic un- certainty, and develops a rigorous methodology for efficient refinement of epistemic un- certainty by identifying important epistemic variables that significantly affect the overall performance of an engineering system. The proposed methodology is illustrated using the NASA Langley Uncertainty Quantification Challenge (NASA-LUQC) problem that deals with uncertainty analysis of a generic transport model (GTM). First, Bayesian inference is used to infer subsystem-level epistemic quantities using the subsystem-level model and corresponding data. Second, tools of variance-based global sensitivity analysis are used to identify four important epistemic variables (this limitation specified in the NASA-LUQC is reflective of practical engineering situations where not all epistemic variables can be refined due to time/budget constraints) that significantly affect system-level performance. The most significant contribution of this paper is the development of the sequential refine- ment methodology, where epistemic variables for refinement are not identified all-at-once. Instead, only one variable is first identified, and then, Bayesian inference and global sensi- tivity calculations are repeated to identify the next important variable. This procedure is continued until all 4 variables are identified and the refinement in the system-level perfor- mance is computed. The advantages of the proposed sequential refinement methodology over the all-at-once uncertainty refinement approach are explained, and then applied to the NASA Langley Uncertainty Quantification Challenge problem.

When a gold standard isn't so golden: Lack of prediction of subjective sleep quality from sleep polysomnography.

PubMed

Kaplan, Katherine A; Hirshman, Jason; Hernandez, Beatriz; Stefanick, Marcia L; Hoffman, Andrew R; Redline, Susan; Ancoli-Israel, Sonia; Stone, Katie; Friedman, Leah; Zeitzer, Jamie M

2017-02-01

Reports of subjective sleep quality are frequently collected in research and clinical practice. It is unclear, however, how well polysomnographic measures of sleep correlate with subjective reports of prior-night sleep quality in elderly men and women. Furthermore, the relative importance of various polysomnographic, demographic and clinical characteristics in predicting subjective sleep quality is not known. We sought to determine the correlates of subjective sleep quality in older adults using more recently developed machine learning algorithms that are suitable for selecting and ranking important variables. Community-dwelling older men (n=1024) and women (n=459), a subset of those participating in the Osteoporotic Fractures in Men study and the Study of Osteoporotic Fractures study, respectively, completed a single night of at-home polysomnographic recording of sleep followed by a set of morning questions concerning the prior night's sleep quality. Questionnaires concerning demographics and psychological characteristics were also collected prior to the overnight recording and entered into multivariable models. Two machine learning algorithms, lasso penalized regression and random forests, determined variable selection and the ordering of variable importance separately for men and women. Thirty-eight sleep, demographic and clinical correlates of sleep quality were considered. Together, these multivariable models explained only 11-17% of the variance in predicting subjective sleep quality. Objective sleep efficiency emerged as the strongest correlate of subjective sleep quality across all models, and across both sexes. Greater total sleep time and sleep stage transitions were also significant objective correlates of subjective sleep quality. The amount of slow wave sleep obtained was not determined to be important. Overall, the commonly obtained measures of polysomnographically-defined sleep contributed little to subjective ratings of prior-night sleep quality. Though they explained relatively little of the variance, sleep efficiency, total sleep time and sleep stage transitions were among the most important objective correlates. Published by Elsevier B.V.

When a gold standard isn't so golden: Lack of prediction of subjective sleep quality from sleep polysomnography

PubMed Central

Kaplan, Katherine A.; Hirshman, Jason; Hernandez, Beatriz; Stefanick, Marcia L.; Hoffman, Andrew R.; Redline, Susan; Ancoli-Israel, Sonia; Stone, Katie; Friedman, Leah; Zeitzer, Jamie M.

2016-01-01

Background Reports of subjective sleep quality are frequently collected in research and clinical practice. It is unclear, however, how well polysomnographic measures of sleep correlate with subjective reports of prior-night sleep quality in elderly men and women. Furthermore, the relative importance of various polysomnographic, demographic and clinical characteristics in predicting subjective sleep quality is not known. We sought to determine the correlates of subjective sleep quality in in older adults using more recently developed machine learning algorithms that are suitable for selecting and ranking important variables. Methods Community-dwelling older men (n=1024) and women (n=459), a subset of those participating in the Osteoporotic Fractures in Men study and the Study of Osteoporotic Fractures study, respectively, completed a single night of at-home polysomnographic recording of sleep followed by a set of morning questions concerning the prior night's sleep quality. Questionnaires concerning demographics and psychological characteristics were also collected prior to the overnight recording and entered into multivariable models. Two machine learning algorithms, lasso penalized regression and random forests, determined variable selection and the ordering of variable importance separately for men and women. Results Thirty-eight sleep, demographic and clinical correlates of sleep quality were considered. Together, these multivariable models explained only 11-17% of the variance in predicting subjective sleep quality. Objective sleep efficiency emerged as the strongest correlate of subjective sleep quality across all models, and across both sexes. Greater total sleep time and sleep stage transitions were also significant objective correlates of subjective sleep quality. The amount of slow wave sleep obtained was not determined to be important. Conclusions Overall, the commonly obtained measures of polysomnographically-defined sleep contributed little to subjective ratings of prior-night sleep quality. Though they explained relatively little of the variance, sleep efficiency, total sleep time and sleep stage transitions were among the most important objective correlates. PMID:27889439

Effects of biotic and abiotic indices on long term soil moisture data in a grassland biodiversity experiment

NASA Astrophysics Data System (ADS)

Fischer, Christine; Hohenbrink, Tobias; Leimer, Sophia; Roscher, Christiane; Ravenek, Janneke; de Kroon, Hans; Kreutziger, Yvonne; Wirth, Christian; Eisenhauer, Nico; Gleixner, Gerd; Weigelt, Alexandra; Mommer, Liesje; Beßler, Holger; Schröder, Boris; Hildebrandt, Anke

2015-04-01

Soil moisture is the dynamic link between climate, soil and vegetation and the dynamics and variation are affected by several often interrelated factors such as soil texture, soil structural parameters (soil organic carbon) and vegetation parameters (belowground- and aboveground biomass). For the characterization and estimation of soil moisture and its variability and the resulting water fluxes and solute transports, the knowledge of the relative importance of these factors is of major challenge for hydrology and bioclimatology. Because of the heterogeneity of these factors, soil moisture varies strongly over time and space. Our objective was to assess the spatio-temporal variability of soil moisture and factors which could explain that variability, like soil properties and vegetation cover, in in a long term biodiversity experiment (Jena Experiment). The Jena Experiment consist 86 plots on which plant species richness (0, 1, 2, 4, 8, 16, and 60) and functional groups (legumes, grasses, tall herbs, and small herbs) were manipulated in a factorial design Soil moisture measurements were performed weekly April to September 2003-2005 and 2008-2013 using Delta T theta probe. Measurements were integrated to three depth intervals: 0.0 - 0.20, 0.20 - 0.40 and 0.40 - 0.70 m. We analyze the spatio-temporal patterns of soil water content on (i) the normalized time series and (ii) the first components obtained from a principal component analysis (PCA). Both were correlated with the design variables of the Jena Experiment (plant species richness and plant functional groups) and other influencing factors such as soil texture, soil structural variables and vegetation parameters. For the time stability of soil water content, the analysis showed that plots containing grasses was consistently drier than average at the soil surface in all observed years while plots containing legumes comparatively moister, but only up to the year 2008. In 0.40 - 0.70 m soil deep plots presence of small herbs led to higher than average soil moisture in some years (2008, 2012, 2013). Interestingly, plant species richness led to moister than average subsoil at the beginning of the experiment (2003 and 2004), which changed to lower than average up to the year 2010 in all depths. There was no effect of species diversity in the years since 2010, although species diversity generally increases leaf area index and aboveground biomass. The first component from the PCA analysis described the mean behavior in time of all soil moisture time series. The second component reflected the impact of soil depth. The first two components explained 76% of the data set total variance. The third component is linked to plant species richness and explained about 4 % of the total variance of soil moisture data. The fourth component, which explained 2.4 %, showed a high correlation to soil texture. Within this study we investigate the dominant factors controlling spatio-temporal patterns of soil moisture at several soil depths. Although climate and soil depths were the most important drivers, other factors like plant species richness and soil texture affected the temporal variation while certain plant functional groups were important for the spatial variability.

Cetacean distributions relative to ocean processes in the northern California Current System

NASA Astrophysics Data System (ADS)

Tynan, Cynthia T.; Ainley, David G.; Barth, John A.; Cowles, Timothy J.; Pierce, Stephen D.; Spear, Larry B.

2005-01-01

Associations between cetacean distributions, oceanographic features, and bioacoustic backscatter were examined during two process cruises in the northern California Current System (CCS) during late spring and summer 2000. Line-transect surveys of cetaceans were conducted across the shelf and slope, out to 150 km offshore from Newport, Oregon (44.6°N) to Crescent City, California (41.9°N), in conjunction with multidisciplinary mesoscale and fine-scale surveys of ocean and ecosystem structure. Occurrence patterns (presence/absence) of cetaceans were compared with hydrographic and ecological variables (e.g., sea surface salinity, sea surface temperature, thermocline depth, halocline depth, chlorophyll maximum, distance to the center of the equatorward jet, distance to the shoreward edge of the upwelling front, and acoustic backscatter at 38, 120, 200 and 420 kHz) derived from a towed, undulating array and a bioacoustic system. Using a multiple logistic regression model, 60.2% and 94.4% of the variation in occurrence patterns of humpback whales Megaptera novaeangliae during late spring and summer, respectively, were explained. Sea surface temperature, depth, and distance to the alongshore upwelling front were the most important environmental variables during June, when humpbacks occurred over the slope (200-2000 m). During August, when humpbacks concentrated over a submarine bank (Heceta Bank) and off Cape Blanco, sea surface salinity was the most important variable, followed by latitude and depth. Humpbacks did not occur in the lowest salinity water of the Columbia River plume. For harbor porpoise Phocoena phocoena, the model explained 79.2% and 70.1% of the variation in their occurrence patterns during June and August, respectively. During spring, latitude, sea surface salinity, and thermocline gradient were the most important predictors. During summer, latitude and distance to the inshore edge of the upwelling front were the most important variables. Typically a coastal species, harbor porpoises extended their distribution farther offshore at Heceta Bank and at Cape Blanco, where they were associated with the higher chlorophyll concentrations in these regions. Pacific white-sided dolphin Lagenorhynchus obliquidens was the most numerous small cetacean in early June, but was rare during August. The model explained 44.5% of the variation in their occurrence pattern, which was best described by distance to the upwelling front and acoustic backscatter at 38 kHz. The model of the occurrence pattern of Dall's porpoise Phocoenoides dalli was more successful when mesoscale variability in the CCS was higher during summer. Thus, the responses of cetaceans to biophysical features and upwelling processes in the northern CCS were both seasonally and spatially specific. Heceta Bank and associated flow-topography interactions were very important to a cascade of trophic dynamics that ultimately influenced the distribution of foraging cetaceans. The higher productivity associated with upwelling near Cape Blanco also had a strong influence on the distribution of cetaceans.

Are hotspots always hotspots? The relationship between diversity, resource and ecosystem functions in the Arctic.

PubMed

Link, Heike; Piepenburg, Dieter; Archambault, Philippe

2013-01-01

The diversity-ecosystem function relationship is an important topic in ecology but has not received much attention in Arctic environments, and has rarely been tested for its stability in time. We studied the temporal variability of benthic ecosystem functioning at hotspots (sites with high benthic boundary fluxes) and coldspots (sites with lower fluxes) across two years in the Canadian Arctic. Benthic remineralisation function was measured as fluxes of oxygen, silicic acid, phosphate, nitrate and nitrite at the sediment-water interface. In addition we determined sediment pigment concentration and taxonomic and functional macrobenthic diversity. To separate temporal from spatial variability, we sampled the same nine sites from the Mackenzie Shelf to Baffin Bay during the same season (summer or fall) in 2008 and 2009. We observed that temporal variability of benthic remineralisation function at hotspots is higher than at coldspots and that taxonomic and functional macrobenthic diversity did not change significantly between years. Temporal variability of food availability (i.e., sediment surface pigment concentration) seemed higher at coldspot than at hotspot areas. Sediment chlorophyll a (Chl a) concentration, taxonomic richness, total abundance, water depth and abundance of the largest gallery-burrowing polychaete Lumbrineristetraura together explained 42% of the total variation in fluxes. Food supply proxies (i.e., sediment Chl a and depth) split hot- from coldspot stations and explained variation on the axis of temporal variability, and macrofaunal community parameters explained variation mostly along the axis separating eastern from western sites with hot- or coldspot regimes. We conclude that variability in benthic remineralisation function, food supply and diversity will react to climate change on different time scales, and that their interactive effects may hide the detection of progressive change, particularly at hotspots. Time-series of benthic functions and its related parameters should be conducted at both hot- and coldspots to produce reliable predictive models.

Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales

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

Wu, Jin; Guan, Kaiyu; Hayek, Matthew

Gross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model wasmore » able to explain most of the variability in GEP at hourly (R 2 = 0.77) to interannual (R 2 = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental limitations to tropical forest photosynthesis. For example, we found that biotically regulated canopy photosynthetic light-use efficiency (associated with leaf phenology) increased with sunlight during dry seasons (consistent with light but not water limitation of canopy development) but that realized GEP was nonetheless lower relative to its potential efficiency during dry than wet seasons (consistent with water limitation of photosynthesis in given assemblages of leaves). Lastly, this work highlights the importance of accounting for differential regulation of GEP at different timescales and of identifying the underlying feedbacks and adaptive mechanisms.« less

Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales

DOE PAGES

Wu, Jin; Guan, Kaiyu; Hayek, Matthew; ...

2016-09-19

Gross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model wasmore » able to explain most of the variability in GEP at hourly (R 2 = 0.77) to interannual (R 2 = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental limitations to tropical forest photosynthesis. For example, we found that biotically regulated canopy photosynthetic light-use efficiency (associated with leaf phenology) increased with sunlight during dry seasons (consistent with light but not water limitation of canopy development) but that realized GEP was nonetheless lower relative to its potential efficiency during dry than wet seasons (consistent with water limitation of photosynthesis in given assemblages of leaves). Lastly, this work highlights the importance of accounting for differential regulation of GEP at different timescales and of identifying the underlying feedbacks and adaptive mechanisms.« less

Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales.

PubMed

Wu, Jin; Guan, Kaiyu; Hayek, Matthew; Restrepo-Coupe, Natalia; Wiedemann, Kenia T; Xu, Xiangtao; Wehr, Richard; Christoffersen, Bradley O; Miao, Guofang; da Silva, Rodrigo; de Araujo, Alessandro C; Oliviera, Raimundo C; Camargo, Plinio B; Monson, Russell K; Huete, Alfredo R; Saleska, Scott R

2017-03-01

Gross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model was able to explain most of the variability in GEP at hourly (R 2  = 0.77) to interannual (R 2  = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental limitations to tropical forest photosynthesis. For example, we found that biotically regulated canopy photosynthetic light-use efficiency (associated with leaf phenology) increased with sunlight during dry seasons (consistent with light but not water limitation of canopy development) but that realized GEP was nonetheless lower relative to its potential efficiency during dry than wet seasons (consistent with water limitation of photosynthesis in given assemblages of leaves). This work highlights the importance of accounting for differential regulation of GEP at different timescales and of identifying the underlying feedbacks and adaptive mechanisms. © 2016 John Wiley & Sons Ltd.

Local-scale drivers of tree survival in a temperate forest.

PubMed

Wang, Xugao; Comita, Liza S; Hao, Zhanqing; Davies, Stuart J; Ye, Ji; Lin, Fei; Yuan, Zuoqiang

2012-01-01

Tree survival plays a central role in forest ecosystems. Although many factors such as tree size, abiotic and biotic neighborhoods have been proposed as being important in explaining patterns of tree survival, their contributions are still subject to debate. We used generalized linear mixed models to examine the relative importance of tree size, local abiotic conditions and the density and identity of neighbors on tree survival in an old-growth temperate forest in northeastern China at three levels (community, guild and species). Tree size and both abiotic and biotic neighborhood variables influenced tree survival under current forest conditions, but their relative importance varied dramatically within and among the community, guild and species levels. Of the variables tested, tree size was typically the most important predictor of tree survival, followed by biotic and then abiotic variables. The effect of tree size on survival varied from strongly positive for small trees (1-20 cm dbh) and medium trees (20-40 cm dbh), to slightly negative for large trees (>40 cm dbh). Among the biotic factors, we found strong evidence for negative density and frequency dependence in this temperate forest, as indicated by negative effects of both total basal area of neighbors and the frequency of conspecific neighbors. Among the abiotic factors tested, soil nutrients tended to be more important in affecting tree survival than topographic variables. Abiotic factors generally influenced survival for species with relatively high abundance, for individuals in smaller size classes and for shade-tolerant species. Our study demonstrates that the relative importance of variables driving patterns of tree survival differs greatly among size classes, species guilds and abundance classes in temperate forest, which can further understanding of forest dynamics and offer important insights into forest management.

Local-Scale Drivers of Tree Survival in a Temperate Forest

PubMed Central

Wang, Xugao; Comita, Liza S.; Hao, Zhanqing; Davies, Stuart J.; Ye, Ji; Lin, Fei; Yuan, Zuoqiang

2012-01-01

Tree survival plays a central role in forest ecosystems. Although many factors such as tree size, abiotic and biotic neighborhoods have been proposed as being important in explaining patterns of tree survival, their contributions are still subject to debate. We used generalized linear mixed models to examine the relative importance of tree size, local abiotic conditions and the density and identity of neighbors on tree survival in an old-growth temperate forest in northeastern China at three levels (community, guild and species). Tree size and both abiotic and biotic neighborhood variables influenced tree survival under current forest conditions, but their relative importance varied dramatically within and among the community, guild and species levels. Of the variables tested, tree size was typically the most important predictor of tree survival, followed by biotic and then abiotic variables. The effect of tree size on survival varied from strongly positive for small trees (1–20 cm dbh) and medium trees (20–40 cm dbh), to slightly negative for large trees (>40 cm dbh). Among the biotic factors, we found strong evidence for negative density and frequency dependence in this temperate forest, as indicated by negative effects of both total basal area of neighbors and the frequency of conspecific neighbors. Among the abiotic factors tested, soil nutrients tended to be more important in affecting tree survival than topographic variables. Abiotic factors generally influenced survival for species with relatively high abundance, for individuals in smaller size classes and for shade-tolerant species. Our study demonstrates that the relative importance of variables driving patterns of tree survival differs greatly among size classes, species guilds and abundance classes in temperate forest, which can further understanding of forest dynamics and offer important insights into forest management. PMID:22347996

Applying the Expectancy-Value Model to understand health values.

PubMed

Zhang, Xu-Hao; Xie, Feng; Wee, Hwee-Lin; Thumboo, Julian; Li, Shu-Chuen

2008-03-01

Expectancy-Value Model (EVM) is the most structured model in psychology to predict attitudes by measuring attitudinal attributes (AAs) and relevant external variables. Because health value could be categorized as attitude, we aimed to apply EVM to explore its usefulness in explaining variances in health values and investigate underlying factors. Focus group discussion was carried out to identify the most common and significant AAs toward 5 different health states (coded as 11111, 11121, 21221, 32323, and 33333 in EuroQol Five-Dimension (EQ-5D) descriptive system). AAs were measured in a sum of multiplications of subjective probability (expectancy) and perceived value of attributes with 7-point Likert scales. Health values were measured using visual analog scales (VAS, range 0-1). External variables (age, sex, ethnicity, education, housing, marital status, and concurrent chronic diseases) were also incorporated into survey questionnaire distributed by convenience sampling among eligible respondents. Univariate analyses were used to identify external variables causing significant differences in VAS. Multiple linear regression model (MLR) and hierarchical regression model were used to investigate the explanatory power of AAs and possible significant external variable(s) separately or in combination, for each individual health state and a mixed scenario of five states, respectively. Four AAs were identified, namely, "worsening your quality of life in terms of health" (WQoL), "adding a burden to your family" (BTF), "making you less independent" (MLI) and "unable to work or study" (UWS). Data were analyzed based on 232 respondents (mean [SD] age: 27.7 [15.07] years, 49.1% female). Health values varied significantly across 5 health states, ranging from 0.12 (33333) to 0.97 (11111). With no significant external variables identified, EVM explained up to 62% of the variances in health values across 5 health states. The explanatory power of 4 AAs were found to be between 13% and 28% in separate MLR models (P < 0.05). When data were analyzed for each health state, variances in health values became small and explanatory power of EVM was reduced to a range between 8% and 23%. EVM was useful in explaining variances of health values and predicting important factors. Its power to explain small variances might be restricted due to limitations of 7-point Likert scale to measure AAs accurately. With further improvement and validation of a compatible continuous scale for more accurate measurement, EVM is expected to explain health values to a larger extent.

Explaining Racial Disparities in Child Asthma Readmission Using a Causal Inference Approach

PubMed Central

Beck, Andrew F.; Huang, Bin; Auger, Katherine A.; Ryan, Patrick H.; Chen, Chen; Kahn, Robert S.

2017-01-01

IMPORTANCE Childhood asthma is characterized by disparities in the experience of morbidity, including the risk for readmission to the hospital after an initial hospitalization. African American children have been shown to have more than 2 times the hazard of readmission when compared with their white counterparts. OBJECTIVE To explain why African American children are at greater risk for asthma-related readmissions than white children. DESIGN, SETTING, AND PARTICIPANTS This study was completed as part of the Greater Cincinnati Asthma Risks Study, a population-based, prospective, observational cohort. From August 2010 to October 2011, it enrolled 695 children, aged 1 to 16 years, admitted for asthma or wheezing who identified as African American (n = 441) or white (n = 254) in an inpatient setting of an urban, tertiary care children’s hospital. MAIN OUTCOMES AND MEASURES The main outcome was time to asthma-related readmission and race was the predictor. Biologic, environmental, disease management, access, and socioeconomic hardship variables were measured; their roles in understanding racial readmission disparities were conceptualized using a directed acyclic graphic. Inverse probability of treatment weighting balanced African American and white children with respect to key measured variables. Racial differences in readmission hazard were assessed using weighted Cox proportional hazards regression and Kaplan-Meier curves. RESULTS The sample was 65% male (n = 450), and the median age was 5.4 years. African American children were 2.26 times more likely to be readmitted than white children (95% CI, 1.56–3.26). African American children significantly differed with respect to nearly every measured biologic, environmental, disease management, access, and socioeconomic hardship variable. Socioeconomic hardship variables explained 53% of the observed disparity (hazard ratio, 1.47; 95% CI, 1.05–2.05). The addition of biologic, environmental, disease management, and access variables resulted in 80% of the readmission disparity being explained. The difference between African American and white children with respect to readmission hazard no longer reached the level of significance (hazard ratio, 1.18; 95% CI, 0.87–1.60; Cox P = .30 and log-rank P = .39). CONCLUSIONS AND RELEVANCE A total of 80% of the observed readmission disparity between African American and white children could be explained after statistically balancing available biologic, environmental, disease management, access to care, and socioeconomic and hardship variables across racial groups. Such a comprehensive, well-framed approach to exposures that are associated with morbidity is critical as we attempt to better understand and lessen persistent child asthma disparities. PMID:27182793

European Wintertime Windstorms and its Links to Large-Scale Variability Modes

NASA Astrophysics Data System (ADS)

Befort, D. J.; Wild, S.; Walz, M. A.; Knight, J. R.; Lockwood, J. F.; Thornton, H. E.; Hermanson, L.; Bett, P.; Weisheimer, A.; Leckebusch, G. C.

2017-12-01

Winter storms associated with extreme wind speeds and heavy precipitation are the most costly natural hazard in several European countries. Improved understanding and seasonal forecast skill of winter storms will thus help society, policy-makers and (re-) insurance industry to be better prepared for such events. We firstly assess the ability to represent extra-tropical windstorms over the Northern Hemisphere of three seasonal forecast ensemble suites: ECMWF System3, ECMWF System4 and GloSea5. Our results show significant skill for inter-annual variability of windstorm frequency over parts of Europe in two of these forecast suites (ECMWF-S4 and GloSea5) indicating the potential use of current seasonal forecast systems. In a regression model we further derive windstorm variability using the forecasted NAO from the seasonal model suites thus estimating the suitability of the NAO as the only predictor. We find that the NAO as the main large-scale mode over Europe can explain some of the achieved skill and is therefore an important source of variability in the seasonal models. However, our results show that the regression model fails to reproduce the skill level of the directly forecast windstorm frequency over large areas of central Europe. This suggests that the seasonal models also capture other sources of variability/predictability of windstorms than the NAO. In order to investigate which other large-scale variability modes steer the interannual variability of windstorms we develop a statistical model using a Poisson GLM. We find that the Scandinavian Pattern (SCA) in fact explains a larger amount of variability for Central Europe during the 20th century than the NAO. This statistical model is able to skilfully reproduce the interannual variability of windstorm frequency especially for the British Isles and Central Europe with correlations up to 0.8.

Ocean carbon and heat variability in an Earth System Model

NASA Astrophysics Data System (ADS)

Thomas, J. L.; Waugh, D.; Gnanadesikan, A.

2016-12-01

Ocean carbon and heat content are very important for regulating global climate. Furthermore, due to lack of observations and dependence on parameterizations, there has been little consensus in the modeling community on the magnitude of realistic ocean carbon and heat content variability, particularly in the Southern Ocean. We assess the differences between global oceanic heat and carbon content variability in GFDL ESM2Mc using a 500-year, pre-industrial control simulation. The global carbon and heat content are directly out of phase with each other; however, in the Southern Ocean the heat and carbon content are in phase. The global heat mutli-decadal variability is primarily explained by variability in the tropics and mid-latitudes, while the variability in global carbon content is primarily explained by Southern Ocean variability. In order to test the robustness of this relationship, we use three additional pre-industrial control simulations using different mesoscale mixing parameterizations. Three pre-industrial control simulations are conducted with the along-isopycnal diffusion coefficient (Aredi) set to constant values of 400, 800 (control) and 2400 m2 s-1. These values for Aredi are within the range of parameter settings commonly used in modeling groups. Finally, one pre-industrial control simulation is conducted where the minimum in the Gent-McWilliams parameterization closure scheme (AGM) increased to 600 m2 s-1. We find that the different simulations have very different multi-decadal variability, especially in the Weddell Sea where the characteristics of deep convection are drastically changed. While the temporal frequency and amplitude global heat and carbon content changes significantly, the overall spatial pattern of variability remains unchanged between the simulations.

Sociopolitical and economic elements to explain the environmental performance of countries.

PubMed

Almeida, Thiago Alexandre das Neves; García-Sánchez, Isabel-María

2017-01-01

The present research explains environmental performance using an ecological composite index as the dependent variable and focusing on two national dimensions: sociopolitical characteristics and economics. Environmental performance is measured using the Composite Index of Environmental Performance (CIEP) indicator proposed by García-Sánchez et al. (2015). The first model performs a factor analysis to aggregate the variables according to each analyzed dimension. In the second model, the estimation is run using only single variables. Both models are estimated using generalized least square estimation (GLS) using panel data from 152 countries and 6 years. The results show that sociopolitical factors and international trade have a positive effect on environmental performance. When the variables are separately analyzed, democracy and social policy have a positive effect on environmental performance while transport, infrastructure, consumption of goods, and tourism have a negative effect. Further observation is that the trade-off between importing and exporting countries overshadows the pollution caused by production. It was also observed that infrastructure has a negative coefficient for developing countries and positive for developed countries. The best performances are in the democratic and richer countries that are located in Europe, while the worst environmental performance is by the nondemocratic and the poorest countries, which are on the African continent.

[Determining factors of job-satisfaction: presence of work-family conflict in a sample of Italian nurses].

PubMed

Cortese, C G; Ghislieri, Chiara; Colombo, Lara

2008-01-01

Organization research has shown increasing interest in the dynamics of work-family conflict (w.f.c.). The NEXT study highlights that w.f.c. significantly influences satisfaction for one's job and the decision to quit the nursing profession. This study analyzes w.f.c. in a sample of Italian nurses, with the aim of examining the main differences in relation to personal variables, and understanding the degree to which w.f.c. explains job satisfaction. A self-reporting questionnaire was administered to 325 nurses in different hospitals of Northern Italy. Descriptive, reliability and Anova data analysis was performed. The relationships between variables were analyzed through correlations (Pearson's r); the role of w.f.c. in explaining job satisfaction was estimated via multiple regression. W.f.c. appeared to be more critical in subjects who had care responsibilities and in those who had more demanding work assignments. W.f.c. contributed to explaining job satisfaction, even if it was not its principal determining factor. This area of research appears to be important in that it leads to a better comprehension of the dynamics involved in work satisfaction and can suggest possible initiatives for support and development.

Environmental variability and acoustic signals: a multi-level approach in songbirds.

PubMed

Medina, Iliana; Francis, Clinton D

2012-12-23

Among songbirds, growing evidence suggests that acoustic adaptation of song traits occurs in response to habitat features. Despite extensive study, most research supporting acoustic adaptation has only considered acoustic traits averaged for species or populations, overlooking intraindividual variation of song traits, which may facilitate effective communication in heterogeneous and variable environments. Fewer studies have explicitly incorporated sexual selection, which, if strong, may favour variation across environments. Here, we evaluate the prevalence of acoustic adaptation among 44 species of songbirds by determining how environmental variability and sexual selection intensity are associated with song variability (intraindividual and intraspecific) and short-term song complexity. We show that variability in precipitation can explain short-term song complexity among taxonomically diverse songbirds, and that precipitation seasonality and the intensity of sexual selection are related to intraindividual song variation. Our results link song complexity to environmental variability, something previously found for mockingbirds (Family Mimidae). Perhaps more importantly, our results illustrate that individual variation in song traits may be shaped by both environmental variability and strength of sexual selection.

Mechanisms driving variability in the ocean forcing of Pine Island Glacier

PubMed Central

Webber, Benjamin G. M.; Heywood, Karen J.; Stevens, David P.; Dutrieux, Pierre; Abrahamsen, E. Povl; Jenkins, Adrian; Jacobs, Stanley S.; Ha, Ho Kyung; Lee, Sang Hoon; Kim, Tae Wan

2017-01-01

Pine Island Glacier (PIG) terminates in a rapidly melting ice shelf, and ocean circulation and temperature are implicated in the retreat and growing contribution to sea level rise of PIG and nearby glaciers. However, the variability of the ocean forcing of PIG has been poorly constrained due to a lack of multi-year observations. Here we show, using a unique record close to the Pine Island Ice Shelf (PIIS), that there is considerable oceanic variability at seasonal and interannual timescales, including a pronounced cold period from October 2011 to May 2013. This variability can be largely explained by two processes: cumulative ocean surface heat fluxes and sea ice formation close to PIIS; and interannual reversals in ocean currents and associated heat transport within Pine Island Bay, driven by a combination of local and remote forcing. Local atmospheric forcing therefore plays an important role in driving oceanic variability close to PIIS. PMID:28211473

Multivariable and Bayesian Network Analysis of Outcome Predictors in Acute Aneurysmal Subarachnoid Hemorrhage: Review of a Pure Surgical Series in the Post-International Subarachnoid Aneurysm Trial Era.

PubMed

Zador, Zsolt; Huang, Wendy; Sperrin, Matthew; Lawton, Michael T

2018-06-01

Following the International Subarachnoid Aneurysm Trial (ISAT), evolving treatment modalities for acute aneurysmal subarachnoid hemorrhage (aSAH) has changed the case mix of patients undergoing urgent surgical clipping. To update our knowledge on outcome predictors by analyzing admission parameters in a pure surgical series using variable importance ranking and machine learning. We reviewed a single surgeon's case series of 226 patients suffering from aSAH treated with urgent surgical clipping. Predictions were made using logistic regression models, and predictive performance was assessed using areas under the receiver operating curve (AUC). We established variable importance ranking using partial Nagelkerke R2 scores. Probabilistic associations between variables were depicted using Bayesian networks, a method of machine learning. Importance ranking showed that World Federation of Neurosurgical Societies (WFNS) grade and age were the most influential outcome prognosticators. Inclusion of only these 2 predictors was sufficient to maintain model performance compared to when all variables were considered (AUC = 0.8222, 95% confidence interval (CI): 0.7646-0.88 vs 0.8218, 95% CI: 0.7616-0.8821, respectively, DeLong's P = .992). Bayesian networks showed that age and WFNS grade were associated with several variables such as laboratory results and cardiorespiratory parameters. Our study is the first to report early outcomes and formal predictor importance ranking following aSAH in a post-ISAT surgical case series. Models showed good predictive power with fewer relevant predictors than in similar size series. Bayesian networks proved to be a powerful tool in visualizing the widespread association of the 2 key predictors with admission variables, explaining their importance and demonstrating the potential for hypothesis generation.

Variation in soil carbon dioxide efflux at two spatial scales in a topographically complex boreal forest

USGS Publications Warehouse

Kelsey, Katharine C.; Wickland, Kimberly P.; Striegl, Robert G.; Neff, Jason C.

2012-01-01

Carbon dynamics of high-latitude regions are an important and highly uncertain component of global carbon budgets, and efforts to constrain estimates of soil-atmosphere carbon exchange in these regions are contingent on accurate representations of spatial and temporal variability in carbon fluxes. This study explores spatial and temporal variability in soilatmosphere carbon dynamics at both fine and coarse spatial scales in a high-elevation, permafrost-dominated boreal black spruce forest. We evaluate the importance of landscape-level investigations of soil-atmosphere carbon dynamics by characterizing seasonal trends in soil-atmosphere carbon exchange, describing soil temperature-moisture-respiration relations, and quantifying temporal and spatial variability at two spatial scales: the plot scale (0–5 m) and the landscape scale (500–1000 m). Plot-scale spatial variability (average variation on a given measurement day) in soil CO2 efflux ranged from a coefficient of variation (CV) of 0.25 to 0.69, and plot-scale temporal variability (average variation of plots across measurement days) in efflux ranged from a CV of 0.19 to 0.36. Landscape-scale spatial and temporal variability in efflux was represented by a CV of 0.40 and 0.31, respectively, indicating that plot-scale spatial variability in soil respiration is as great as landscape-scale spatial variability at this site. While soil respiration was related to soil temperature at both the plot- and landscape scale, landscape-level descriptions of soil moisture were necessary to define soil respiration-moisture relations. Soil moisture variability was also integral to explaining temporal variability in soil respiration. Our results have important implications for research efforts in high-latitude regions where remote study sites make landscape-scale field campaigns challenging.

Physical controls on total and methylmercury concentrations in streams and lakes of the northeastern USA

USGS Publications Warehouse

Shanley, J.B.; Kamman, N.C.; Clair, T.A.; Chalmers, A.

2005-01-01

The physical factors controlling total mercury (HgT) and methylmercury (MeHg) concentrations in lakes and streams of northeastern USA were assessed in a regional data set containing 693 HgT and 385 corresponding MeHg concentrations in surface waters. Multiple regression models using watershed characteristics and climatic variables explained 38% or less of the variance in HgT and MeHg. Land cover percentages and soil permeability generally provided modest predictive power. Percent wetlands alone explained 19% of the variance in MeHg in streams at low-flow, and it was the only significant (p < 0.02) predictor for MeHg in lakes, albeit explaining only 7% of the variance. When stream discharge was added as a variable it became the dominant predictor for HgT in streams, improving the model r 2 from 0.19 to 0.38. Stream discharge improved the MeHg model more modestly, from r 2 of 0.25 to 0.33. Methylation efficiency (MeHg/HgT) was modeled well (r 2 of 0.78) when a seasonal term was incorporated (sine wave with annual period). Physical models explained 18% of the variance in fish Hg concentrations in 134 lakes and 55% in 20 reservoirs. Our results highlight the important role of seasonality and short-term hydrologic changes to the delivery of Hg to water bodies. ?? 2005 Springer Science+Business Media, Inc.

The Relationships between Workaholism and Symptoms of Psychiatric Disorders: A Large-Scale Cross-Sectional Study

PubMed Central

Griffiths, Mark D.; Sinha, Rajita; Hetland, Jørn

2016-01-01

Despite the many number of studies examining workaholism, large-scale studies have been lacking. The present study utilized an open web-based cross-sectional survey assessing symptoms of psychiatric disorders and workaholism among 16,426 workers (Mage = 37.3 years, SD = 11.4, range = 16–75 years). Participants were administered the Adult ADHD Self-Report Scale, the Obsession-Compulsive Inventory-Revised, the Hospital Anxiety and Depression Scale, and the Bergen Work Addiction Scale, along with additional questions examining demographic and work-related variables. Correlations between workaholism and all psychiatric disorder symptoms were positive and significant. Workaholism comprised the dependent variable in a three-step linear multiple hierarchical regression analysis. Basic demographics (age, gender, relationship status, and education) explained 1.2% of the variance in workaholism, whereas work demographics (work status, position, sector, and annual income) explained an additional 5.4% of the variance. Age (inversely) and managerial positions (positively) were of most importance. The psychiatric symptoms (ADHD, OCD, anxiety, and depression) explained 17.0% of the variance. ADHD and anxiety contributed considerably. The prevalence rate of workaholism status was 7.8% of the present sample. In an adjusted logistic regression analysis, all psychiatric symptoms were positively associated with being a workaholic. The independent variables explained between 6.1% and 14.4% in total of the variance in workaholism cases. Although most effect sizes were relatively small, the study’s findings expand our understanding of possible psychiatric predictors of workaholism, and particularly shed new insight into the reality of adult ADHD in work life. The study’s implications, strengths, and shortcomings are also discussed. PMID:27192149

Does a Corresponding Set of Variables for Explaining Voluntary Organizational Turnover Transfer to Explaining Voluntary Occupational Turnover?

ERIC Educational Resources Information Center

Blau, Gary

2007-01-01

This study proposed and tested corresponding sets of variables for explaining voluntary organizational versus occupational turnover for a sample of medical technologists. This study is believed to be the first test of the Rhodes and Doering (1983) occupational change model using occupational turnover data. Results showed that corresponding job…

Climatic extremes improve predictions of spatial patterns of tree species

USGS Publications Warehouse

Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.

2009-01-01

Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

Using social cognitive theory to explain discretionary, "leisure-time" physical exercise among high school students.

PubMed

Winters, Eric R; Petosa, Rick L; Charlton, Thomas E

2003-06-01

To examine whether knowledge of high school students' actions of self-regulation, and perceptions of self-efficacy to overcome exercise barriers, social situation, and outcome expectation will predict non-school related moderate and vigorous physical exercise. High school students enrolled in introductory Physical Education courses completed questionnaires that targeted selected Social Cognitive Theory variables. They also self-reported their typical "leisure-time" exercise participation using a standardized questionnaire. Bivariate correlation statistic and hierarchical regression were conducted on reports of moderate and vigorous exercise frequency. Each predictor variable was significantly associated with measures of moderate and vigorous exercise frequency. All predictor variables were significant in the final regression model used to explain vigorous exercise. After controlling for the effects of gender, the psychosocial variables explained 29% of variance in vigorous exercise frequency. Three of four predictor variables were significant in the final regression equation used to explain moderate exercise. The final regression equation accounted for 11% of variance in moderate exercise frequency. Professionals who attempt to increase the prevalence of physical exercise through educational methods should focus on the psychosocial variables utilized in this study.

Birth Order and health: major issues.

PubMed

Elliott, B A

1992-08-01

Birth Order has been described as a variable with a complex relationship to child and adult outcomes. A review of the medical literature over the past 5 years identified 20 studies that investigated the relationship between Birth Order and a health outcome. Only one of the studies established a relationship between Birth Order and a health outcome: third and fourth-born children have a higher incidence of accidents that result in hospitalization. The other demonstrated relationships are each explained by intervening variables or methodological limitations. Although Birth Order is not a strongly independent explanatory factor in understanding health outcomes, it is an important marker variable. Statistically significant relationships between Birth Order and health outcomes yield insights into the ways a family influences an individual's health.

Relationships between pediatric asthma and socioeconomic/urban variables in Baltimore, Maryland

NASA Technical Reports Server (NTRS)

Kimes, Daniel; Ullah, Asad; Levine, Elissa; Nelson, Ross; Timmins, Sidey; Weiss, Sheila; Bollinger, Mary E.; Blaisdell, Carol

2004-01-01

Spatial relationships between clinical data for pediatric asthmatics (hospital and emergency department utilization rates), and socioeconomic and urban characteristics in Baltimore City were analyzed with the aim of identifying factors that contribute to increased asthma rates. Socioeconomic variables and urban characteristics derived from satellite data explained 95% of the spatial variation in hospital rates. The proportion of families headed by a single female was the most important variable accounting for 89% of the spatial variation. Evidence suggests that the high rates of hospital admissions and emergency department (ED) visits may partially be due to the difficulty of single parents with limited resources managing their child's asthma condition properly. This knowledge can be used for education towards mitigating ED and hospital events in Baltimore City.

The role of density-dependent and -independent processes in spawning habitat selection by salmon in an Arctic riverscape.

PubMed

Huntsman, Brock M; Falke, Jeffrey A; Savereide, James W; Bennett, Katrina E

2017-01-01

Density-dependent (DD) and density-independent (DI) habitat selection is strongly linked to a species' evolutionary history. Determining the relative importance of each is necessary because declining populations are not always the result of altered DI mechanisms but can often be the result of DD via a reduced carrying capacity. We developed spatially and temporally explicit models throughout the Chena River, Alaska to predict important DI mechanisms that influence Chinook salmon spawning success. We used resource-selection functions to predict suitable spawning habitat based on geomorphic characteristics, a semi-distributed water-and-energy balance hydrologic model to generate stream flow metrics, and modeled stream temperature as a function of climatic variables. Spawner counts were predicted throughout the core and periphery spawning sections of the Chena River from escapement estimates (DD) and DI variables. Additionally, we used isodar analysis to identify whether spawners actively defend spawning habitat or follow an ideal free distribution along the riverscape. Aerial counts were best explained by escapement and reference to the core or periphery, while no models with DI variables were supported in the candidate set. Furthermore, isodar plots indicated habitat selection was best explained by ideal free distributions, although there was strong evidence for active defense of core spawning habitat. Our results are surprising, given salmon commonly defend spawning resources, and are likely due to competition occurring at finer spatial scales than addressed in this study.

The role of density-dependent and –independent processes in spawning habitat selection by salmon in an Arctic riverscape

DOE PAGES

Huntsman, Brock M.; Falke, Jeffrey A.; Savereide, James W.; ...

2017-05-22

Density-dependent (DD) and density-independent (DI) habitat selection is strongly linked to a species’ evolutionary history. Determining the relative importance of each is necessary because declining populations are not always the result of altered DI mechanisms but can often be the result of DD via a reduced carrying capacity. Here, we developed spatially and temporally explicit models throughout the Chena River, Alaska to predict important DI mechanisms that influence Chinook salmon spawning success. We used resource-selection functions to predict suitable spawning habitat based on geomorphic characteristics, a semi-distributed water-and-energy balance hydrologic model to generate stream flow metrics, and modeled stream temperaturemore » as a function of climatic variables. Spawner counts were predicted throughout the core and periphery spawning sections of the Chena River from escapement estimates (DD) and DI variables. In addition, we used isodar analysis to identify whether spawners actively defend spawning habitat or follow an ideal free distribution along the riverscape. Aerial counts were best explained by escapement and reference to the core or periphery, while no models with DI variables were supported in the candidate set. Moreover, isodar plots indicated habitat selection was best explained by ideal free distributions, although there was strong evidence for active defense of core spawning habitat. These results are surprising, given salmon commonly defend spawning resources, and are likely due to competition occurring at finer spatial scales than addressed in this study.« less

The role of density-dependent and –independent processes in spawning habitat selection by salmon in an Arctic riverscape

USGS Publications Warehouse

Huntsman, Brock M.; Falke, Jeffrey A.; Savereide, James W.; Bennett, Katrina E.

2017-01-01

Density-dependent (DD) and density-independent (DI) habitat selection is strongly linked to a species’ evolutionary history. Determining the relative importance of each is necessary because declining populations are not always the result of altered DI mechanisms but can often be the result of DD via a reduced carrying capacity. We developed spatially and temporally explicit models throughout the Chena River, Alaska to predict important DI mechanisms that influence Chinook salmon spawning success. We used resource-selection functions to predict suitable spawning habitat based on geomorphic characteristics, a semi-distributed water-and-energy balance hydrologic model to generate stream flow metrics, and modeled stream temperature as a function of climatic variables. Spawner counts were predicted throughout the core and periphery spawning sections of the Chena River from escapement estimates (DD) and DI variables. Additionally, we used isodar analysis to identify whether spawners actively defend spawning habitat or follow an ideal free distribution along the riverscape. Aerial counts were best explained by escapement and reference to the core or periphery, while no models with DI variables were supported in the candidate set. Furthermore, isodar plots indicated habitat selection was best explained by ideal free distributions, although there was strong evidence for active defense of core spawning habitat. Our results are surprising, given salmon commonly defend spawning resources, and are likely due to competition occurring at finer spatial scales than addressed in this study.

Regionalization of precipitation characteristics in Iran's Lake Urmia basin

NASA Astrophysics Data System (ADS)

Fazel, Nasim; Berndtsson, Ronny; Uvo, Cintia Bertacchi; Madani, Kaveh; Kløve, Bjørn

2018-04-01

Lake Urmia in northwest Iran, once one of the largest hypersaline lakes in the world, has shrunk by almost 90% in area and 80% in volume during the last four decades. To improve the understanding of regional differences in water availability throughout the region and to refine the existing information on precipitation variability, this study investigated the spatial pattern of precipitation for the Lake Urmia basin. Daily rainfall time series from 122 precipitation stations with different record lengths were used to extract 15 statistical descriptors comprising 25th percentile, 75th percentile, and coefficient of variation for annual and seasonal total precipitation. Principal component analysis in association with cluster analysis identified three main homogeneous precipitation groups in the lake basin. The first sub-region (group 1) includes stations located in the center and southeast; the second sub-region (group 2) covers mostly northern and northeastern part of the basin, and the third sub-region (group 3) covers the western and southern edges of the basin. Results of principal component (PC) and clustering analyses showed that seasonal precipitation variation is the most important feature controlling the spatial pattern of precipitation in the lake basin. The 25th and 75th percentiles of winter and autumn are the most important variables controlling the spatial pattern of the first rotated principal component explaining about 32% of the total variance. Summer and spring precipitation variations are the most important variables in the second and third rotated principal components, respectively. Seasonal variation in precipitation amount and seasonality are explained by topography and influenced by the lake and westerly winds that are related to the strength of the North Atlantic Oscillation. Despite using incomplete time series with different lengths, the identified sub-regions are physically meaningful.

Racial Disparities in Mortality Among Middle-Aged and Older Men: Does Marriage Matter?

PubMed

Su, Dejun; Stimpson, Jim P; Wilson, Fernando A

2015-07-01

Based on longitudinal data from the Health and Retirement Study, this study assesses the importance of marital status in explaining racial disparities in all-cause mortality during an 18-year follow-up among White and African American men aged 51 to 61 years in 1992. Being married was associated with significant advantages in household income, health behaviors, and self-rated health. These advantages associated with marriage at baseline also got translated into better survival chance for married men during the 1992-2010 follow-up. Both marital selection and marital protection were relevant in explaining the mortality advantages associated with marriage. After adjusting for the effect of selected variables on premarital socioeconomic status and health, about 28% of the mortality gap between White and African American men in the Health and Retirement Study can be explained by the relatively low rates of marriage among African American men. Addressing the historically low rates of marriage among African Americans and their contributing factors becomes important for reducing racial disparities in men's mortality. © The Author(s) 2014.

Assessing the Impact of Socioeconomic Variables on Small Area Variations in Suicide Outcomes in England

PubMed Central

Congdon, Peter

2012-01-01

Ecological studies of suicide and self-harm have established the importance of area variables (e.g., deprivation, social fragmentation) in explaining variations in suicide risk. However, there are likely to be unobserved influences on risk, typically spatially clustered, which can be modeled as random effects. Regression impacts may be biased if no account is taken of spatially structured influences on risk. Furthermore a default assumption of linear effects of area variables may also misstate or understate their impact. This paper considers variations in suicide outcomes for small areas across England, and investigates the impact on them of area socio-economic variables, while also investigating potential nonlinearity in their impact and allowing for spatially clustered unobserved factors. The outcomes are self-harm hospitalisations and suicide mortality over 6,781 Middle Level Super Output Areas. PMID:23271304

Assessing the impact of socioeconomic variables on small area variations in suicide outcomes in England.

PubMed

Congdon, Peter

2012-12-27

Ecological studies of suicide and self-harm have established the importance of area variables (e.g., deprivation, social fragmentation) in explaining variations in suicide risk. However, there are likely to be unobserved influences on risk, typically spatially clustered, which can be modeled as random effects. Regression impacts may be biased if no account is taken of spatially structured influences on risk. Furthermore a default assumption of linear effects of area variables may also misstate or understate their impact. This paper considers variations in suicide outcomes for small areas across England, and investigates the impact on them of area socio-economic variables, while also investigating potential nonlinearity in their impact and allowing for spatially clustered unobserved factors. The outcomes are self-harm hospitalisations and suicide mortality over 6,781 Middle Level Super Output Areas.

Attitudes toward same-sex marriage: the case of Scandinavia.

PubMed

Jakobsson, Niklas; Kotsadam, Andreas; Jakobsson, Siri Støre

2013-01-01

The purpose of this study was to examine the variables that explain attitudes toward same-sex marriage. Using recently collected Scandinavian data (from Norway and Sweden) with a high response rate, this study shows that gender, regular participation in religious activities, political ideology, education, whether the respondent lived in the capital city, and attitudes toward gender equality were important for attitudes toward same-sex marriage. Age and income were not important for attitudes toward same-sex marriage. Although both Norwegians and Swedes clearly favor same-sex marriage, Swedes are significantly more positive than Norwegians.

Environmental controls of marine productivity hot spots around Antarctica

NASA Astrophysics Data System (ADS)

Arrigo, Kevin R.; van Dijken, Gert L.; Strong, Aaron L.

2015-08-01

Antarctic coastal polynyas are biologically rich ecosystems that support large populations of mammals and birds and are globally significant sinks of atmospheric carbon dioxide. To support local phytoplankton blooms, these highly productive ecosystems require a large input of iron (Fe), the sources of which are poorly known. Here we assess the relative importance of six different environmental factors in controlling the amount of phytoplankton biomass and rates of net primary production (NPP) in 46 coastal polynyas around Antarctica. Data presented here suggest that melting ice shelves are a primary supplier of Fe to coastal polynyas, with basal melt rates explaining 59% of the between-polynya variance in mean chlorophyll a (Chl a) concentration. In a multiple regression analysis, which explained 78% of the variance in chlorophyll a (Chl a) between polynyas, basal melt rate explained twice as much of the variance as the next most important variable. Fe upwelled from sediments, which is partly controlled by continental shelf width, was also important in some polynyas. Of secondary importance to phytoplankton abundance and NPP were sea surface temperature and polynya size. Surprisingly, differences in light availability and the length of the open water season explained little or none of the variance in either Chl a or NPP between polynyas. If the productivity of coastal polynyas is indeed sensitive to the release of Fe from melting ice shelves, future changes in ice shelf melt rates could dramatically influence Antarctic coastal ecosystems and the ability of continental shelf waters to sequester atmospheric carbon dioxide. This article was corrected on 26 AUG 2015. See the end of the full text for details.

Effect of Adding McKenzie Syndrome, Centralization, Directional Preference, and Psychosocial Classification Variables to a Risk-Adjusted Model Predicting Functional Status Outcomes for Patients With Lumbar Impairments.

PubMed

Werneke, Mark W; Edmond, Susan; Deutscher, Daniel; Ward, Jason; Grigsby, David; Young, Michelle; McGill, Troy; McClenahan, Brian; Weinberg, Jon; Davidow, Amy L

2016-09-01

Study Design Retrospective cohort. Background Patient-classification subgroupings may be important prognostic factors explaining outcomes. Objectives To determine effects of adding classification variables (McKenzie syndrome and pain patterns, including centralization and directional preference; Symptom Checklist Back Pain Prediction Model [SCL BPPM]; and the Fear-Avoidance Beliefs Questionnaire subscales of work and physical activity) to a baseline risk-adjusted model predicting functional status (FS) outcomes. Methods Consecutive patients completed a battery of questionnaires that gathered information on 11 risk-adjustment variables. Physical therapists trained in Mechanical Diagnosis and Therapy methods classified each patient by McKenzie syndromes and pain pattern. Functional status was assessed at discharge by patient-reported outcomes. Only patients with complete data were included. Risk of selection bias was assessed. Prediction of discharge FS was assessed using linear stepwise regression models, allowing 13 variables to enter the model. Significant variables were retained in subsequent models. Model power (R(2)) and beta coefficients for model variables were estimated. Results Two thousand sixty-six patients with lumbar impairments were evaluated. Of those, 994 (48%), 10 (<1%), and 601 (29%) were excluded due to incomplete psychosocial data, McKenzie classification data, and missing FS at discharge, respectively. The final sample for analyses was 723 (35%). Overall R(2) for the baseline prediction FS model was 0.40. Adding classification variables to the baseline model did not result in significant increases in R(2). McKenzie syndrome or pain pattern explained 2.8% and 3.0% of the variance, respectively. When pain pattern and SCL BPPM were added simultaneously, overall model R(2) increased to 0.44. Although none of these increases in R(2) were significant, some classification variables were stronger predictors compared with some other variables included in the baseline model. Conclusion The small added prognostic capabilities identified when combining McKenzie or pain-pattern classifications with the SCL BPPM classification did not significantly improve prediction of FS outcomes in this study. Additional research is warranted to investigate the importance of classification variables compared with those used in the baseline model to maximize predictive power. Level of Evidence Prognosis, level 4. J Orthop Sports Phys Ther 2016;46(9):726-741. Epub 31 Jul 2016. doi:10.2519/jospt.2016.6266.

Does internal variability change in response to global warming? A large ensemble modelling study of tropical rainfall

NASA Astrophysics Data System (ADS)

Milinski, S.; Bader, J.; Jungclaus, J. H.; Marotzke, J.

2017-12-01

There is some consensus on mean state changes of rainfall under global warming; changes of the internal variability, on the other hand, are more difficult to analyse and have not been discussed as much despite their importance for understanding changes in extreme events, such as droughts or floodings. We analyse changes in the rainfall variability in the tropical Atlantic region. We use a 100-member ensemble of historical (1850-2005) model simulations with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1) to identify changes of internal rainfall variability. To investigate the effects of global warming on the internal variability, we employ an additional ensemble of model simulations with stronger external forcing (1% CO2-increase per year, same integration length as the historical simulations) with 68 ensemble members. The focus of our study is on the oceanic Atlantic ITCZ. We find that the internal variability of rainfall over the tropical Atlantic does change due to global warming and that these changes in variability are larger than changes in the mean state in some regions. From splitting the total variance into patterns of variability, we see that the variability on the southern flank of the ITCZ becomes more dominant, i.e. explaining a larger fraction of the total variance in a warmer climate. In agreement with previous studies, we find that changes in the mean state show an increase and narrowing of the ITCZ. The large ensembles allow us to do a statistically robust differentiation between the changes in variability that can be explained by internal variability and those that can be attributed to the external forcing. Furthermore, we argue that internal variability in a transient climate is only well defined in the ensemble domain and not in the temporal domain, which requires the use of a large ensemble.

Landscape genomics and pathway analysis to understand genetic adaptation of South African indigenous goat populations.

PubMed

Mdladla, K; Dzomba, E F; Muchadeyi, F C

2018-04-01

In Africa, extensively raised livestock populations in most smallholder farming communities are exposed to harsh and heterogeneous climatic conditions and disease pathogens that they adapt to in order to survive. Majority of these livestock species, including goats, are of non-descript and uncharacterized breeds and their response to natural selection presented by heterogeneous environments is still unresolved. This study investigated genetic diversity and its association with environmental and geographic conditions in 194 South African indigenous goats from different geographic locations genotyped on the Illumina goat SNP50K panel. Population structure analysis revealed a homogeneous genetic cluster of the Tankwa goats, restricted to the Northern Cape province. Overall, the Boer, Kalahari Red, and Savanna showed a wide geographic spread of shared genetic components, whereas the village ecotypes revealed a longitudinal distribution. The relative importance of environmental factors on genetic variation of goat populations was assessed using redundancy analysis (RDA). Climatic and geographic variables explained 22% of the total variation while climatic variables alone accounted for 17% of the diversity. Geographic variables solitarily explained 1% of the total variation. The first axis (Model I) of the RDA analysis revealed 329 outlier SNPs. Landscape genomic approaches of spatial analysis method (SAM) identified a total of 843 (1.75%) SNPs, while latent factor mixed models (LFMM) identified 714 (1.48%) SNPs significantly associated with environmental variables. Significant markers were within genes involved in biological functions potentially important for environmental adaptation. Overall, the study suggested environmental factors to have some effect in shaping the genetic variation of South African indigenous goat populations. Loci observed to be significant and under selection may be responsible for the adaption of the goat populations to local production systems.

Hydrometeorological daily recharge assessment model (DREAM) for the Western Mountain Aquifer, Israel: Model application and effects of temporal patterns

NASA Astrophysics Data System (ADS)

Sheffer, N. A.; Dafny, E.; Gvirtzman, H.; Navon, S.; Frumkin, A.; Morin, E.

2010-05-01

Recharge is a critical issue for water management. Recharge assessment and the factors affecting recharge are of scientific and practical importance. The purpose of this study was to develop a daily recharge assessment model (DREAM) on the basis of a water balance principle with input from conventional and generally available precipitation and evaporation data and demonstrate the application of this model to recharge estimation in the Western Mountain Aquifer (WMA) in Israel. The WMA (area 13,000 km2) is a karst aquifer that supplies 360-400 Mm3 yr-1 of freshwater, which constitutes 20% of Israel's freshwater and is highly vulnerable to climate variability and change. DREAM was linked to a groundwater flow model (FEFLOW) to simulate monthly hydraulic heads and spring flows. The models were calibrated for 1987-2002 and validated for 2003-2007, yielding high agreement between calculated and measured values (R2 = 0.95; relative root-mean-square error = 4.8%; relative bias = 1.04). DREAM allows insights into the effect of intra-annual precipitation distribution factors on recharge. Although annual precipitation amount explains ˜70% of the variability in simulated recharge, analyses with DREAM indicate that the rainy season length is an important factor controlling recharge. Years with similar annual precipitation produce different recharge values as a result of temporal distribution throughout the rainy season. An experiment with a synthetic data set exhibits similar results, explaining ˜90% of the recharge variability. DREAM represents significant improvement over previous recharge estimation techniques in this region by providing near-real-time recharge estimates that can be used to predict the impact of climate variability on groundwater resources at high temporal and spatial resolution.

Varying Land-Use Has an Influence on Wattled and Grey Crowned Cranes' Abundance and Distribution in Driefontein Grasslands Important Bird Area, Zimbabwe.

PubMed

Fakarayi, Togarasei; Mashapa, Clayton; Gandiwa, Edson; Kativu, Shakkie

2016-01-01

Three species of cranes are distributed widely throughout southern Africa, but little is known about how they respond to the changes in land-use that have occurred in this region. This study assessed habitat preference of the two crane species across land-use categories of the self contained small scale commercial farms of 30 to 40 ha per household (A1), large scale commercial agriculture farms of > 50 ha per household (A2) and Old Resettlement, farms of < 5 ha per household with communal grazing land in Driefontein Grasslands Important Bird Area (IBA), Zimbabwe. The study further explored how selected explanatory (environmental) habitat variables influence crane species abundance. Crane bird counts and data on influencing environmental variables were collected between June and August 2012. Our results show that varying land-use categories had an influence on the abundance and distribution of the Wattled Crane (Bugeranus carunculatus) and the Grey Crowned Crane (Belearica regulorum) across Driefontein Grasslands IBA. The Wattled Crane was widely distributed in the relatively undisturbed A2 farms while the Grey Crowned Crane was associated with the more disturbed land of A1 farms, Old Resettlement and its communal grazing land. Cyperus esculentus and percent (%) bare ground were strong environmental variables best explaining the observed patterns in Wattled Crane abundance across land-use categories. The pattern in Grey Crowned Crane abundance was best explained by soil penetrability, moisture and grass height variables. A holistic sustainable land-use management that takes into account conservation of essential habitats in Driefontein Grasslands IBA is desirable for crane populations and other wetland dependent species that include water birds.

Varying Land-Use Has an Influence on Wattled and Grey Crowned Cranes’ Abundance and Distribution in Driefontein Grasslands Important Bird Area, Zimbabwe

PubMed Central

Fakarayi, Togarasei; Mashapa, Clayton; Gandiwa, Edson; Kativu, Shakkie

2016-01-01

Three species of cranes are distributed widely throughout southern Africa, but little is known about how they respond to the changes in land-use that have occurred in this region. This study assessed habitat preference of the two crane species across land-use categories of the self contained small scale commercial farms of 30 to 40 ha per household (A1), large scale commercial agriculture farms of > 50 ha per household (A2) and Old Resettlement, farms of < 5 ha per household with communal grazing land in Driefontein Grasslands Important Bird Area (IBA), Zimbabwe. The study further explored how selected explanatory (environmental) habitat variables influence crane species abundance. Crane bird counts and data on influencing environmental variables were collected between June and August 2012. Our results show that varying land-use categories had an influence on the abundance and distribution of the Wattled Crane (Bugeranus carunculatus) and the Grey Crowned Crane (Belearica regulorum) across Driefontein Grasslands IBA. The Wattled Crane was widely distributed in the relatively undisturbed A2 farms while the Grey Crowned Crane was associated with the more disturbed land of A1 farms, Old Resettlement and its communal grazing land. Cyperus esculentus and percent (%) bare ground were strong environmental variables best explaining the observed patterns in Wattled Crane abundance across land-use categories. The pattern in Grey Crowned Crane abundance was best explained by soil penetrability, moisture and grass height variables. A holistic sustainable land-use management that takes into account conservation of essential habitats in Driefontein Grasslands IBA is desirable for crane populations and other wetland dependent species that include water birds. PMID:27875552

Baleen whale abundance and distribution in relation to environmental variables and prey density in the Eastern Bering Sea

NASA Astrophysics Data System (ADS)

Zerbini, Alexandre N.; Friday, Nancy A.; Palacios, Daniel M.; Waite, Janice M.; Ressler, Patrick H.; Rone, Brenda K.; Moore, Sue E.; Clapham, Phillip J.

2016-12-01

The Bering Sea is one of the most productive marine ecosystems in the world and an important habitat for various marine mammal species. Once abundant in this region, most baleen whale species were severely depleted by commercial whaling in the 19th and early 20th centuries. Since their protection in mid-20th century, baleen whale populations have been recovering and reoccupying their historical habitats. These species can consume large amounts of their prey and thus can modify the local structure of ecosystems. Characterizing the extent to which environmental conditions and prey density influence baleen whale abundance in the Eastern Bering Sea is essential to improve our understanding of ecosystem dynamics and to predict how these species might respond to ecosystem variability associated with climate changes. In this study, physiographic, oceanographic, and biological datasets from 2008 to 2010 were combined to model the habitat characteristics of fin whales, humpback whales, and minke whales in the EBS in early summer (June and July) using generalized additive models (GAMs). The explained deviances of the best-supported models were 54.9%, 20.6%, and 68.3% for minke, fin and humpback whales, respectively. Minke and fin whales had similar distribution patterns in the EBS but their abundance was predicted by different explanatory variables. Euphausiid and pollock biomasses, and depth were important predictors of minke whale numbers, while distance to shore, euphausiid biomass, distance to the 200 m isobath, and chlorophyll-a concentration better explained fin whale abundance. Humpback whales showed a preference for shallow, coastal waters north of the Alaska Peninsula. For this species, sea surface temperature, depth, chlorophyll-a concentration and euphausid biomass were important predictors of abundance. This study is the first to provide a habitat baseline for baleen whales in the EBS based on a quantitative assessment of the relationship between whale abundance, environmental variables, and density of euphausiids and age-1 pollock in early summer. Because this study was conducted during a cold temperature regime in the Bering Sea, additional research is needed to assess how whales respond to environmental variables and prey biomass in years with warm conditions.

Primates and the evolution of long, slow life histories.

PubMed

Jones, James Holland

2011-09-27

Primates are characterized by relatively late ages at first reproduction, long lives and low fertility. Together, these traits define a life-history of reduced reproductive effort. Understanding the optimal allocation of reproductive effort, and specifically reduced reproductive effort, has been one of the key problems motivating the development of life-history theory. Because of their unusual constellation of life-history traits, primates play an important role in the continued development of life-history theory. In this review, I present the evidence for the reduced reproductive effort life histories of primates and discuss the ways that such life-history tactics are understood in contemporary theory. Such tactics are particularly consistent with the predictions of stochastic demographic models, suggesting a key role for environmental variability in the evolution of primate life histories. The tendency for primates to specialize in high-quality, high-variability food items may make them particularly susceptible to environmental variability and explains their low reproductive-effort tactics. I discuss recent applications of life-history theory to human evolution and emphasize the continuity between models used to explain peculiarities of human reproduction and senescence with the long, slow life histories of primates more generally. Copyright © 2011 Elsevier Ltd. All rights reserved.

Social anxiety following traumatic brain injury: an exploration of associated factors.

PubMed

Curvis, William; Simpson, Jane; Hampson, Natalie

2018-06-01

Social anxiety (SA) following traumatic brain injury (TBI) has the potential to affect an individual's general psychological well-being and social functioning, however little research has explored factors associated with its development. The present study used hierarchical multiple regression to investigate the demographic, clinical and psychological factors associated with SA following TBI. A sample of 85 people who experienced TBI were recruited through social media websites and brain injury services across the North-West of England. The overall combined biopsychosocial model was significant, explaining 52-54.3% of the variance in SA (across five imputations of missing data). The addition of psychological variables (self-esteem, locus of control, self-efficacy) made a significant contribution to the overall model, accounting for an additional 12.2-13% of variance in SA above that explained by demographic and clinical variables. Perceived stigma was the only significant independent predictor of SA (B = .274, p = .005). The findings suggest that psychological variables are important in the development of SA following TBI and must be considered alongside clinical factors. Furthermore, the significant role of stigma highlights the need for intervention at both an individualised and societal level.

Primates and the Evolution of Long-Slow Life Histories

PubMed Central

Jones, James Holland

2011-01-01

Summary Primates are characterized by relatively late ages at first reproduction, long lives and low fertility. Together, these traits define a life-history of reduced reproductive effort. Understanding the optimal allocation of reproductive effort, and specifically reduced reproductive effort, has been one of the key problems motivating the development of life history theory. Because of their unusual constellation of life-history traits, primates play an important role in the continued development of life history theory. In this review, I present the evidence for the reduced reproductive effort life histories of primates and discuss the ways that such life-history tactics are understood in contemporary theory. Such tactics are particularly consistent with the predictions of stochastic demographic models, suggesting a key role for environmental variability in the evolution of primate life histories. The tendency for primates to specialize in high-quality, high-variability food items may make them particularly susceptible to environmental variability and explain their low reproductive-effort tactics. I discuss recent applications of life history theory to human evolution and emphasize the continuity between models used to explain peculiarities of human reproduction and senescence with the long, slow life histories of primates more generally. PMID:21959161

Airport Choice in Sao Paulo Metropolitan Area: An Application of the Conditional Logit Model

NASA Technical Reports Server (NTRS)

Moreno, Marcelo Baena; Muller, Carlos

2003-01-01

Using the conditional LOGIT model, this paper addresses the airport choice in the Sao Paulo Metropolitan Area. In this region, Guarulhos International Airport (GRU) and Congonhas Airport (CGH) compete for passengers flying to several domestic destinations. The airport choice is believed to be a result of the tradeoff passengers perform considering airport access characteristics, airline level of service characteristics and passenger experience with the analyzed airports. It was found that access time to the airports better explain the airport choice than access distance, whereas direct flight frequencies gives better explanation to the airport choice than the indirect (connections and stops) and total (direct plus indirect) flight frequencies. Out of 15 tested variables, passenger experience with the analyzed airports was the variable that best explained the airport choice in the region. Model specifications considering 1, 2 or 3 variables were tested. The model specification most adjusted to the observed data considered access time, direct flight frequencies in the travel period (morning or afternoon peak) and passenger experience with the analyzed airports. The influence of these variables was therefore analyzed across market segments according to departure airport and flight duration criteria. The choice of GRU (located neighboring Sao Paulo city) is not well explained by the rationality of access time economy and the increase of the supply of direct flight frequencies, while the choice of CGH (located inside Sao Paulo city) is. Access time was found to be more important to passengers flying shorter distances while direct flight frequencies in the travel period were more significant to those flying longer distances. Keywords: Airport choice, Multiple airport region, Conditional LOGIT model, Access time, Flight frequencies, Passenger experience with the analyzed airports, Transportation planning

Determinants of personal exposure to PM2.5, ultrafine particle counts, and CO in a transport microenvironment.

PubMed

Kaur, S; Nieuwenhuijsen, M J

2009-07-01

Short-term human exposure concentrations to PM2.5, ultrafine particle counts (particle range: 0.02-1 microm), and carbon monoxide (CO) were investigated at and around a street canyon intersection in Central London, UK. During a four week field campaign, groups of four volunteers collected samples at three timings (morning, lunch, and afternoon), along two different routes (a heavily trafficked route and a backstreet route) via five modes of transport (walking, cycling, bus, car, and taxi). This was followed by an investigation into the determinants of exposure using a regression technique which incorporated the site-specific traffic counts, meteorological variables (wind speed and temperature) and the mode of transport used. The analyses explained 9, 62, and 43% of the variability observed in the exposure concentrations to PM2.5, ultrafine particle counts, and CO in this study, respectively. The mode of transport was a statistically significant determinant of personal exposure to PM2.5, ultrafine particle counts, and CO, and for PM2.5 and ultrafine particle counts it was the most important determinant. Traffic count explained little of the variability in the PM2.5 concentrations, but it had a greater influence on ultrafine particle count and CO concentrations. The analyses showed that temperature had a statistically significant impact on ultrafine particle count and CO concentrations. Wind speed also had a statistically significant effect but smaller. The small proportion in variability explained in PM2.5 by the model compared to the largest proportion in ultrafine particle counts and CO may be due to the effect of long-range transboundary sources, whereas for ultrafine particle counts and CO, local traffic is the main source.

Intrusive thoughts in obsessive-compulsive disorder and eating disorder patients: a differential analysis.

PubMed

García-Soriano, Gemma; Roncero, Maria; Perpiñá, Conxa; Belloch, Amparo

2014-05-01

The present study aims to compare the unwanted intrusions experienced by obsessive-compulsive (OCD) and eating disorder (ED) patients, their appraisals, and their control strategies and analyse which variables predict the intrusions' disruption and emotional disturbance in each group. Seventy-nine OCD and 177 ED patients completed two equivalent self-reports designed to assess OCD-related and ED-related intrusions, their dysfunctional appraisals, and associated control strategies. OCD and ED patients experienced intrusions with comparable frequency and emotional disturbance, but OCD patients experienced greater disruption. Differences appeared between groups on some appraisals and control strategies. Intolerance to uncertainty (OCD group) and thought importance (ED group) predicted their respective emotional disturbance and disruption. Additionally, control importance (OCD group) and thought-action fusion moral (OCD and ED groups) predicted their emotional disturbance. OCD and ED share the presence of intrusions; however, different variables explain why they are disruptive and emotionally disturbing. Cognitive intrusions require further investigation as a transdiagnostic variable. Copyright © 2014 John Wiley & Sons, Ltd and Eating Disorders Association.

The role of self-transcendence: a missing variable in the pursuit of successful aging?

PubMed

McCarthy, Valerie Lander; Ling, Jiying; Carini, Robert M

2013-07-01

While successful aging is often defined as the absence of disease and disability or as life satisfaction, self-transcendence may also play an important role. The objective of this research was to test a nursing theory of successful aging proposing that transcendence and adaptation predict successful aging. In this cross-sectional exploratory study, a convenience sample of older adults (N = 152) were surveyed about self-transcendence, proactive coping, and successful aging. Using hierarchical multiple regression, self-transcendence, proactive coping, and all control variables (i.e., sex, race, perceived health, place of residence) together explained 50% of the variance in successful aging (p < 0.001). However, proactive coping alone was not a significant predictor of successful aging. Thus, this study did not support the theory that both self-transcendence and proactive coping predict successful aging. Self-transcendence was the only significant contributor to this multidimensional view of successful aging. Self-transcendence is an important variable in the pursuit of successful aging, which merits further investigation. Copyright 2013, SLACK Incorporated.

Testing a model of physical activity among mothers and fathers of young children: integrating self-determined motivation, planning, and the theory of planned behavior.

PubMed

Hamilton, Kyra; Cox, Stephen; White, Katherine M

2012-02-01

Parents are at risk for inactivity; however, research into understanding parental physical activity (PA) is scarce. We integrated self-determined motivation, planning, and the theory of planned behavior (TPB) to better understand parental PA. Parents (252 mothers, 206 fathers) completed a main questionnaire assessing measures underpinning these constructs and a 1-week follow-up of PA behavior to examine whether self-determined motivation indirectly influenced intention via the TPB variables (i.e., attitude, subjective norm, and perceived behavioral control) and intention indirectly influenced behavior via planning. We found self-determined motivation on intention was fully mediated by the TPB variables and intention on behavior was partially mediated by the planning variables. In addition, slight differences in the model's paths between the sexes were revealed. The results illustrate the range of important determinants of parental PA and provide support for the integrated model in explaining PA decision making as well as the importance of examining sex differences.

African American patients' intent to screen for colorectal cancer: Do cultural factors, health literacy, knowledge, age and gender matter?

PubMed

Brittain, Kelly; Christy, Shannon M; Rawl, Susan M

2016-02-01

African Americans have higher colorectal cancer (CRC) mortality rates. Research suggests that CRC screening interventions targeting African Americans be based upon cultural dimensions. Secondary analysis of data from African-Americans who were not up-to-date with CRC screening (n=817) was conducted to examine: 1) relationships among cultural factors (i.e., provider trust, cancer fatalism, health temporal orientation (HTO)), health literacy, and CRC knowledge; 2) age and gender differences; and 3) relationships among the variables and CRC screening intention. Provider trust, fatalism, HTO, health literacy and CRC knowledge had significant relationships among study variables. The FOBT intention model explained 43% of the variance with age and gender being significant predictors. The colonoscopy intention model explained 41% of the variance with gender being a significant predictor. Results suggest that when developing CRC interventions for African Americans, addressing cultural factors remain important, but particular attention should be given to the age and gender of the patient.

Environment and host as large-scale controls of ectomycorrhizal fungi.

PubMed

van der Linde, Sietse; Suz, Laura M; Orme, C David L; Cox, Filipa; Andreae, Henning; Asi, Endla; Atkinson, Bonnie; Benham, Sue; Carroll, Christopher; Cools, Nathalie; De Vos, Bruno; Dietrich, Hans-Peter; Eichhorn, Johannes; Gehrmann, Joachim; Grebenc, Tine; Gweon, Hyun S; Hansen, Karin; Jacob, Frank; Kristöfel, Ferdinand; Lech, Paweł; Manninger, Miklós; Martin, Jan; Meesenburg, Henning; Merilä, Päivi; Nicolas, Manuel; Pavlenda, Pavel; Rautio, Pasi; Schaub, Marcus; Schröck, Hans-Werner; Seidling, Walter; Šrámek, Vít; Thimonier, Anne; Thomsen, Iben Margrete; Titeux, Hugues; Vanguelova, Elena; Verstraeten, Arne; Vesterdal, Lars; Waldner, Peter; Wijk, Sture; Zhang, Yuxin; Žlindra, Daniel; Bidartondo, Martin I

2018-06-06

Explaining the large-scale diversity of soil organisms that drive biogeochemical processes-and their responses to environmental change-is critical. However, identifying consistent drivers of belowground diversity and abundance for some soil organisms at large spatial scales remains problematic. Here we investigate a major guild, the ectomycorrhizal fungi, across European forests at a spatial scale and resolution that is-to our knowledge-unprecedented, to explore key biotic and abiotic predictors of ectomycorrhizal diversity and to identify dominant responses and thresholds for change across complex environmental gradients. We show the effect of 38 host, environment, climate and geographical variables on ectomycorrhizal diversity, and define thresholds of community change for key variables. We quantify host specificity and reveal plasticity in functional traits involved in soil foraging across gradients. We conclude that environmental and host factors explain most of the variation in ectomycorrhizal diversity, that the environmental thresholds used as major ecosystem assessment tools need adjustment and that the importance of belowground specificity and plasticity has previously been underappreciated.

Single- and Dual-Process Models of Biased Contingency Detection

PubMed Central

2016-01-01

Abstract. Decades of research in causal and contingency learning show that people’s estimations of the degree of contingency between two events are easily biased by the relative probabilities of those two events. If two events co-occur frequently, then people tend to overestimate the strength of the contingency between them. Traditionally, these biases have been explained in terms of relatively simple single-process models of learning and reasoning. However, more recently some authors have found that these biases do not appear in all dependent variables and have proposed dual-process models to explain these dissociations between variables. In the present paper we review the evidence for dissociations supporting dual-process models and we point out important shortcomings of this literature. Some dissociations seem to be difficult to replicate or poorly generalizable and others can be attributed to methodological artifacts. Overall, we conclude that support for dual-process models of biased contingency detection is scarce and inconclusive. PMID:27025532

Key factors affecting urban runoff pollution under cold climatic conditions

NASA Astrophysics Data System (ADS)

Valtanen, Marjo; Sillanpää, Nora; Setälä, Heikki

2015-10-01

Urban runoff contains various pollutants and has the potential of deteriorating the quality of aquatic ecosystems. In this study our objective is to shed light on the factors that control the runoff water quality in urbanized catchments. The effects of runoff event characteristics, land use type and catchment imperviousness on event mass loads (EML) and event mean concentrations (EMC) were studied during warm and cold periods in three study catchments (6.1, 6.5 and 12.6 ha in size) in the city of Lahti, Finland. Runoff and rainfall were measured continuously for two years at each catchment. Runoff samples were taken for total nutrients (tot-P and tot-N), total suspended solids (TSS), heavy metals (Zn, Cr, Al, Co, Ni, Cu, Pb, Mn) and total organic carbon (TOC). Stepwise multiple linear regression analysis (SMLR) was used to identify general relationships between the following variables: event water quality, runoff event characteristics and catchment characteristics. In general, the studied variables explained 50-90% of the EMLs but only 30-60% of the EMCs, with runoff duration having an important role in most of the SMLR models. Mean runoff intensity or peak flow was also often included in the runoff quality models. Yet, the importance (being the first, second or third best) and role (negative or positive impact) of the explanatory variables varied between the cold and warm period. Land use type often explained cold period concentrations, but imperviousness alone explained EMCs weakly. As for EMLs, the influence of imperviousness and/or land use was season and pollutant dependent. The study suggests that pollutant loads can be - throughout the year - adequately predicted by runoff characteristics given that seasonal differences are taken into account. Although pollutant concentrations were sensitive to variation in seasonal and catchment conditions as well, the accurate estimation of EMCs would require a more complete set of explanatory factors than used in this study.

Remote sensing of PM2.5 during cloudy and nighttime periods using ceilometer backscatter

NASA Astrophysics Data System (ADS)

Li, Siwei; Joseph, Everette; Min, Qilong; Yin, Bangsheng; Sakai, Ricardo; Payne, Megan K.

2017-06-01

Monitoring PM2.5 (particulate matter with aerodynamic diameter d ≤ 2.5 µm) mass concentration has become of more importance recently because of the negative impacts of fine particles on human health. However, monitoring PM2.5 during cloudy and nighttime periods is difficult since nearly all the passive instruments used for aerosol remote sensing are not able to measure aerosol optical depth (AOD) under either cloudy or nighttime conditions. In this study, an empirical model based on the regression between PM2.5 and the near-surface backscatter measured by ceilometers was developed and tested using 6 years of data (2006 to 2011) from the Howard University Beltsville Campus (HUBC) site. The empirical model can explain ˜ 56, ˜ 34 and ˜ 42 % of the variability in the hourly average PM2.5 during daytime clear, daytime cloudy and nighttime periods, respectively. Meteorological conditions and seasons were found to influence the relationship between PM2.5 mass concentration and the surface backscatter. Overall the model can explain ˜ 48 % of the variability in the hourly average PM2.5 at the HUBC site when considering the seasonal variation. The model also was tested using 4 years of data (2012 to 2015) from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, which was geographically and climatologically different from the HUBC site. The results show that the empirical model can explain ˜ 66 and ˜ 82 % of the variability in the daily average PM2.5 at the ARM SGP site and HUBC site, respectively. The findings of this study illustrate the strong need for ceilometer data in air quality monitoring under cloudy and nighttime conditions. Since ceilometers are used broadly over the world, they may provide an important supplemental source of information of aerosols to determine surface PM2.5 concentrations.

[Bioacoustic of the advertisement call of Ceratophrys cranwelli (Anura: Ceratophryidae)].

PubMed

Valetti, Julián Alonso; Salas, Nancy Edith; Martino, Adolfo Ludovico

2013-03-01

The advertisement call plays an important role in the life history of anuran amphibians, mainly during the breeding season. Call features represent an important character to discriminate species, and sound emissions are very effective to assure or reinforce genetic incompatibility, especially in the case of sibling species. Since frogs are ectotherms, acoustic properties of their calls will vary with temperature. In this study, we described the advertisement call of C. cranwelli, quantifying the temperature effect on its components. The acoustic emissions were recorded during 2007 using a DAT record Sony TCD-100 with stereo microphone ECM-MS907 Sony and tape TDK DAT-RGX 60. As males emit their calls floating in temporary ponds, water temperatures were registered after recording the advertisement calls with a digital thermometer TES 1300+/-0.1 degreeC. Altogether, 54 calls from 18 males were analyzed. The temporal variables of each advertisement call were measured using oscillograms and sonograms and the analyses of dominant frequency were performed using a spectrogram. Multiple correlation analysis was used to identify the temperature-dependent acoustic variables and the temperature effect on these variables was quantified using linear regression models. The advertisement call of C. cranwelli consists of a single pulse group. Call duration, Pulse duration and Pulse interval decreased with the temperature, whereas the Pulse rate increased with temperature. The temperature-dependent variables were standardized at 25 degreeC according to the linear regression model obtained. The acoustic variables that were correlated with the temperature are the variables which emissions depend on laryngeal muscles and the temperature constraints the contractile properties of muscles. Our results indicated that temperature explains an important fraction of the variability in some acoustic variables (79% in the Pulse rate), and demonstrated the importance of considering the effect of temperature in acoustic components. The results suggest that acoustic variables show geographic variation to compare data with previous works.

Estimating an area-level socioeconomic status index and its association with colonoscopy screening adherence.

PubMed

Wheeler, David C; Czarnota, Jenna; Jones, Resa M

2017-01-01

Socioeconomic status (SES) is often considered a risk factor for health outcomes. SES is typically measured using individual variables of educational attainment, income, housing, and employment variables or a composite of these variables. Approaches to building the composite variable include using equal weights for each variable or estimating the weights with principal components analysis or factor analysis. However, these methods do not consider the relationship between the outcome and the SES variables when constructing the index. In this project, we used weighted quantile sum (WQS) regression to estimate an area-level SES index and its effect in a model of colonoscopy screening adherence in the Minnesota-Wisconsin Metropolitan Statistical Area. We considered several specifications of the SES index including using different spatial scales (e.g., census block group-level, tract-level) for the SES variables. We found a significant positive association (odds ratio = 1.17, 95% CI: 1.15-1.19) between the SES index and colonoscopy adherence in the best fitting model. The model with the best goodness-of-fit included a multi-scale SES index with 10 variables at the block group-level and one at the tract-level, with home ownership, race, and income among the most important variables. Contrary to previous index construction, our results were not consistent with an assumption of equal importance of variables in the SES index when explaining colonoscopy screening adherence. Our approach is applicable in any study where an SES index is considered as a variable in a regression model and the weights for the SES variables are not known in advance.

The contribution of general and cancer-related variables in explaining physical activity in a breast cancer population 3 weeks to 6 months post-treatment.

PubMed

Charlier, Caroline; Van Hoof, Elke; Pauwels, Evelyn; Lechner, Lilian; Spittaels, Heleen; De Bourdeaudhuij, Ilse

2013-01-01

Physical activity determinants are subject to change when confronted with the diagnosis of 'cancer' and new cancer-related determinants appear. The aim of the present study is to compare the contribution of cancer-related determinants with more general ones in explaining physical activity 3 weeks to 6 months post-treatment. A theory-based and validated questionnaire was used to identify physical activity levels (total and domain-specific) and associated determinants among 464 breast cancer survivors (aged 18 to 65 years) 3 weeks to 6 months post-treatment. Descriptive analyses showed higher scores for general determinants in comparison with cancer-related determinants. Nevertheless, regression analyses showed that both general and cancer-related determinants explained total and domain-specific physical activity. Self-efficacy, enjoyment, social support, lack of time and lack of company were important general determinants. The perception of returning to normal life, cancer-related barriers (fatigue, lack of energy and physical side effects) and self-efficacy in overcoming these barriers were important cancer-related determinants. Although results differed according to the women's working status and the physical activity domain, general self-efficacy explained most physical activity types in both groups. Comparable with the general population, enhancing breast cancer survivors' self-efficacy in being sufficiently physically active seems to be important in physical activity interventions post-treatment. However, interventions should be tailored to the experienced symptoms and working status of the women. Copyright © 2011 John Wiley & Sons, Ltd.

North Tropical Atlantic Climate Variability and Model Biases

NASA Astrophysics Data System (ADS)

Yang, Y.

2017-12-01

Remote forcing from El Niño-Southern Oscillation (ENSO) and local ocean-atmosphere feedback are important for climate variability over the North Tropical Atlantic. These two factors are extracted by the ensemble mean and inter-member difference of a 10-member Pacific Ocean-Global Atmosphere (POGA) experiment, in which sea surface temperatures (SSTs) are restored to the observed anomalies over the tropical Pacific but fully coupled to the atmosphere elsewhere. POGA reasonably captures main features of observed North Tropical Atlantic variability. ENSO forced and local North Tropical Atlantic modes (NTAMs) develop with wind-evaporation-SST feedback, explaining one third and two thirds of total variance respectively. Notable biases, however, exist. The seasonality of the simulated NTAM is delayed by one month, due to the late development of the North Atlantic Oscillation (NAO) in the model. A spurious band of enhanced sea surface temperature (SST) variance (SBEV) is identified over the northern equatorial Atlantic in POGA and 14 out of 23 CMIP5 models. The SBEV is especially pronounced in boreal spring and due to the combined effect of both anomalous atmospheric thermal forcing and oceanic vertical upwelling. While the tropical North Atlantic variability is only weakly correlated with the Atlantic Zonal Mode (AZM) in observations, the SBEV in CMIP5 produces conditions that drive and intensify the AZM variability via triggering the Bjerknes feedback. This partially explains why AZM is strong in some CMIP5 models even though the equatorial cold tongue and easterly trades are biased low.

Orthotic comfort is related to kinematics, kinetics, and EMG in recreational runners.

PubMed

Mündermann, Anne; Nigg, Benno M; Humble, R Neil; Stefanyshyn, Darren J

2003-10-01

The purpose of this study was to determine the relationship between differences in comfort and changes in lower extremity kinematic and kinetic variables and muscle activity in response to foot orthoses. Twenty-one recreational runners volunteered for this study. Three orthotic conditions (posting, custom-molding, and posting and custom-molding) were compared with a control (flat) insert. Lower extremity kinematic, kinetic, and EMG data were collected for 108 trials per subject and condition in nine sessions per subject for overground running at 4 m.s-1. Comfort for all orthotic conditions was assessed in each session using a visual analog scale. The statistical tests used included repeated measures ANOVA, linear regression analysis, and discriminant analysis (alpha = 0.05). Comfort ratings were significantly different between orthotic conditions and the control condition ([lower, upper] confidence limits; posting: [-3.1, -0.8]; molding: [0.4, 3.4]; and posting and molding: [-1.1, 1.9]); 34.9% of differences in comfort were explained by changes in 15 kinematic, kinetic, and EMG variables. The 15 kinematic, kinetic, and EMG variables that partially explained differences in comfort classified 75.0% of cases correctly to the corresponding orthotic condition. In general, comfort is an important and relevant feature of foot orthoses. Evaluations of foot orthoses using comfort do not only reflect subjective perceptions but also differences in functional biomechanical variables. Future research should focus on defining the relationship between comfort and biomechanical variables for material modifications of footwear, different modes of locomotion, and the general population.

Climate mode links to atmospheric carbon monoxide over fire regions

NASA Astrophysics Data System (ADS)

Buchholz, R. R.; Hammerling, D.; Worden, H. M.; Monks, S. A.; Edwards, D. P.; Deeter, M. N.; Emmons, L. K.

2017-12-01

Fire is a strong contributor to variability in atmospheric carbon monoxide (CO), particularly for the Southern Hemisphere and tropics. The magnitude of emissions, such as CO, from biomass burning are related to climate through both the availability and dryness of fuel. We investigate this link between CO and climate using satellite measured CO and climate indices. Interannual variability in satellite-measured CO is determined for the time period covering 2001-2016. We use MOPITT total column retrievals and focus on biomass burning regions of the Southern Hemisphere and tropics. In each of the regions, data driven relationships are determined between CO and climate indices for the climate modes: El Niño Southern Oscillation (ENSO); the Indian Ocean Dipole (IOD); the Tropical Southern Atlantic (TSA); and the Antarctic Oscillation (AAO). Step-wise forward and backward regression combined with the Bayesian Information Criterion is used to select the best predictive model from combinations of lagged indices. We find evidence for the importance of first-order interaction terms of the climate modes when explaining CO variability. Generally, over 50% of the variability can be explained, with over 70% for the Maritime Southeast Asia and North Australasia regions. To help interpret variability, we draw on the chemistry-climate model CAM-chem, which provides information on source contributions and the relative influence of emissions and meteorology. Our results have implications for applications such as air quality forecasting and verifying climate-chemistry models.

Biological community structure on patch reefs in Biscayne National Park, FL, USA

USGS Publications Warehouse

Kuffner, Ilsa B.; Grober-Dunsmore, Rikki; Brock, John C.; Hickey, T. Don

2010-01-01

Coral reef ecosystem management benefits from continual quantitative assessment of the resources being managed, plus assessment of factors that affect distribution patterns of organisms in the ecosystem. In this study, we investigate the relationships among physical, benthic, and fish variables in an effort to help explain the distribution patterns of organisms on patch reefs within Biscayne National Park, FL, USA. We visited a total of 196 randomly selected sampling stations on 12 shallow (<10 m) patch reefs and measured physical variables (e.g., substratum rugosity, substratum type) and benthic and fish community variables. We also incorporated data on substratum rugosity collected remotely via airborne laser surveying (Experimental Advanced Airborne Research Lidar—EAARL). Across all stations, only weak relationships were found between physical, benthic cover, and fish assemblage variables. Much of the variance was attributable to a “reef effect,” meaning that community structure and organism abundances were more variable at stations among reefs than within reefs. However, when the reef effect was accounted for and removed statistically, patterns were detected. Within reefs, juvenile scarids were most abundant at stations with high coverage of the fleshy macroalgae Dictyota spp., and the calcified alga Halimeda tuna was most abundant at stations with low EAARL rugosity. Explanations for the overwhelming importance of “reef” in explaining variance in our dataset could include the stochastic arrangement of organisms on patch reefs related to variable larval recruitment in space and time and/or strong historical effects due to patchy disturbances (e.g., hurricanes, fishing), as well as legacy effects of prior residents (“priority” effects).

Drivers of nutritional change in four South Asian countries: a dynamic observational analysis.

PubMed

Headey, Derek; Hoddinott, John; Park, Seollee

2016-05-01

This paper quantifies the factors explaining long-term improvements in child height for age z-scores in Bangladesh (1996/1997-2011), India (1992/1993-2005/2006), Nepal (1997-2011) and Pakistan (1991-2013). We apply the same statistical techniques to data from a common data source from which we have extracted a set of common explanatory variables that capture 'nutrition-sensitive' factors. Three are particularly important in explaining height for age z-score changes over these timeframes: improvements in material well-being; increases in female education; and improvements in sanitation. These factors have comparable associations across all four countries. © 2016 The Authors. Maternal & Child Nutrition published by John Wiley & Sons Ltd.

Drivers of nutritional change in four South Asian countries: a dynamic observational analysis

PubMed Central

Hoddinott, John; Park, Seollee

2016-01-01

Abstract This paper quantifies the factors explaining long‐term improvements in child height for age z‐scores in Bangladesh (1996/1997–2011), India (1992/1993–2005/2006), Nepal (1997–2011) and Pakistan (1991–2013). We apply the same statistical techniques to data from a common data source from which we have extracted a set of common explanatory variables that capture ‘nutrition‐sensitive’ factors. Three are particularly important in explaining height for age z‐score changes over these timeframes: improvements in material well‐being; increases in female education; and improvements in sanitation. These factors have comparable associations across all four countries. PMID:27187917

Do Riparian Buffers Protect Stream Invertebrate Communities in South American Atlantic Forest Agricultural Areas?

PubMed

Hunt, L; Marrochi, N; Bonetto, C; Liess, M; Buss, D F; Vieira da Silva, C; Chiu, M-C; Resh, V H

2017-12-01

We investigated the influence and relative importance of insecticides and other agricultural stressors in determining variability in invertebrate communities in small streams in intensive soy-production regions of Brazil and Paraguay. In Paraguay we sampled 17 sites on tributaries of the Pirapó River in the state of Itapúa and in Brazil we sampled 18 sites on tributaries of the San Francisco River in the state of Paraná. The riparian buffer zones generally contained native Atlantic forest remnants and/or introduced tree species at various stages of growth. In Brazil the stream buffer width was negatively correlated with sediment insecticide concentrations and buffer width was found to have moderate importance in mitigating effects on some sensitive taxa such as mayflies. However, in both regions insecticides had low relative importance in explaining variability in invertebrate communities, while various habitat parameters were more important. In Brazil, the percent coverage of soft depositional sediment in streams was the most important agriculture-related explanatory variable, and the overall stream-habitat score was the most important variable in Paraguay streams. Paraguay and Brazil both have laws requiring forested riparian buffers. The ample forested riparian buffer zones typical of streams in these regions are likely to have mitigated the effects of pesticides on stream invertebrate communities. This study provides evidence that riparian buffer regulations in the Atlantic Forest region are protecting stream ecosystems from pesticides and other agricultural stressors. Further studies are needed to determine the minimum buffer widths necessary to achieve optimal protection.

A Comparative Study on the Teaching Profession in Turkey and South Korea: Secondary Analysis of TALIS 2008 Data in Relation to Teacher Self-Efficacy

ERIC Educational Resources Information Center

Aslan, Berna

2015-01-01

Problem Statement: Teacher self-efficacy is important factor for school and student success. This study investigates the variables that explain teacher self-efficacy in Turkey and South Korea according to TALIS 2008 data. A detailed comparison was conducted and the state of the teaching profession in both countries is discussed. Purpose of the…

Tannat grape composition responses to spatial variability of temperature in an Uruguay's coastal wine region

NASA Astrophysics Data System (ADS)

Fourment, Mercedes; Ferrer, Milka; González-Neves, Gustavo; Barbeau, Gérard; Bonnardot, Valérie; Quénol, Hervé

2017-09-01

Spatial variability of temperature was studied in relation to the berry basic composition and secondary compounds of the Tannat cultivar at harvest from vineyards located in Canelones and Montevideo, the most important wine region of Uruguay. Monitoring of berries and recording of temperature were performed in 10 commercial vineyards of Tannat situated in the southern coastal wine region of the country for three vintages (2012, 2013, and 2014). Results from a multivariate correlation analysis between berry composition and temperature over the three vintages showed that (1) Tannat responses to spatial variability of temperature were different over the vintages, (2) correlations between secondary metabolites and temperature were higher than those between primary metabolites, and (3) correlation values between berry composition and climate variables increased when ripening occurred under dry conditions (below average rainfall). For a particular studied vintage (2013), temperatures explained 82.5% of the spatial variability of the berry composition. Daily thermal amplitude was found to be the most important spatial mode of variability with lower values recorded at plots nearest to the sea and more exposed to La Plata River. The highest levels in secondary compounds were found in berries issued from plots situated as far as 18.3 km from La Plata River. The increasing knowledge of temperature spatial variability and its impact on grape berry composition contributes to providing possible issues to adapt grapevine to climate change.

Clinical Trials With Large Numbers of Variables: Important Advantages of Canonical Analysis.

PubMed

Cleophas, Ton J

2016-01-01

Canonical analysis assesses the combined effects of a set of predictor variables on a set of outcome variables, but it is little used in clinical trials despite the omnipresence of multiple variables. The aim of this study was to assess the performance of canonical analysis as compared with traditional multivariate methods using multivariate analysis of covariance (MANCOVA). As an example, a simulated data file with 12 gene expression levels and 4 drug efficacy scores was used. The correlation coefficient between the 12 predictor and 4 outcome variables was 0.87 (P = 0.0001) meaning that 76% of the variability in the outcome variables was explained by the 12 covariates. Repeated testing after the removal of 5 unimportant predictor and 1 outcome variable produced virtually the same overall result. The MANCOVA identified identical unimportant variables, but it was unable to provide overall statistics. (1) Canonical analysis is remarkable, because it can handle many more variables than traditional multivariate methods such as MANCOVA can. (2) At the same time, it accounts for the relative importance of the separate variables, their interactions and differences in units. (3) Canonical analysis provides overall statistics of the effects of sets of variables, whereas traditional multivariate methods only provide the statistics of the separate variables. (4) Unlike other methods for combining the effects of multiple variables such as factor analysis/partial least squares, canonical analysis is scientifically entirely rigorous. (5) Limitations include that it is less flexible than factor analysis/partial least squares, because only 2 sets of variables are used and because multiple solutions instead of one is offered. We do hope that this article will stimulate clinical investigators to start using this remarkable method.

The History of Variable Stars: A Fresh Look

NASA Astrophysics Data System (ADS)

Hatch, R. A.

2012-06-01

(Abstract only) For historians of astronomy, variable stars are important for a simple reason - stars change. But good evidence suggests this is a very modern idea. Over the millennia, our species has viewed stars as eternal and unchanging, forever fixed in time and space - indeed, the Celestial Dance was a celebration of order, reason, and stability. But everything changed in the period between Copernicus and Newton. According to tradition, two New Stars announced the birth of the New Science. Blazing across the celestial stage, Tycho's Star (1572) and Kepler's Star (1604) appeared dramatically - and just as unexpectedly - disappeared forever. But variable stars were different. Mira Ceti, the oldest, brightest, and most controversial variable star, was important because it appeared and disappeared again and again. Mira was important because it did not go away. The purpose of this essay is to take a fresh look at the history of variable stars. In re-thinking the traditional narrative, I begin with the first sightings of David Fabricius (1596) and his contemporaries - particularly Hevelius (1662) and Boulliau (1667) - to new traditions that unfolded from Newton and Maupertuis to Herschel (1780) and Pigott (1805). The essay concludes with important 19th-century developments, particularly by Argelander (1838), Pickering (1888), and Lockyer (1890). Across three centuries, variable stars prompted astronomers to re-think all the ways that stars were no longer "fixed." New strategies were needed. Astronomers needed to organize, to make continuous observations, to track changing magnitudes, and to explain stellar phases. Importantly - as Mira suggested from the outset - these challenges called for an army of observers with the discipline of Spartans. But recruiting that army required a strategy, a set of theories with shared expectations. Observation and theory worked hand-in-hand. In presenting new historical evidence from neglected printed sources and unpublished manuscripts, this essay aims to offer a fresh look at the history of variable stars.

Physician attitudes toward advanced directives: a literature review of variables impacting on physicians attitude toward advance directives.

PubMed

Coleman, Albert M E

2013-11-01

To review physician's attitudes as well as the variables that may impact on physicians' attitude toward advance directives (ADs). Literature review of 17 published articles, covering the period 1989 to 2011. Physicians overall have a positive attitude toward patients' AD. However, other factors affect this "general positive attitude." These factors influence the attitude-behavior relationship of physicians, and hence their actual practice in relation to patients' AD. The findings from this review are of importance in explaining the differences in the attitude of physicians toward AD and their compliance. This raises the issue of consideration of other ethical paradigms/theories in the clinical context other than the framework of "principlism-"based autonomy, on which AD leans on. This is important in light of the pluralism of ethical theories.

Effects of land-use and climate on Holocene vegetation composition in northern Europe

NASA Astrophysics Data System (ADS)

Marquer, Laurent; Gaillard, Marie-José; Sugita, Shinya; Poska, Anneli; Trondman, Anna-Kari; Mazier, Florence; Nielsen, Anne Birgitte; Fyfe, Ralph; Jönsson, Anna Maria

2016-04-01

Prior to the advent of agriculture, broad-scale vegetation patterns in Europe were controlled primarily by climate. Early agriculture can be detected in palaeovegetation records, but the relative extent to which past regional vegetation was climatically or anthropogenically-forced is of current scientific interest. Using comparisons of transformed pollen data, climate-model data, dynamic vegetation model simulations and anthropogenic land-cover change data, this study aims to estimate the relative impacts of human activities and climate on the Holocene vegetation composition of northern Europe at a subcontinental scale. The REVEALS model was used for pollen-based quantitative reconstruction of vegetation (RV). Climate variables from ECHAM and the extent of human deforestation from KK10 were used as explanatory variables to evaluate their respective impacts on RV. Indices of vegetation-composition changes based on RV and climate-induced vegetation simulated by the LPJ-GUESS model (LPJG) were used to assess the relative importance of climate and anthropogenic impacts. The results show that climate is the major predictor of Holocene vegetation changes until 5000 years ago. The similarity in rate of change and turnover between RV and LPJG decreases after this time. Changes in RV explained by climate and KK10 vary for the last 2000 years; the similarity in rate of change, turnover, and evenness between RV and LPJG decreases to the present. The main conclusions provide important insights on Neolithic forest clearances that affected regional vegetation from 6700 years ago, although climate (temperature and precipitation) still was a major driver of vegetation change (explains 37% of the variation) at the subcontinental scale. Land use became more important around 5000-4000 years ago, while the influence of climate decreased (explains 28% of the variation). Land-use affects all indices of vegetation compositional change during the last 2000 years; the influence of climate on vegetation, although reduced, remains at 16% until modern time while land-use explains 7%, which underlines that North-European vegetation is still climatically sensitive and, therefore, responds strongly to ongoing climate change.

Oral health care activities performed by caregivers for institutionalized elderly in Barcelona-Spain.

PubMed

Cornejo-Ovalle, Marco; Costa-de-Lima, Kenio; Pérez, Glória; Borrell, Carme; Casals-Peidro, Elías

2013-07-01

To describe the frequency of brushing teeth and cleaning of dentures, performed by caregivers, for institutionalized elderly people. A cross-sectional study in a sample of 196 caregivers of 31 health centers in Barcelona. The dependent variables were frequency of dental brushing and frequency of cleaning of dentures of the elderly by caregivers. The independent variables were characteristics of caregivers and institutions. We performed bivariate and multivariate descriptive analyses. Robust Poisson regression models were fitted to determine factors associated with the dependent variables and to assess the strength of the association. 83% of caregivers were women, 79% worked on more than one shift, 42% worked only out of necessity, 92% were trained to care for elderly persons, 67% were trained in oral hygiene care for the elderly, and 73% recognized the existence of institutional protocols on oral health among residents. The variables explaining the lower frequency of brushing teeth by caregivers for the elderly, adjusted for the workload, were: no training in the care of elderly persons (PRa 1.7 CI95%: 1.6-1.8), not fully agreeing with the importance of oral health care of the elderly (PRa 2.5 CI95%: 1.5-4.1) and not knowing of the existence of oral health protocols (PRa 1.8 CI95% 1.2-2.6). The variables that explain the lower frequency of cleaning dentures, adjusted for the workload, were lack of training in elderly care (PRa 1.7 CI95%: 1.3-1.9) and not knowing of the existence of protocols (PRa 3.7 CI95%: 1.6-8.7). The majority of caregivers perform activities of oral health care for the elderly at least once per day. The frequency of this care depends mainly on whether caregivers are trained to perform these activities, the importance given to oral health, the workload of caregivers and the existence of institutional protocols on oral health of institutionalized elderly persons.

Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales

NASA Technical Reports Server (NTRS)

Zeng, Fanwei; Collatz, George James; Pinzon, Jorge E.; Ivanoff, Alvaro

2013-01-01

Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.

Controls on the spatial variability of key soil properties: comparing field data with a mechanistic soilscape evolution model

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Giraldez, J. V.

2016-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of a geostatistical versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

Pain Catastrophizing and Pain-Related Fear in Osteoarthritis Patients: Relationships to Pain and Disability

PubMed Central

Somers, Tamara J.; Keefe, Francis J.; Pells, Jennifer J.; Dixon, Kim E.; Waters, Sandra J.; Riordan, Paul A.; Blumenthal, James A.; McKee, Daphne C.; LaCaille, Lara; Tucker, Jessica M.; Schmitt, Daniel; Caldwell, David S.; Kraus, Virginia B.; Sims, Ershela L.; Shelby, Rebecca A.; Rice, John R.

2009-01-01

This study examined the degree to which pain catastrophizing and pain-related fear explain pain, psychological disability, physical disability, and walking speed in patients with osteoarthritis (OA) of the knee. Participants in this study were 106 individuals diagnosed as having OA of at least one knee, who reported knee pain persisting six months or longer. Results suggest that pain catastrophizing explained a significant proportion (all P's ≤ 0.05) of variance in measures of pain (partial r2 [pr2] = 0.10), psychological disability (pr2 = 0.20), physical disability (pr2 = 0.11), and gait velocity at normal (pr2 = 0.04), fast (pr2 = 0.04), and intermediate speeds (pr2 = 0.04). Pain-related fear explained a significant proportion of the variance in measures of psychological disability (pr2 = 0.07) and walking at a fast speed (pr2 = 0.05). Pain cognitions, particularly pain catastrophizing, appear to be important variables in understanding pain, disability, and walking at normal, fast, and intermediate speeds in knee OA patients. Clinicians interested in understanding variations in pain and disability in this population may benefit by expanding the focus of their inquiries beyond traditional medical and demographic variables to include an assessment of pain catastrophizing and pain-related fear. PMID:19041218

Development of a stock-recruitment model and assessment of biological reference points for the Lake Erie walleye fishery

USGS Publications Warehouse

Zhao, Yingming; Kocovsky, Patrick M.; Madenjian, Charles P.

2013-01-01

We developed an updated stock–recruitment relationship for Lake Erie Walleye Sander vitreus using the Akaike information criterion model selection approach. Our best stock–recruitment relationship was a Ricker spawner–recruit function to which spring warming rate was added as an environmental variable, and this regression model explained 39% of the variability in Walleye recruitment over the 1978 through 2006 year-classes. Thus, most of the variability in Lake Erie Walleye recruitment appeared to be attributable to factors other than spawning stock size and spring warming rate. The abundance of age-0 Gizzard Shad Dorosoma cepedianum, which was an important term in previous models, may still be an important factor for Walleye recruitment, but poorer ability to monitor Gizzard Shad since the late 1990s could have led to that term failing to appear in our best model. Secondly, we used numerical simulation to demonstrate how to use the stock recruitment relationship to characterize the population dynamics (such as stable age structure, carrying capacity, and maximum sustainable yield) and some biological reference points (such as fishing rates at different important biomass or harvest levels) for an age-structured population in a deterministic way.

Exploring public databases to characterize urban flood risks in Amsterdam

NASA Astrophysics Data System (ADS)

Gaitan, Santiago; ten Veldhuis, Marie-claire; van de Giesen, Nick

2015-04-01

Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to decide upon investment to reduce their impacts. Obvious flooding factors affecting flood risk include sewer systems performance and urban topography. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall and socioeconomic characteristics may help to explain probability and impacts of urban flooding. Several public databases were analyzed: complaints about flooding made by citizens, rainfall depths (15 min and 100 Ha spatio-temporal resolution), grids describing number of inhabitants, income, and housing price (1Ha and 25Ha resolution); and buildings age. Data analysis was done using Python and GIS programming, and included spatial indexing of data, cluster analysis, and multivariate regression on the complaints. Complaints were used as a proxy to characterize flooding impacts. The cluster analysis, run for all the variables except the complaints, grouped part of the grid-cells of central Amsterdam into a highly differentiated group, covering 10% of the analyzed area, and accounting for 25% of registered complaints. The configuration of the analyzed variables in central Amsterdam coincides with a high complaint count. Remaining complaints were evenly dispersed along other groups. An adjusted R2 of 0.38 in the multivariate regression suggests that explaining power can improve if additional variables are considered. While rainfall intensity explained 4% of the incidence of complaints, population density and building age significantly explained around 20% each. Data mining of public databases proved to be a valuable tool to identify factors explaining variability in occurrence of urban pluvial flooding, though additional variables must be considered to fully explain flood risk variability.

Socioeconomic status, parenting, and externalizing problems in African American single-mother homes: A person-oriented approach.

PubMed

Anton, Margaret T; Jones, Deborah J; Youngstrom, Eric A

2015-06-01

African American youth, particularly those from single-mother homes, are overrepresented in statistics on externalizing problems. The family is a central context in which to understand externalizing problems; however, reliance on variable-oriented approaches to the study of parenting, which originate from work with intact, middle-income, European American families, may obscure important information regarding variability in parenting styles among African American single mothers, and in turn, variability in youth outcomes as well. The current study demonstrated that within African American single-mother families: (a) a person-, rather than variable-, oriented approach to measuring parenting style may further elucidate variability; (b) socioeconomic status may provide 1 context within which to understanding variability in parenting style; and (c) 1 marker of socioeconomic status, income, and parenting style may each explain variability in youth externalizing problems; however, the interaction between income and parenting style was not significant. Findings have potential implications for better understanding the specific contexts in which externalizing problems may be most likely to occur within this at-risk and underserved group. (c) 2015 APA, all rights reserved).

Organizational variables on nurses' job performance in Turkey: nursing assessments.

PubMed

Top, Mehmet

2013-01-01

The purpose of this study was to describe the influence of organizational variables on hospital staff nurses' job performance as reported by staff nurses in two cities in Turkey. Hospital ownership status, employment status were examined for their effect on this influence. The reported influence of organizational variables on job performance was measured by a questionnaire developed for this study. Nurses were asked to evaluate the influence of 28 organizational variables on their job performance using a five-point Likert-type scale (1- Never effective, 5- Very effective). The study used comparative and descriptive study design. The staff nurses who were included in this study were 831 hospital staff nurses. Descriptive statistics, frequencies, t-test, ANOVA and factor analysis were used for data analysis. The study showed the relative importance of the 28 organizational variables in influencing nurses' job performance. Nurses in this study reported that workload and technological support are the most influential organizational variables on their job performance. Factor analysis yielded a five-factor model that explained 53.99% of total variance. Administratively controllable influence job organizational variables influence job performance of nurses in different magnitude.

Socioeconomic Status, Parenting, and Externalizing Problems in African American Single-Mother Homes: A Person-Oriented Approach

PubMed Central

Anton, Margaret T.; Jones, Deborah J.; Youngstrom, Eric A.

2016-01-01

African American youth, particularly those from single-mother homes, are overrepresented in statistics on externalizing problems. The family is a central context in which to understand externalizing problems; however, reliance on variable-oriented approaches to the study of parenting, which originate from work with intact, middle-income, European American families, may obscure important information regarding variability in parenting styles among African American single mothers, and in turn, variability in youth outcomes as well. The current study demonstrated that within African American single-mother families: (a) a person-, rather than variable-, oriented approach to measuring parenting style may further elucidate variability; (b) socioeconomic status may provide 1 context within which to understanding variability in parenting style; and (c) 1 marker of socioeconomic status, income, and parenting style may each explain variability in youth externalizing problems; however, the interaction between income and parenting style was not significant. Findings have potential implications for better understanding the specific contexts in which externalizing problems may be most likely to occur within this at-risk and underserved group. PMID:26053349

Joint variability of global runoff and global sea surface temperatures

USGS Publications Warehouse

McCabe, G.J.; Wolock, D.M.

2008-01-01

Global land surface runoff and sea surface temperatures (SST) are analyzed to identify the primary modes of variability of these hydroclimatic data for the period 1905-2002. A monthly water-balance model first is used with global monthly temperature and precipitation data to compute time series of annual gridded runoff for the analysis period. The annual runoff time series data are combined with gridded annual sea surface temperature data, and the combined dataset is subjected to a principal components analysis (PCA) to identify the primary modes of variability. The first three components from the PCA explain 29% of the total variability in the combined runoff/SST dataset. The first component explains 15% of the total variance and primarily represents long-term trends in the data. The long-term trends in SSTs are evident as warming in all of the oceans. The associated long-term trends in runoff suggest increasing flows for parts of North America, South America, Eurasia, and Australia; decreasing runoff is most notable in western Africa. The second principal component explains 9% of the total variance and reflects variability of the El Ni??o-Southern Oscillation (ENSO) and its associated influence on global annual runoff patterns. The third component explains 5% of the total variance and indicates a response of global annual runoff to variability in North Aflantic SSTs. The association between runoff and North Atlantic SSTs may explain an apparent steplike change in runoff that occurred around 1970 for a number of continental regions.

[Variations among Spanish regions in the use of three cardiovascular technologies].

PubMed

Fitch-Warner, Kathryn; García de Yébenes, María J; Lázaro y de Mercado, Pablo; Belaza-Santurde, Javier

2006-12-01

There is evidence that some geographic variations in the use of medical technologies are not explained by differences in disease burden. The objectives of this study were to quantify variability in the use of percutaneous coronary intervention (PCI), implantable cardioverter-defibrillators (ICDs), and cardiac resynchronization therapy (CRT) in Spanish autonomous regions and to try to explain the variability found for the first two technologies. Linear regression models were developed in which the number of procedures performed per million population (pmp) in 2003 in each autonomous region was the dependent variable. Independent variables used included indices of technology provision, regional wealth, and disease burden. For PCI, the mean utilization rate for the whole of Spain was 1038 procedures pmp, with a high-low ratio of 1.95. Differences in gross domestic product explained 21% of the variability, but there was no relationship between the number of procedures performed and disease burden. For ICDs, the mean number of procedures performed in the whole of Spain was 46 pmp, with a high-low ratio of 3.04. As for PCI, differences in regional wealth explained 40% of the variability, with disease burden making no contribution. For CRT, the mean number of procedures performed in Spain in 2003 was 15 pmp, with a high-low ratio of 15.7. The considerable regional variation that exists in the use of these three medical technologies is principally explained by differences in regional wealth and not in disease burden.

Understanding the spatial complexity of surface hoar from slope to range scale

NASA Astrophysics Data System (ADS)

Hendrikx, J.

2015-12-01

Surface hoar, once buried, is a common weak layer type in avalanche accidents in continental and intermountain snowpacks around the World. Despite this, there is still limited understanding of the spatial variability in both the formation of, and eventual burial of, surface hoar at spatial scales which are of critical importance to avalanche forecasters. While it is relatively well understood that aspect plays an important role in the spatial location of the formation, and burial of these grain forms, due to the unequal distribution of incoming radiation, this factor alone does not explain the complex and often confusing spatial pattern of these grains forms throughout the landscape at different spatial scales. In this paper we present additional data from a unique data set including over two hundred days of manual observations of surface hoar at sixteen locations on Pioneer Mountain at the Yellowstone Club in southwestern Montana. Using this wealth of observational data located on different aspects, elevations and exposures, coupled with detailed meteorological observations, and detailed slope scale observation, we examine the spatial variability of surface hoar at this scale, and examine the factors that control its spatial distribution. Our results further supports our preliminary work, which shows that small-scale slope conditions, meteorological differences, and local scale lapse rates, can greatly influence the spatial variability of surface hoar, over and above that which aspect alone can explain. These results highlight our incomplete understanding of the processes at both the slope and range scale, and are likely to have implications for both regional and local scale avalanche forecasting in environments where surface hoar cause ongoing instabilities.

Hierarchical analysis of cardiovascular risk factors in relation to the development of acute coronary syndromes, in different parts of Greece: the CARDIO2000 study.

PubMed

Panagiotakos, Demosthenes B; Pitsavos, Christos; Chrysohoou, Christine; Stefanadis, Christodoulos

2008-01-01

During 2000 to 2002, 700 men (59 +/- 10 years) and 148 women (65 +/- 9 years) patients with first event of an ACS were randomly selected from cardiology clinics of Greek regions. Afterwards, 1078 population-based, age-matched and sex-matched controls were randomly selected from the same hospitals. The frequency ratio between men and women in the case series of patients was about 4:1, in both south and north Greek areas. Hierarchical classification analysis showed that for north Greek areas family history of coronary heart disease, hypercholesterolemia, hypertension, diabetes (explained variability 35%), and less significantly, dietary habits, smoking, body mass index, and physical activity status (explained variability 4%) were associated with the development of ACS, whereas for south Greek areas hypercholesterolemia, family history of coronary heart disease, diabetes, smoking, hypertension, dietary habits, physical activity (explained variability 34%), and less significantly body mass index (explained variability <1%), were associated with the development of the disease.

Tuned Normalization Explains the Size of Attention Modulations

PubMed Central

Ni, Amy M.; Ray, Supratim; Maunsell, John H. R.

2012-01-01

SUMMARY The effect of attention on firing rates varies considerably within a single cortical area. The firing rate of some neurons is greatly modulated by attention while others are hardly affected. The reason for this variability across neurons is unknown. We found that the variability in attention modulation across neurons in area MT of macaques can be well explained by variability in the strength of tuned normalization across neurons. The presence of tuned normalization also explains a striking asymmetry in attention effects within neurons: when two stimuli are in a neuron’s receptive field, directing attention to the preferred stimulus modulates firing rates more than directing attention to the non-preferred stimulus. These findings show that much of the neuron-to-neuron variability in modulation of responses by attention depends on variability in the way the neurons process multiple stimuli, rather than differences in the influence of top-down signals related to attention. PMID:22365552

Tuned normalization explains the size of attention modulations.

PubMed

Ni, Amy M; Ray, Supratim; Maunsell, John H R

2012-02-23

The effect of attention on firing rates varies considerably within a single cortical area. The firing rate of some neurons is greatly modulated by attention while others are hardly affected. The reason for this variability across neurons is unknown. We found that the variability in attention modulation across neurons in area MT of macaques can be well explained by variability in the strength of tuned normalization across neurons. The presence of tuned normalization also explains a striking asymmetry in attention effects within neurons: when two stimuli are in a neuron's receptive field, directing attention to the preferred stimulus modulates firing rates more than directing attention to the nonpreferred stimulus. These findings show that much of the neuron-to-neuron variability in modulation of responses by attention depends on variability in the way the neurons process multiple stimuli, rather than differences in the influence of top-down signals related to attention. Copyright © 2012 Elsevier Inc. All rights reserved.

Operator- and software-related post-experimental variability and source of error in 2-DE analysis.

PubMed

Millioni, Renato; Puricelli, Lucia; Sbrignadello, Stefano; Iori, Elisabetta; Murphy, Ellen; Tessari, Paolo

2012-05-01

In the field of proteomics, several approaches have been developed for separating proteins and analyzing their differential relative abundance. One of the oldest, yet still widely used, is 2-DE. Despite the continuous advance of new methods, which are less demanding from a technical standpoint, 2-DE is still compelling and has a lot of potential for improvement. The overall variability which affects 2-DE includes biological, experimental, and post-experimental (software-related) variance. It is important to highlight how much of the total variability of this technique is due to post-experimental variability, which, so far, has been largely neglected. In this short review, we have focused on this topic and explained that post-experimental variability and source of error can be further divided into those which are software-dependent and those which are operator-dependent. We discuss these issues in detail, offering suggestions for reducing errors that may affect the quality of results, summarizing the advantages and drawbacks of each approach.

Landscape correlates of breeding bird richness across the United States mid-Atlantic region

USGS Publications Warehouse

Jones, K.B.; Neale, A.C.; Nash, M.S.; Riitters, K.H.; Wickham, J.D.; O'Neill, R. V.; Van Remortel, R. D.

2000-01-01

Using a new set of landscape indicator data generated by the U.S.EPA, and a comprehensive breeding bird database from the National Breeding Bird Survey, we evaluated associations between breeding bird richness and landscape characteristics across the entire mid-Atlantic region of the United States. We evaluated how these relationships varied among different groupings (guilds) of birds based on functional, structural, and compositional aspects of individual species demographics. Forest edge was by far the most important landscape attribute affecting the richness of the lumped specialist and generalist guilds; specialist species richness was negatively associated with forest edge and generalist richness was positively associated with forest edge. Landscape variables (indicators) explained a greater proportion of specialist species richness than the generalist guild (46% and 31%, respectively). The lower value in generalists may reflect freer-scale distributions of open habitat that go undetected by the Landsat satellite, open habitats created by roads (the areas from which breeding bird data are obtained), and the lumping of a wide variety of species into the generalist category. A further breakdown of species into 16 guilds showed considerable variation in the response of breeding birds to landscape conditions; forest obligate species had the strongest association with landscape indicators measured in this study (55% of the total variation explained) and forest generalists and open ground nesters the lowest (17% of the total variation explained). The variable response of guild species richness to landscape pattern suggests that one must consider species' demographics when assessing the consequences of landscape change on breeding birds.Using a new set of landscape indicator data generated by the U.S. EPA, and a comprehensive breeding bird database from the National Breeding Bird Survey, we evaluated associations between breeding bird richness and landscape characteristics across the entire mid-Atlantic region of the United States. We evaluated how these relationships varied among different groupings (guilds) of birds based on functional, structural, and compositional aspects of individual species demographics. Forest edge was by far the most important landscape attribute affecting the richness of the lumped specialist and generalist guilds; specialist species richness was negatively associated with forest edge and generalist richness was positively associated with forest edge. Landscape variables (indicators) explained a greater proportion of specialist species richness than the generalist guild (46% and 31%, respectively). The lower value in generalists may reflect finer-scale distributions of open habitat that go undetected by the Landsat satellite, open habitats created by roads (the areas from which breeding bird data are obtained), and the lumping of a wide variety of species into the generalist category. A further breakdown of species into 16 guilds showed considerable variation in the response of breeding birds to landscape conditions; forest obligate species had the strongest association with landscape indicators measured in this study (55% of the total variation explained) and forest generalists and open ground nesters the lowest (17% of the total variation explained). The variable response of guild species richness to landscape pattern suggests that one must consider species' demographics when assessing the consequences of landscape change on breeding birds.

Rotary ultrasonic machining of CFRP: a mechanistic predictive model for cutting force.

PubMed

Cong, W L; Pei, Z J; Sun, X; Zhang, C L

2014-02-01

Cutting force is one of the most important output variables in rotary ultrasonic machining (RUM) of carbon fiber reinforced plastic (CFRP) composites. Many experimental investigations on cutting force in RUM of CFRP have been reported. However, in the literature, there are no cutting force models for RUM of CFRP. This paper develops a mechanistic predictive model for cutting force in RUM of CFRP. The material removal mechanism of CFRP in RUM has been analyzed first. The model is based on the assumption that brittle fracture is the dominant mode of material removal. CFRP micromechanical analysis has been conducted to represent CFRP as an equivalent homogeneous material to obtain the mechanical properties of CFRP from its components. Based on this model, relationships between input variables (including ultrasonic vibration amplitude, tool rotation speed, feedrate, abrasive size, and abrasive concentration) and cutting force can be predicted. The relationships between input variables and important intermediate variables (indentation depth, effective contact time, and maximum impact force of single abrasive grain) have been investigated to explain predicted trends of cutting force. Experiments are conducted to verify the model, and experimental results agree well with predicted trends from this model. Copyright © 2013 Elsevier B.V. All rights reserved.

Depressive symptoms in institutionalized older adults

PubMed Central

Santiago, Lívia Maria; Mattos, Inês Echenique

2014-01-01

OBJECTIVE To estimate the prevalence of depressive symptoms among institutionalized elderly individuals and to analyze factors associated with this condition. METHODS This was a cross-sectional study involving 462 individuals aged 60 or older, residents in long stay institutions in four Brazilian municipalities. The dependent variable was assessed using the 15-item Geriatric Depression Scale. Poisson’s regression was used to evaluate associations with co-variables. We investigated which variables were most relevant in terms of presence of depressive symptoms within the studied context through factor analysis. RESULTS Prevalence of depressive symptoms was 48.7%. The variables associated with depressive symptoms were: regular/bad/very bad self-rated health; comorbidities; hospitalizations; and lack of friends in the institution. Five components accounted for 49.2% of total variance of the sample: functioning, social support, sensory deficiency, institutionalization and health conditions. In the factor analysis, functionality and social support were the components which explained a large part of observed variance. CONCLUSIONS A high prevalence of depressive symptoms, with significant variation in distribution, was observed. Such results emphasize the importance of health conditions and functioning for institutionalized older individuals developing depression. They also point to the importance of providing opportunities for interaction among institutionalized individuals. PMID:24897042

Geomagnetic activity: Dependence on solar wind parameters

NASA Technical Reports Server (NTRS)

Svalgaard, L.

1977-01-01

Current ideas about the interaction between the solar wind and the earth's magnetosphere are reviewed. The solar wind dynamic pressure as well as the influx of interplanetary magnetic field lines are both important for the generation of geomagnetic activity. The influence of the geometry of the situation as well as the variability of the interplanetary magnetic field are both found to be important factors. Semi-annual and universal time variations are discussed as well as the 22-year cycle in geomagnetic activity. All three are found to be explainable by the varying geometry of the interaction. Long term changes in geomagnetic activity are examined.

Linking landscape characteristics to local grizzly bear abundance using multiple detection methods in a hierarchical model

USGS Publications Warehouse

Graves, T.A.; Kendall, Katherine C.; Royle, J. Andrew; Stetz, J.B.; Macleod, A.C.

2011-01-01

Few studies link habitat to grizzly bear Ursus arctos abundance and these have not accounted for the variation in detection or spatial autocorrelation. We collected and genotyped bear hair in and around Glacier National Park in northwestern Montana during the summer of 2000. We developed a hierarchical Markov chain Monte Carlo model that extends the existing occupancy and count models by accounting for (1) spatially explicit variables that we hypothesized might influence abundance; (2) separate sub-models of detection probability for two distinct sampling methods (hair traps and rub trees) targeting different segments of the population; (3) covariates to explain variation in each sub-model of detection; (4) a conditional autoregressive term to account for spatial autocorrelation; (5) weights to identify most important variables. Road density and per cent mesic habitat best explained variation in female grizzly bear abundance; spatial autocorrelation was not supported. More female bears were predicted in places with lower road density and with more mesic habitat. Detection rates of females increased with rub tree sampling effort. Road density best explained variation in male grizzly bear abundance and spatial autocorrelation was supported. More male bears were predicted in areas of low road density. Detection rates of males increased with rub tree and hair trap sampling effort and decreased over the sampling period. We provide a new method to (1) incorporate multiple detection methods into hierarchical models of abundance; (2) determine whether spatial autocorrelation should be included in final models. Our results suggest that the influence of landscape variables is consistent between habitat selection and abundance in this system.

Predicting assemblages and species richness of endemic fish in the upper Yangtze River.

PubMed

He, Yongfeng; Wang, Jianwei; Lek-Ang, Sithan; Lek, Sovan

2010-09-01

The present work describes the ability of two modeling methods, Classification and Regression Tree (CART) and Random Forest (RF), to predict endemic fish assemblages and species richness in the upper Yangtze River, and then to identify the determinant environmental factors contributing to the models. The models included 24 predictor variables and 2 response variables (fish assemblage and species richness) for a total of 46 site units. The predictive quality of the modeling approaches was judged with a leave-one-out validation procedure. There was an average success of 60.9% and 71.7% to assign each site unit to the correct assemblage of fish, and 73% and 84% to explain the variance in species richness, by using CART and RF models, respectively. RF proved to be better than CART in terms of accuracy and efficiency in ecological applications. In any case, the mixed models including both land cover and river characteristic variables were more powerful than either individual one in explaining the endemic fish distribution pattern in the upper Yangtze River. For instance, altitude, slope, length, discharge, runoff, farmland and alpine and sub-alpine meadow played important roles in driving the observed endemic fish assemblage structure, while farmland, slope grassland, discharge, runoff, altitude and drainage area in explaining the observed patterns of endemic species richness. Therefore, the various effects of human activity on natural aquatic ecosystems, in particular, the flow modification of the river and the land use changes may have a considerable effect on the endemic fish distribution patterns on a regional scale. Copyright 2010 Elsevier B.V. All rights reserved.

Geomorphic determinants of species composition of alpine tundra, Glacier National Park, U.S.A.

USGS Publications Warehouse

George P. Malanson,; Bengtson, Lindsey E.; Fagre, Daniel B.

2012-01-01

Because the distribution of alpine tundra is associated with spatially limited cold climates, global warming may threaten its local extent or existence. This notion has been challenged, however, based on observations of the diversity of alpine tundra in small areas primarily due to topographic variation. The importance of diversity in temperature or moisture conditions caused by topographic variation is an open question, and we extend this to geomorphology more generally. The extent to which geomorphic variation per se, based on relatively easily assessed indicators, can account for the variation in alpine tundra community composition is analyzed versus the inclusion of broad indicators of regional climate variation. Visual assessments of topography are quantified and reduced using principal components analysis (PCA). Observations of species cover are reduced using detrended correspondence analysis (DCA). A “best subsets” regression approach using the Akaike Information Criterion for selection of variables is compared to a simple stepwise regression with DCA scores as the dependent variable and scores on significant PCA axes plus more direct measures of topography as independent variables. Models with geographic coordinates (representing regional climate gradients) excluded explain almost as much variation in community composition as models with them included, although they are important contributors to the latter. The geomorphic variables in the model are those associated with local moisture differences such as snowbeds. The potential local variability of alpine tundra can be a buffer against climate change, but change in precipitation may be as important as change in temperature.

Factors Contributing to 50-ft Walking Speed and Observed Ethnic Differences in Older Community-Dwelling Mexican Americans and European Americans

PubMed Central

Hazuda, Helen P.

2015-01-01

Background Mexican Americans comprise the most rapidly growing segment of the older US population and are reported to have poorer functional health than European Americans, but few studies have examined factors contributing to ethnic differences in walking speed between Mexican Americans and European Americans. Objective The purpose of this study was to examine factors that contribute to walking speed and observed ethnic differences in walking speed in older Mexican Americans and European Americans using the disablement process model (DPM) as a guide. Design This was an observational, cross-sectional study. Methods Participants were 703 Mexican American and European American older adults (aged 65 years and older) who completed the baseline examination of the San Antonio Longitudinal Study of Aging (SALSA). Hierarchical regression models were performed to identify the contribution of contextual, lifestyle/anthropometric, disease, and impairment variables to walking speed and to ethnic differences in walking speed. Results The ethic difference in unadjusted mean walking speed (Mexican Americans=1.17 m/s, European Americans=1.29 m/s) was fully explained by adjustment for contextual (ie, age, sex, education, income) and lifestyle/anthropometric (ie, body mass index, height, physical activity) variables; adjusted mean walking speed in both ethnic groups was 1.23 m/s. Contextual variables explained 20.3% of the variance in walking speed, and lifestyle/anthropometric variables explained an additional 8.4%. Diseases (ie, diabetes, stroke, chronic obstructive pulmonary disease) explained an additional 1.9% of the variance in walking speed; impairments (ie, FEV1, upper leg pain, and lower extremity strength and range of motion) contributed an additional 5.5%. Thus, both nonmodifiable (ie, contextual, height) and modifiable (ie, impairments, body mass index, physical activity) factors contributed to walking speed in older Mexican Americans and European Americans. Limitations The study was conducted in a single geographic area and included only Mexican American Hispanic individuals. Conclusions Walking speed in older Mexican Americans and European Americans is influenced by modifiable and nonmodifiable factors, underscoring the importance of the DPM framework, which incorporates both factors into the physical therapist patient/client management process. PMID:25592187

Climatic suitability, isolation by distance and river resistance explain genetic variation in a Brazilian whiptail lizard.

PubMed

Oliveira, Eliana Faria; Martinez, Pablo Ariel; São-Pedro, Vinícius Avelar; Gehara, Marcelo; Burbrink, Frank Thomas; Mesquita, Daniel Oliveira; Garda, Adrian Antonio; Colli, Guarino Rinaldi; Costa, Gabriel Correa

2018-03-01

Spatial patterns of genetic variation can help understand how environmental factors either permit or restrict gene flow and create opportunities for regional adaptations. Organisms from harsh environments such as the Brazilian semiarid Caatinga biome may reveal how severe climate conditions may affect patterns of genetic variation. Herein we combine information from mitochondrial DNA with physical and environmental features to study the association between different aspects of the Caatinga landscape and spatial genetic variation in the whiptail lizard Ameivula ocellifera. We investigated which of the climatic, environmental, geographical and/or historical components best predict: (1) the spatial distribution of genetic diversity, and (2) the genetic differentiation among populations. We found that genetic variation in A. ocellifera has been influenced mainly by temperature variability, which modulates connectivity among populations. Past climate conditions were important for shaping current genetic diversity, suggesting a time lag in genetic responses. Population structure in A. ocellifera was best explained by both isolation by distance and isolation by resistance (main rivers). Our findings indicate that both physical and climatic features are important for explaining the observed patterns of genetic variation across the xeric Caatinga biome.

High resolution stalagmite climate record from the Yucatán Peninsula spanning the Maya terminal classic period

NASA Astrophysics Data System (ADS)

Medina-Elizalde, Martín; Burns, Stephen J.; Lea, David W.; Asmerom, Yemane; von Gunten, Lucien; Polyak, Victor; Vuille, Mathias; Karmalkar, Ambarish

2010-09-01

The decline of the Classic Maya civilization was complex and geographically variable, and occurred over a ~ 150-year interval, known as the Terminal Classic Period (TCP, C.E. 800-950). Paleoclimate studies based on lake sediments from the Yucatán Peninsula lowlands suggested that drought prevailed during the TCP and was likely an important factor in the disintegration of the Classic Maya civilization. The lacustrine evidence for decades of severe drought in the Yucatán Peninsula, however, does not readily explain the long 150-year socio-political decline of the Classic Maya civilization. Here we present a new, absolute-dated, high-resolution stalagmite δ18O record from the northwest Yucatán Peninsula that provides a much more detailed picture of climate variability during the last 1500 years. Direct calibration between stalagmite δ18O and rainfall amount offers the first quantitative estimation of rainfall variability during the Terminal Classic Period. Our results show that eight severe droughts, lasting from 3 to 18 years, occurred during major depopulation events of Classic Maya city-states. During these droughts, rainfall was reduced by 52% to 36%. The number and short duration of the dry intervals help explain why the TCP collapse of the Mayan civilization occurred over 150 years.

Repetitive negative thinking predicts depression and anxiety symptom improvement during brief cognitive behavioral therapy.

PubMed

Kertz, Sarah J; Koran, Jennifer; Stevens, Kimberly T; Björgvinsson, Thröstur

2015-05-01

Repetitive negative thinking (RNT) is a common symptom across depression and anxiety disorders and preliminary evidence suggests that decreases in rumination and worry are related to improvement in depression and anxiety symptoms. However, despite its prevalence, relatively little is known about transdiagnostic RNT and its temporal associations with symptom improvement during treatment. The current study was designed to examine the influence of RNT on subsequent depression and anxiety symptoms during treatment. Participants (n = 131; 52% female; 93% White; M = 34.76 years) were patients presenting for treatment in a brief, cognitive behavior therapy based, partial hospitalization program. Participants completed multiple assessments of depression (Center for the Epidemiological Studies of Depression-10 scale), anxiety (the 7-item Generalized Anxiety Disorder Scale), and repetitive negative thinking (Perseverative Thinking Questionnaire) over the course of treatment. Results indicated statistically significant between and within person effects of RNT on depression and anxiety, even after controlling for the effect of time, previous symptom levels, referral source, and treatment length. RNT explained 22% of the unexplained variability in depression scores and 15% of the unexplained variability in anxiety scores beyond that explained by the control variables. RNT may be an important transdiagnostic treatment target for anxiety and depression. Copyright © 2015 Elsevier Ltd. All rights reserved.

Simulating and explaining passive air sampling rates for semi-volatile compounds on polyurethane foam passive samplers

PubMed Central

Petrich, Nicholas T.; Spak, Scott N.; Carmichael, Gregory R.; Hu, Dingfei; Martinez, Andres; Hornbuckle, Keri C.

2013-01-01

Passive air samplers (PAS) including polyurethane foam (PUF) are widely deployed as an inexpensive and practical way to sample semi-volatile pollutants. However, concentration estimates from PAS rely on constant empirical mass transfer rates, which add unquantified uncertainties to concentrations. Here we present a method for modeling hourly sampling rates for semi-volatile compounds from hourly meteorology using first-principle chemistry, physics, and fluid dynamics, calibrated from depuration experiments. This approach quantifies and explains observed effects of meteorology on variability in compound-specific sampling rates and analyte concentrations; simulates nonlinear PUF uptake; and recovers synthetic hourly concentrations at a reference temperature. Sampling rates are evaluated for polychlorinated biphenyl congeners at a network of Harner model samplers in Chicago, Illinois during 2008, finding simulated average sampling rates within analytical uncertainty of those determined from loss of depuration compounds, and confirming quasi-linear uptake. Results indicate hourly, daily and interannual variability in sampling rates, sensitivity to temporal resolution in meteorology, and predictable volatility-based relationships between congeners. We quantify importance of each simulated process to sampling rates and mass transfer and assess uncertainty contributed by advection, molecular diffusion, volatilization, and flow regime within the PAS, finding PAS chamber temperature contributes the greatest variability to total process uncertainty (7.3%). PMID:23837599

Effect of climatological factors on respiratory syncytial virus epidemics

PubMed Central

NOYOLA, D. E.; MANDEVILLE, P. B.

2008-01-01

SUMMARY Respiratory syncytial virus (RSV) presents as yearly epidemics in temperate climates. We analysed the association of atmospheric conditions to RSV epidemics in San Luis Potosí, S.L.P., Mexico. The weekly number of RSV detections between October 2002 and May 2006 were correlated to ambient temperature, barometric pressure, relative humidity, vapour tension, dew point, precipitation, and hours of light using time-series and regression analyses. Of the variation in RSV cases, 49·8% was explained by the study variables. Of the explained variation in RSV cases, 32·5% was explained by the study week and 17·3% was explained by meteorological variables (average daily temperature, maximum daily temperature, temperature at 08:00 hours, and relative humidity at 08:00 hours). We concluded that atmospheric conditions, particularly temperature, partly explain the year to year variability in RSV activity. Identification of additional factors that affect RSV seasonality may help develop a model to predict the onset of RSV epidemics. PMID:18177520

Individualism, collectivism, and Chinese adolescents' aggression: intracultural variations.

PubMed

Li, Yan; Wang, Mo; Wang, Cixin; Shi, Junqi

2010-01-01

This study examined the relations between cultural values (i.e., individualism and collectivism) and aggression among 460 (234 girls) Chinese adolescents. Conflict level and social status insecurity were examined as potential explaining mechanisms for these relations. The results showed that adolescents' endorsement of collectivism was negatively related to their use of overt and relational aggression as reported by teachers and peers, whereas positive associations were found between the endorsement of individualism and adolescent aggression. Adolescents' conflict level and social status insecurity accounted for a significant part of these associations. Findings of this study demonstrate the importance of examining intracultural variations of cultural values in relation to adolescent aggression as well as the process variables in explaining the relations. (c) 2010 Wiley-Liss, Inc.

Understanding Cervicogenic Headache

PubMed Central

Chua, Nicholas H L; Suijlekom, Hans V; Wilder-Smith, Oliver H; Vissers, Kris C P

2012-01-01

The purported mechanism underlying the development and progression of cervicogenic headache (CEH) is the convergence of sensory inputs at the trigeminocervical nucleus. This mechanism explains the radiation of pain from the neck or the occipitonuchal area and its spread to the oculo-fronto-temporal region; it also explains the recurrent headaches caused by improper neck postures or external pressure to the structures in the neck and the occipital region. These neural connectivity mechanisms involving the trigeminal nucleus are also evident from the eyeblink reflex and findings of quantitative sensory testing (QST). Understanding the mechanisms underlying the development of CEH is important because it will not only provide a better treatment outcome but will also allow practitioners to appreciate the variability of symptomatic presentations in these patients. PMID:24223325

Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability.

PubMed

Booth, Ben B B; Dunstone, Nick J; Halloran, Paul R; Andrews, Timothy; Bellouin, Nicolas

2012-04-04

Systematic climate shifts have been linked to multidecadal variability in observed sea surface temperatures in the North Atlantic Ocean. These links are extensive, influencing a range of climate processes such as hurricane activity and African Sahel and Amazonian droughts. The variability is distinct from historical global-mean temperature changes and is commonly attributed to natural ocean oscillations. A number of studies have provided evidence that aerosols can influence long-term changes in sea surface temperatures, but climate models have so far failed to reproduce these interactions and the role of aerosols in decadal variability remains unclear. Here we use a state-of-the-art Earth system climate model to show that aerosol emissions and periods of volcanic activity explain 76 per cent of the simulated multidecadal variance in detrended 1860-2005 North Atlantic sea surface temperatures. After 1950, simulated variability is within observational estimates; our estimates for 1910-1940 capture twice the warming of previous generation models but do not explain the entire observed trend. Other processes, such as ocean circulation, may also have contributed to variability in the early twentieth century. Mechanistically, we find that inclusion of aerosol-cloud microphysical effects, which were included in few previous multimodel ensembles, dominates the magnitude (80 per cent) and the spatial pattern of the total surface aerosol forcing in the North Atlantic. Our findings suggest that anthropogenic aerosol emissions influenced a range of societally important historical climate events such as peaks in hurricane activity and Sahel drought. Decadal-scale model predictions of regional Atlantic climate will probably be improved by incorporating aerosol-cloud microphysical interactions and estimates of future concentrations of aerosols, emissions of which are directly addressable by policy actions.

Objective classification of atmospheric circulation over southern Scandinavia

NASA Astrophysics Data System (ADS)

Linderson, Maj-Lena

2001-02-01

A method for calculating circulation indices and weather types following the Lamb classification is applied to southern Scandinavia. The main objective is to test the ability of the method to describe the atmospheric circulation over the area, and to evaluate the extent to which the pressure patterns determine local precipitation and temperature in Scania, southernmost Sweden. The weather type classification method works well and produces distinct groups. However, the variability within the group is large with regard to the location of the low pressure centres, which may have implications for the precipitation over the area. The anticyclonic weather type dominates, together with the cyclonic and westerly types. This deviates partly from the general picture for Sweden and may be explained by the southerly location of the study area. The cyclonic type is most frequent in spring, although cloudiness and amount of rain are lowest during this season. This could be explained by the occurrence of weaker cyclones or low air humidity during this time of year. Local temperature and precipitation were modelled by stepwise regression for each season, designating weather types as independent variables. Only the winter season-modelled temperature and precipitation show a high and robust correspondence to the observed temperature and precipitation, even though <60% of the precipitation variance is explained. In the other seasons, the connection between atmospheric circulation and the local temperature and precipitation is low. Other meteorological parameters may need to be taken into account. The time and space resolution of the mean sea level pressure (MSLP) grid may affect the results, as many important features might not be covered by the classification. Local physiography may also influence the local climate in a way that cannot be described by the atmospheric circulation pattern alone, stressing the importance of using more than one observation series.

[Physical activity and reproductive health].

PubMed

Sundgot-Borgen, J

2000-11-20

The purpose of this article is to review the present knowledge about physical activity and reproductive health. Medline and manual search for articles related to exercise and menstrual function, and exercise and pregnancy were performed. Repetitive intensive exercise with increased stress hormone utilisation seems to partly explain the disturbances in the hypothalamic-pituitary-adrenal axis. The prevalence of menstrual irregularities is higher among athletes who participate in sports in which leanness is considered important for performance. Most of the studies concerning exercise-induced amenorrhoea have focused on low body weight and low fat ratio of body weight. However, energy drain and nutrient deficiency have been found to be important variables explaining menstrual irregularity in athletes. Loss of bone mass is related to menstrual irregularities hence it is important that menstrual irregularity not is considered a "normal" aspect of being an athlete. There are a number of positive effects and a few hypothetical risks related to exercise during pregnancy. There are no clinically controlled studies allowing us to draw conclusions about the effect of intensive training during pregnancy. Physically active women should be aware of the importance of sufficient energy intake to keep their regular menstrual cycle. Moderate exercise during pregnancy is recommended.

Working memory capacity links cognitive reserve with long-term memory in moderate to severe TBI: a translational approach.

PubMed

Sandry, Joshua; DeLuca, John; Chiaravalloti, Nancy

2015-01-01

Traumatic brain injury (TBI) can have devastating negative consequences on an individuals' ability to remember information; however, there is variability among memory impairment resulting from TBI. Some individuals exhibit long-term memory (LTM) impairment while others do not. This variability has been explained, at least in part, by the theory of cognitive reserve (CR). The theory suggests that individuals who have spent significant time engaged in intellectually enriching activities (higher CR) are better able to withstand LTM impairment despite neurological injury. The cognitive mechanisms that underlie this relationship are not well-specified. Recent evidence suggests that working memory (WM) capacity may be one mediating variable that can help explain how/why cognitive reserve (CR) protects against LTM impairment. The present research tested this hypothesis in a sample of fifty moderate to severe TBI patients. Specific neuropsychological tests were administered to estimate CR, LTM and WM. The results were congruent with a recent theoretical model that implicates WM capacity as a mediating variable in the relationship between CR and LTM (Sobel's Z = 2.62, p = 0.009). These data corroborate recent findings in an alternate neurological population and suggest that WM is an underlying mechanism of CR. Additional research is necessary to establish whether (1) WM is an important individual difference variable to include in memory rehabilitation trials and (2) to determine whether rehabilitation and treatment strategies that specifically target WM may also lead to complimentary improvements on diagnostic tests of delayed LTM in TBI and other memory impaired populations.

Controls on the interannual variability of hypoxia in a subtropical embayment and its adjacent waters in the Guangdong coastal upwelling system, northern South China Sea

NASA Astrophysics Data System (ADS)

Zhang, Heng; Cheng, Weicong; Chen, Yuren; Yu, Liuqian; Gong, Wenping

2018-06-01

Coastal embayments located downwind of large rivers under an upwelling-favorable wind are prone to develop low-oxygen or hypoxic conditions in their bottom water. One such embayment is Mirs Bay, off the Guangdong coast, which is affected by upwelling and the Pearl River Estuary (PRE) plume during summer. The relative importance of physical and biochemical processes on the interannual variability of hypoxia in Mirs Bay and its adjacent waters was investigated using statistical analyses of monthly hydrographic and water quality monitoring data from 2001 to 2015. The results reveal that the southwesterly wind duration and the PRE river discharge together explain 49% of the interannual variability in the size of the hypoxic area, whereas inclusion of the nutrient concentrations inside Mirs Bay and phytoplankton on the shelf explains 75% of the interannual variability in the size of the hypoxic area. This finding suggests that the interannual variability of hypoxia in Mirs Bay is regulated by coupled physical and biochemical processes. Increase of the hypoxic area under a longer-lasting southwesterly wind is caused by increased stratification, extended bottom water residence time, and onshore transport of a low-oxygen water mass induced by stable upwelling. In contrast, a reduction in the size of the hypoxic area may be attributed to a decrease in the surface water residence time of the particulate organic matter outside Mirs Bay due to increased discharge from the PRE. The results also show that the effects of allochthonous particulate organic matter outside Mirs Bay on bottom hypoxia cannot be neglected.

The role of updraft velocity in temporal variability of cloud hydrometeor number

NASA Astrophysics Data System (ADS)

Sullivan, Sylvia; Nenes, Athanasios; Lee, Dong Min; Oreopoulos, Lazaros

2016-04-01

Significant effort has been dedicated to incorporating direct aerosol-cloud links, through parameterization of liquid droplet activation and ice crystal nucleation, within climate models. This significant accomplishment has generated the need for understanding which parameters affecting hydrometer formation drives its variability in coupled climate simulations, as it provides the basis for optimal parameter estimation as well as robust comparison with data, and other models. Sensitivity analysis alone does not address this issue, given that the importance of each parameter for hydrometer formation depends on its variance and sensitivity. To address the above issue, we develop and use a series of attribution metrics defined with adjoint sensitivities to attribute the temporal variability in droplet and crystal number to important aerosol and dynamical parameters. This attribution analysis is done both for the NASA Global Modeling and Assimilation Office Goddard Earth Observing System Model, Version 5 and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1. Within the GEOS simulation, up to 48% of temporal variability in output ice crystal number and 61% in droplet number can be attributed to input updraft velocity fluctuations, while for the CAM simulation, they explain as much as 89% of the ice crystal number variability. This above results suggest that vertical velocity in both model frameworks is seen to be a very important (or dominant) driver of hydrometer variability. Yet, observations of vertical velocity are seldomly available (or used) to evaluate the vertical velocities in simulations; this strikingly contrasts the amount and quality of data available for aerosol-related parameters. Consequentially, there is a strong need for retrievals or measurements of vertical velocity for addressing this important knowledge gap that requires a significant investment and effort by the atmospheric community. The attribution metrics as a tool of understanding for hydrometer variability can be instrumental for understanding the source of differences between models used for aerosol-cloud-climate interaction studies.

Does psychopathology at admission predict the length of inpatient stay in psychiatry? Implications for financing psychiatric services

PubMed Central

2011-01-01

Background The debate on appropriate financing systems in inpatient psychiatry is ongoing. In this context, it is important to control resource use in terms of length of stay (LOS), which is the most costly factor in inpatient care and the one that can be influenced most easily. Previous studies have shown that psychiatric diagnoses provide only limited justification for explaining variation in LOS, and it has been suggested that measures such as psychopathology might be more appropriate to predict resource use. Therefore, we investigated the relationship between LOS and psychopathological syndromes or symptoms at admission as well as other characteristics such as sociodemographic and clinical variables. Methods We considered routine medical data of patients admitted to the Psychiatric University Hospital Zurich in the years 2008 and 2009. Complete data on psychopathology at hospital admission were available in 3,220 inpatient episodes. A subsample of 2,939 inpatient episodes was considered in final statistical models, including psychopathology as well as complete datasets of further measures (e.g. sociodemographic, clinical, treatment-related and psychosocial variables). We used multivariate linear as well as logistic regression analysis with forward selection procedure to determine the predictors of LOS. Results All but two syndrome scores (mania, hostility) were positively related to the length of stay. Final statistical models showed that syndromes or symptoms explained about 5% of the variation in length of stay. The inclusion of syndromes or symptoms as well as basic treatment variables and other factors led to an explained variation of up to 25%. Conclusions Psychopathological syndromes and symptoms at admission and further characteristics only explained a small proportion of the length of inpatient stay. Thus, according to our sample, psychopathology might not be suitable as a primary indicator for estimating LOS and contingent costs. This might be considered in the development of future costing systems in psychiatry. PMID:21801366

Does psychopathology at admission predict the length of inpatient stay in psychiatry? Implications for financing psychiatric services.

PubMed

Warnke, Ingeborg; Rössler, Wulf; Herwig, Uwe

2011-07-29

The debate on appropriate financing systems in inpatient psychiatry is ongoing. In this context, it is important to control resource use in terms of length of stay (LOS), which is the most costly factor in inpatient care and the one that can be influenced most easily. Previous studies have shown that psychiatric diagnoses provide only limited justification for explaining variation in LOS, and it has been suggested that measures such as psychopathology might be more appropriate to predict resource use. Therefore, we investigated the relationship between LOS and psychopathological syndromes or symptoms at admission as well as other characteristics such as sociodemographic and clinical variables. We considered routine medical data of patients admitted to the Psychiatric University Hospital Zurich in the years 2008 and 2009. Complete data on psychopathology at hospital admission were available in 3,220 inpatient episodes. A subsample of 2,939 inpatient episodes was considered in final statistical models, including psychopathology as well as complete datasets of further measures (e.g. sociodemographic, clinical, treatment-related and psychosocial variables). We used multivariate linear as well as logistic regression analysis with forward selection procedure to determine the predictors of LOS. All but two syndrome scores (mania, hostility) were positively related to the length of stay. Final statistical models showed that syndromes or symptoms explained about 5% of the variation in length of stay. The inclusion of syndromes or symptoms as well as basic treatment variables and other factors led to an explained variation of up to 25%. Psychopathological syndromes and symptoms at admission and further characteristics only explained a small proportion of the length of inpatient stay. Thus, according to our sample, psychopathology might not be suitable as a primary indicator for estimating LOS and contingent costs. This might be considered in the development of future costing systems in psychiatry.

gHRV: Heart rate variability analysis made easy.

PubMed

Rodríguez-Liñares, L; Lado, M J; Vila, X A; Méndez, A J; Cuesta, P

2014-08-01

In this paper, the gHRV software tool is presented. It is a simple, free and portable tool developed in python for analysing heart rate variability. It includes a graphical user interface and it can import files in multiple formats, analyse time intervals in the signal, test statistical significance and export the results. This paper also contains, as an example of use, a clinical analysis performed with the gHRV tool, namely to determine whether the heart rate variability indexes change across different stages of sleep. Results from tests completed by researchers who have tried gHRV are also explained: in general the application was positively valued and results reflect a high level of satisfaction. gHRV is in continuous development and new versions will include suggestions made by testers. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Determinants of Internet use as a preferred source of information on personal health.

PubMed

Lemire, Marc; Paré, Guy; Sicotte, Claude; Harvey, Charmian

2008-11-01

To understand the personal, social and cultural factors likely to explain recourse to the Internet as a preferred source of personal health information. A cross-sectional survey was conducted among a population of 2923 Internet users visiting a firmly established website that offers information on personal health. Multiple regression analysis was performed to identify the determinants of site use. The analysis template comprised four classes of determinants likely to explain Internet use: beliefs, intentions, user satisfaction and socio-demographic characteristics. Seven-point Likert scales were used. An analysis of the psychometric qualities of the variables provided compelling evidence of the construct's validity and reliability. A confirmatory factor analysis confirmed the correspondence with the factors predicted by the theoretical model. The regression analysis explained 35% of the variance in Internet use. Use was directly associated with five factors: perceived usefulness, importance given to written media in searches for health information, concern for personal health, importance given to the opinions of physicians and other health professionals, and the trust placed in the information available on the site itself. This study confirms the importance of the credibility of information on the frequency of Internet use as a preferred source of information on personal health. It also shows the potentially influential role of the Internet in the development of personal knowledge of health issues.

Does geography or ecology best explain 'cultural' variation among chimpanzee communities?

PubMed

Kamilar, Jason M; Marshack, Joshua L

2012-02-01

Much attention has been paid to geographic variation in chimpanzee behavior, but few studies have applied quantitative techniques to explain this variation. Here, we apply methods typically utilized in macroecology to explain variation in the putative cultural traits of chimpanzees. We analyzed published data containing 39 behavioral traits from nine chimpanzee communities. We used a canonical correspondence analysis to examine the relative importance of environmental characteristics and geography, which may be a proxy for inter-community gene flow and/or social transmission, for explaining geographic variation in chimpanzee behavior. We found that geography, and longitude in particular, was the best predictor of behavioral variation. Chimpanzee communities in close longitudinal proximity to each other exhibit similar behavioral repertoires, independent of local ecological factors. No ecological variables were significantly related to behavioral variation. These results support the idea that inter-community dispersal patterns have played a major role in structuring behavioral variation. We cannot be certain whether behavioral variation has a genetic basis, is the result of innovation and diffusion, or a combination of the two. Copyright © 2011 Elsevier Ltd. All rights reserved.

Cognitive predictors of adaptive functioning in children with symptomatic epilepsy.

PubMed

Kerr, Elizabeth N; Fayed, Nora

2017-10-01

The current study sought to understand the contribution of the attention and working memory challenges experienced by children with active epilepsy without an intellectual disability to adaptive functioning (AF) while taking into account intellectual ability, co-occurring brain-based psychosocial diagnoses, and epilepsy-related variables. The relationship of attention and working memory with AF was examined in 76 children with active epilepsy with intellectual ability above the 2nd percentile recruited from a tertiary care center. AF was measured using the Scales of Independent Behavior-Revised (SIB-R) and compared with norm-referenced data. Standardized clinical assessments of attention span, sustained attention, as well as basic and more complex working memory were administered to children. Commonality analysis was used to investigate the importance of the variables with respect to the prediction of AF and to construct parsimonious models to elucidate the factors most important in explaining AF. Seventy-one percent of parents reported that their child experienced mild to severe difficulties with overall AF. Similar proportions of children displayed limitations in domain-specific areas of AF (Motor, Social/Communication, Person Living, and Community Living). The reduced models for Broad and domain-specific AF produced a maximum of seven predictor variables, with little loss in overall explained variance compared to the full models. Intellectual ability was a powerful predictor of Broad and domain-specific AF. Complex working memory was the only other cognitive predictor retained in each of the parsimonious models of AF. Sustained attention and complex working memory explained a large amount of the total variance in Motor AF. Children with a previously diagnosed comorbidity displayed lower Social/Communication, Personal Living, and Broad AF than those without a diagnosis. At least one epilepsy-related variable appeared in each of the reduced models, with age of seizure onset and seizure type (generalized or partial) being the main predictors. Intellectual ability was the most powerful predictor of AF in children with epilepsy whose intellectual functioning was above the 2nd percentile. Co-occurring brain-based cognitive and psychosocial issues experienced by children with living epilepsy, particularly complex working memory and diagnosed comorbidities, contribute to AF and may be amenable to intervention. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Putative golden proportions as predictors of facial esthetics in adolescents.

PubMed

Kiekens, Rosemie M A; Kuijpers-Jagtman, Anne Marie; van 't Hof, Martin A; van 't Hof, Bep E; Maltha, Jaap C

2008-10-01

In orthodontics, facial esthetics is assumed to be related to golden proportions apparent in the ideal human face. The aim of the study was to analyze the putative relationship between facial esthetics and golden proportions in white adolescents. Seventy-six adult laypeople evaluated sets of photographs of 64 adolescents on a visual analog scale (VAS) from 0 to 100. The facial esthetic value of each subject was calculated as a mean VAS score. Three observers recorded the position of 13 facial landmarks included in 19 putative golden proportions, based on the golden proportions as defined by Ricketts. The proportions and each proportion's deviation from the golden target (1.618) were calculated. This deviation was then related to the VAS scores. Only 4 of the 19 proportions had a significant negative correlation with the VAS scores, indicating that beautiful faces showed less deviation from the golden standard than less beautiful faces. Together, these variables explained only 16% of the variance. Few golden proportions have a significant relationship with facial esthetics in adolescents. The explained variance of these variables is too small to be of clinical importance.

Different Measures of Structural Similarity Tap Different Aspects of Visual Object Processing

PubMed Central

Gerlach, Christian

2017-01-01

The structural similarity of objects has been an important variable in explaining why some objects are easier to categorize at a superordinate level than to individuate, and also why some patients with brain injury have more difficulties in recognizing natural (structurally similar) objects than artifacts (structurally distinct objects). In spite of its merits as an explanatory variable, structural similarity is not a unitary construct, and it has been operationalized in different ways. Furthermore, even though measures of structural similarity have been successful in explaining task and category-effects, this has been based more on implication than on direct empirical demonstrations. Here, the direct influence of two different measures of structural similarity, contour overlap and within-item structural diversity, on object individuation (object decision) and superordinate categorization performance is examined. Both measures can account for performance differences across objects, but in different conditions. It is argued that this reflects differences between the measures in whether they tap: (i) global or local shape characteristics, and (ii) between- or within-category structural similarity. PMID:28861027

Modeling the acceptance of clinical information systems among hospital medical staff: an extended TAM model.

PubMed

Melas, Christos D; Zampetakis, Leonidas A; Dimopoulou, Anastasia; Moustakis, Vassilis

2011-08-01

Recent empirical research has utilized the Technology Acceptance Model (TAM) to advance the understanding of doctors' and nurses' technology acceptance in the workplace. However, the majority of the reported studies are either qualitative in nature or use small convenience samples of medical staff. Additionally, in very few studies moderators are either used or assessed despite their importance in TAM based research. The present study focuses on the application of TAM in order to explain the intention to use clinical information systems, in a random sample of 604 medical staff (534 physicians) working in 14 hospitals in Greece. We introduce physicians' specialty as a moderator in TAM and test medical staff's information and communication technology (ICT) knowledge and ICT feature demands, as external variables. The results show that TAM predicts a substantial proportion of the intention to use clinical information systems. Findings make a contribution to the literature by replicating, explaining and advancing the TAM, whereas theory is benefited by the addition of external variables and medical specialty as a moderator. Recommendations for further research are discussed. Copyright © 2011 Elsevier Inc. All rights reserved.

Modelling Ecuador's rainfall distribution according to geographical characteristics.

NASA Astrophysics Data System (ADS)

Tobar, Vladimiro; Wyseure, Guido

2017-04-01

It is known that rainfall is affected by terrain characteristics and some studies had focussed on its distribution over complex terrain. Ecuador's temporal and spatial rainfall distribution is affected by its location on the ITCZ, the marine currents in the Pacific, the Amazon rainforest, and the Andes mountain range. Although all these factors are important, we think that the latter one may hold a key for modelling spatial and temporal distribution of rainfall. The study considered 30 years of monthly data from 319 rainfall stations having at least 10 years of data available. The relatively low density of stations and their location in accessible sites near to main roads or rivers, leave large and important areas ungauged, making it not appropriate to rely on traditional interpolation techniques to estimate regional rainfall for water balance. The aim of this research was to come up with a useful model for seasonal rainfall distribution in Ecuador based on geographical characteristics to allow its spatial generalization. The target for modelling was the seasonal rainfall, characterized by nine percentiles for each one of the 12 months of the year that results in 108 response variables, later on reduced to four principal components comprising 94% of the total variability. Predictor variables for the model were: geographic coordinates, elevation, main wind effects from the Amazon and Coast, Valley and Hill indexes, and average and maximum elevation above the selected rainfall station to the east and to the west, for each one of 18 directions (50-135°, by 5°) adding up to 79 predictors. A multiple linear regression model by the Elastic-net algorithm with cross-validation was applied for each one of the PC as response to select the most important ones from the 79 predictor variables. The Elastic-net algorithm deals well with collinearity problems, while allowing variable selection in a blended approach between the Ridge and Lasso regression. The model fitting produced explained variances of 59%, 81%, 49% and 17% for PC1, PC2, PC3 and PC4, respectively, backing up the hypothesis of good correlation between geographical characteristics and seasonal rainfall patterns (comprised in the four principal components). With the obtained coefficients from the regression, the 108 rainfall percentiles for each station were back estimated giving very good results when compared with the original ones, with an overall 60% explained variance.

Tree-, stand- and site-specific controls on landscape-scale patterns of transpiration

NASA Astrophysics Data System (ADS)

Kathrin Hassler, Sibylle; Weiler, Markus; Blume, Theresa

2018-01-01

Transpiration is a key process in the hydrological cycle, and a sound understanding and quantification of transpiration and its spatial variability is essential for management decisions as well as for improving the parameterisation and evaluation of hydrological and soil-vegetation-atmosphere transfer models. For individual trees, transpiration is commonly estimated by measuring sap flow. Besides evaporative demand and water availability, tree-specific characteristics such as species, size or social status control sap flow amounts of individual trees. Within forest stands, properties such as species composition, basal area or stand density additionally affect sap flow, for example via competition mechanisms. Finally, sap flow patterns might also be influenced by landscape-scale characteristics such as geology and soils, slope position or aspect because they affect water and energy availability; however, little is known about the dynamic interplay of these controls.We studied the relative importance of various tree-, stand- and site-specific characteristics with multiple linear regression models to explain the variability of sap velocity measurements in 61 beech and oak trees, located at 24 sites across a 290 km2 catchment in Luxembourg. For each of 132 consecutive days of the growing season of 2014 we modelled the daily sap velocity and derived sap flow patterns of these 61 trees, and we determined the importance of the different controls.Results indicate that a combination of mainly tree- and site-specific factors controls sap velocity patterns in the landscape, namely tree species, tree diameter, geology and aspect. For sap flow we included only the stand- and site-specific predictors in the models to ensure variable independence. Of those, geology and aspect were most important. Compared to these predictors, spatial variability of atmospheric demand and soil moisture explains only a small fraction of the variability in the daily datasets. However, the temporal dynamics of the explanatory power of the tree-specific characteristics, especially species, are correlated to the temporal dynamics of potential evaporation. We conclude that transpiration estimates on the landscape scale would benefit from not only consideration of hydro-meteorological drivers, but also tree, stand and site characteristics in order to improve the spatial and temporal representation of transpiration for hydrological and soil-vegetation-atmosphere transfer models.

Forecasting Total Water Storage Changes in the Amazon basin using Atlantic and Pacific Sea Surface Temperatures

NASA Astrophysics Data System (ADS)

De Linage, C.; Famiglietti, J. S.; Randerson, J. T.

2013-12-01

Floods and droughts frequently affect the Amazon River basin, impacting the transportation, river navigation, agriculture, economy and the carbon balance and biodiversity of several South American countries. The present study aims to find the main variables controlling the natural interannual variability of terrestrial water storage in the Amazon region and to propose a modeling framework for flood and drought forecasting. We propose three simple empirical models using a linear combination of lagged spatial averages of central Pacific (Niño 4 index) and tropical North Atlantic (TNAI index) sea surface temperatures (SST) to predict a decade-long record of 3°, monthly terrestrial water storage anomalies (TWSA) observed by the Gravity Recovery And Climate Experiment (GRACE) mission. In addition to a SST forcing term, the models included a relaxation term to simulate the memory of water storage anomalies in response to external variability in forcing. Model parameters were spatially-variable and individually optimized for each 3° grid cell. We also investigated the evolution of the predictive capability of our models with increasing minimum lead times for TWSA forecasts. TNAI was the primary external forcing for the central and western regions of the southern Amazon (35% of variance explained with a 3-month forecast), whereas Niño 4 was dominant in the northeastern part of the basin (61% of variance explained with a 3-month forecast). Forcing the model with a combination of the two indices improved the fit significantly (p<0.05) for at least 64% of the grid cells, compared to models forced solely with Niño 4 or TNAI. The combined model was able to explain 43% of the variance in the Amazon basin as a whole with a 3-month lead time. While 66% of the observed variance was explained in the northeastern Amazon, only 39% of the variance was captured by the combined model in the central and western regions, suggesting that other, more local, forcing sources were important in these regions. The predictive capability of the combined model was monotonically degraded with increasing lead times. Degradation was smaller in the northeastern Amazon (where 49% of the variance was explained using a 8-month lead time versus 69% for a 1 month lead time) compared to the western and central regions of southern Amazon (where 22% of the variance was explained at 8 months versus 43% at 1 month). Our model may provide early warning information about flooding in the northeastern region of the Amazon basin, where floodplain areas are extensive and the sensitivity of floods to external SST forcing was shown to be high. This work also strengthens our understanding of the mechanisms regulating interannual variability in Amazon fires, as TWSA deficits may subsequently lead to atmospheric water vapor deficits and reduced cloudiness via water-limited evapotranspiration. Finally, this work helps to bridge the gap between the current GRACE mission and the follow-on gravity mission.

Race-ethnicity is a strong correlate of circulating fat-soluble nutrient concentrations in a representative sample of the US population1,2,3

PubMed Central

Schleicher, Rosemary L; Sternberg, Maya R; Pfeiffer, Christine M

2016-01-01

Sociodemographic and lifestyle factors exert important influences on nutritional status; however, information on their association with biomarkers of fat-soluble nutrients is limited, particularly in a representative sample of adults. Serum or plasma concentrations of vitamin A (VIA), vitamin E (VIE), carotenes (CAR), xanthophylls (XAN), 25-hydroxyvitamin D (25OHD), saturated- (SFA), monounsaturated- (MUFA), polyunsaturated- (PUFA) and total fatty acids (tFA) were measured in adults (≥20 y) during all or part of NHANES 2003–2006. Simple and multiple linear regression were used to assess 5 sociodemographic variables (age, sex, race-ethnicity, education, income) and 5 lifestyle behaviors (smoking, alcohol consumption, BMI, physical activity, supplement use) and their relation to biomarker concentrations. Adjustment for total serum cholesterol and lipid-altering drug use was added to the full regression model. Adjustment for latitude and season was added to the full model for 25OHD. Based on simple linear regression, race-ethnicity, BMI and supplement use were significantly related to all fat-soluble biomarkers. Sociodemographic variables as a groupexplained 5–17% of biomarker variability, whereas together, sociodemographic and lifestyle variables explained 22–23% (25OHD, VIE, XAN), 17% (VIA), 15% (MUFA), 10–11% (SFA, CAR, tFA) and 6% (PUFA). Although lipid adjustment explained additional variability for all biomarkers except 25OHD, it appeared to be largely independent of sociodemographic and lifestyle variables. After adjusting for sociodemographic, lifestyle and lipid-related variables, major differences in biomarkers were associated with race-ethnicity (from −44% to 57%); smoking (up to −25%); supplement use (up to 21%); and BMI (up to −15%). Latitude and season attenuated some race-ethnic differences. Of the sociodemographic and lifestyle variables examined, with or without lipid-adjustment, most fat-soluble nutrient biomarkers were significantly associated with race-ethnicity. PMID:23596163

Marine assemblages respond rapidly to winter climate variability.

PubMed

Morley, James W; Batt, Ryan D; Pinsky, Malin L

2017-07-01

Even species within the same assemblage have varied responses to climate change, and there is a poor understanding for why some taxa are more sensitive to climate than others. In addition, multiple mechanisms can drive species' responses, and responses may be specific to certain life stages or times of year. To test how marine species respond to climate variability, we analyzed 73 diverse taxa off the southeast US coast in 26 years of scientific trawl survey data and determined how changes in distribution and biomass relate to temperature. We found that winter temperatures were particularly useful for explaining interannual variation in species' distribution and biomass, although the direction and magnitude of the response varied among species from strongly negative, to little response, to strongly positive. Across species, the response to winter temperature varied greatly, with much of this variation being explained by thermal preference. A separate analysis of annual commercial fishery landings revealed that winter temperatures may also impact several important fisheries in the southeast United States. Based on the life stages of the species surveyed, winter temperature appears to act through overwinter mortality of juveniles or as a cue for migration timing. We predict that this assemblage will be responsive to projected increases in temperature and that winter temperature may be broadly important for species relationships with climate on a global scale. © The Authors Global Change Biology Published by John Wiley & Sons Ltd.

Environmental drivers of the distribution of nitrogen functional genes at a watershed scale.

PubMed

Tsiknia, Myrto; Paranychianakis, Nikolaos V; Varouchakis, Emmanouil A; Nikolaidis, Nikolaos P

2015-06-01

To date only few studies have dealt with the biogeography of microbial communities at large spatial scales, despite the importance of such information to understand and simulate ecosystem functioning. Herein, we describe the biogeographic patterns of microorganisms involved in nitrogen (N)-cycling (diazotrophs, ammonia oxidizers, denitrifiers) as well as the environmental factors shaping these patterns across the Koiliaris Critical Zone Observatory, a typical Mediterranean watershed. Our findings revealed that a proportion of variance ranging from 40 to 80% of functional genes abundance could be explained by the environmental variables monitored, with pH, soil texture, total organic carbon and potential nitrification rate being identified as the most important drivers. The spatial autocorrelation of N-functional genes ranged from 0.2 to 6.2 km and prediction maps, generated by cokriging, revealed distinct patterns of functional genes. The inclusion of functional genes in statistical modeling substantially improved the proportion of variance explained by the models, a result possibly due to the strong relationships that were identified among microbial groups. Significant relationships were set between functional groups, which were further mediated by land use (natural versus agricultural lands). These relationships, in combination with the environmental variables, allow us to provide insights regarding the ecological preferences of N-functional groups and among them the recently identified clade II of nitrous oxide reducers. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

How important are determinants of obesity measured at the individual level for explaining geographic variation in body mass index distributions? Observational evidence from Canada using Quantile Regression and Blinder-Oaxaca Decomposition.

PubMed

Dutton, Daniel J; McLaren, Lindsay

2016-04-01

Obesity prevalence varies between geographic regions in Canada. The reasons for this variation are unclear but most likely implicate both individual-level and population-level factors. The objective of this study was to examine whether equalising correlates of body mass index (BMI) across these geographic regions could be reasonably expected to reduce differences in BMI distributions between regions. Using data from three cycles of the Canadian Community Health Survey (CCHS) 2001, 2003 and 2007 for males and females, we modelled between-region BMI cross-sectionally using quantile regression and Blinder-Oaxaca decomposition of the quantile regression results. We show that while individual-level variables (ie, age, income, education, physical activity level, fruit and vegetable consumption, smoking status, drinking status, family doctor status, rural status, employment in the past 12 months and marital status) may be Caucasian important correlates of BMI within geographic regions, those variables are not capable of explaining variation in BMI between regions. Equalisation of common correlates of BMI between regions cannot be reasonably expected to reduce differences in the BMI distributions between regions. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Ensemble simulations of the role of the stratosphere in the attribution of northern extratropical tropospheric ozone variability

NASA Astrophysics Data System (ADS)

Hess, P.; Kinnison, D.; Tang, Q.

2015-03-01

Despite the need to understand the impact of changes in emissions and climate on tropospheric ozone, the attribution of tropospheric interannual ozone variability to specific processes has proven difficult. Here, we analyze the stratospheric contribution to tropospheric ozone variability and trends from 1953 to 2005 in the Northern Hemisphere (NH) mid-latitudes using four ensemble simulations of the free running (FR) Whole Atmosphere Community Climate Model (WACCM). The simulations are externally forced with observed time-varying (1) sea-surface temperatures (SSTs), (2) greenhouse gases (GHGs), (3) ozone depleting substances (ODS), (4) quasi-biennial oscillation (QBO), (5) solar variability (SV) and (6) stratospheric sulfate surface area density (SAD). A detailed representation of stratospheric chemistry is simulated, including the ozone loss due to volcanic eruptions and polar stratospheric clouds. In the troposphere, ozone production is represented by CH4-NOx smog chemistry, where surface chemical emissions remain interannually constant. Despite the simplicity of its tropospheric chemistry, at many NH measurement locations, the interannual ozone variability in the FR WACCM simulations is significantly correlated with the measured interannual variability. This suggests the importance of the external forcing applied in these simulations in driving interannual ozone variability. The variability and trend in the simulated 1953-2005 tropospheric ozone from 30 to 90° N at background surface measurement sites, 500 hPa measurement sites and in the area average are largely explained on interannual timescales by changes in the 30-90° N area averaged flux of ozone across the 100 hPa surface and changes in tropospheric methane concentrations. The average sensitivity of tropospheric ozone to methane (percent change in ozone to a percent change in methane) from 30 to 90° N is 0.17 at 500 hPa and 0.21 at the surface; the average sensitivity of tropospheric ozone to the 100 hPa ozone flux (percent change in ozone to a percent change in the ozone flux) from 30 to 90° N is 0.19 at 500 hPa and 0.11 at the surface. The 30-90° N simulated downward residual velocity at 100 hPa increased by 15% between 1953 and 2005. However, the impact of this on the 30-90° N 100 hPa ozone flux is modulated by the long-term changes in stratospheric ozone. The ozone flux decreases from 1965 to 1990 due to stratospheric ozone depletion, but increases again by approximately 7% from 1990 to 2005. The first empirical orthogonal function of interannual ozone variability explains from 40% (at the surface) to over 80% (at 150 hPa) of the simulated ozone interannual variability from 30 to 90° N. This identified mode of ozone variability shows strong stratosphere-troposphere coupling, demonstrating the importance of the stratosphere in an attribution of tropospheric ozone variability. The simulations, with no change in emissions, capture almost 50% of the measured ozone change during the 1990s at a variety of locations. This suggests that a large portion of the measured change is not due to changes in emissions, but can be traced to changes in large-scale modes of ozone variability. This emphasizes the difficulty in the attribution of ozone changes, and the importance of natural variability in understanding the trends and variability of ozone. We find little relation between the El Niño-Southern Oscillation (ENSO) index and large-scale tropospheric ozone variability over the long-term record.

How important are coastal fronts to albacore tuna (Thunnus alalunga) habitat in the Northeast Pacific Ocean?

NASA Astrophysics Data System (ADS)

Nieto, Karen; Xu, Yi; Teo, Steven L. H.; McClatchie, Sam; Holmes, John

2017-01-01

We used satellite sea surface temperature (SST) data to characterize coastal fronts and then tested the effects of the fronts and other environmental variables on the distribution of the albacore tuna (Thunnus alalunga) catches in the coastal areas (from the coast to 200 nm offshore) of the Northeast Pacific Ocean. A boosted regression tree (BRT) model was used to explain the spatial and temporal patterns in albacore tuna catch per unit effort (CPUE) (1988-2011), using frontal features (distance to the front and temperature gradient), and other environmental variables like SST, surface chlorophyll concentration (chlorophyll), and geostrophic currents as explanatory variables. Based on over two decades of high-resolution data, the modeled results confirmed previous findings that albacore CPUE distribution is strongly influenced by SST and chlorophyll at fishing locations, and the distance of fronts from the coast (DFRONT-COAST), albeit with substantial seasonal and interannual variation. Albacore CPUEs were higher near warm, low chlorophyll oceanic waters, and near SST fronts. We performed sequential leave-one-year-out cross-validations for all years and found that the relationships in the BRT models were robust for the entire study period. Spatial distributions of model-predicted albacore CPUE were similar to observations, but the model was unable to predict very high CPUEs in some areas. These results help to explain previously observed variability in albacore CPUE and will likely help improve international fisheries management in the face of environmental changes.

Exploratory factor analysis for differentiating sensory and mechanical variables related to muscle-tendon unit elongation

PubMed Central

Chagas, Mauro H.; Magalhães, Fabrício A.; Peixoto, Gustavo H. C.; Pereira, Beatriz M.; Andrade, André G. P.; Menzel, Hans-Joachim K.

2016-01-01

ABSTRACT Background Stretching exercises are able to promote adaptations in the muscle-tendon unit (MTU), which can be tested through physiological and biomechanical variables. Identifying the key variables in MTU adaptations is crucial to improvements in training. Objective To perform an exploratory factor analysis (EFA) involving the variables often used to evaluate the response of the MTU to stretching exercises. Method Maximum joint range of motion (ROMMAX), ROM at first sensation of stretching (FSTROM), peak torque (torqueMAX), passive stiffness, normalized stiffness, passive energy, and normalized energy were investigated in 36 participants during passive knee extension on an isokinetic dynamometer. Stiffness and energy values were normalized by the muscle cross-sectional area and their passive mode assured by monitoring the EMG activity. Results EFA revealed two major factors that explained 89.68% of the total variance: 53.13% was explained by the variables torqueMAX, passive stiffness, normalized stiffness, passive energy, and normalized energy, whereas the remaining 36.55% was explained by the variables ROMMAX and FSTROM. Conclusion This result supports the literature wherein two main hypotheses (mechanical and sensory theories) have been suggested to describe the adaptations of the MTU to stretching exercises. Contrary to some studies, in the present investigation torqueMAX was significantly correlated with the variables of the mechanical theory rather than those of the sensory theory. Therefore, a new approach was proposed to explain the behavior of the torqueMAX during stretching exercises. PMID:27437715

Decomposing race and gender differences in underweight and obesity in South Africa.

PubMed

Averett, Susan L; Stacey, Nicholas; Wang, Yang

2014-12-01

Using data from the National Income Dynamics Study, we document differentials in both underweight and obesity across race and gender in post-Apartheid South Africa. Using a nonlinear decomposition method, we decompose these differences across gender within race and then across race within gender. Less than one third of the differences in obesity and underweight across gender are explained by differences in covariates. In contrast, at least 70% of the obesity differences across race are explained by differences in covariates. Behavioral variables such as smoking and exercise explain the largest part of the bodyweight differentials across gender. For bodyweight differentials across race within gender, however, socioeconomic status and background variables have the largest explanatory power for obesity differentials, while background variables play the key role in explaining the underweight differentials. These results indicate that eradicating obesity and underweight differentials will require targeting policies to specific groups. Copyright © 2014 Elsevier B.V. All rights reserved.

Modeling chlorophyll-a and dissolved oxygen concentration in tropical floodplain lakes (Paraná River, Brazil).

PubMed

Rocha, R R A; Thomaz, S M; Carvalho, P; Gomes, L C

2009-06-01

The need for prediction is widely recognized in limnology. In this study, data from 25 lakes of the Upper Paraná River floodplain were used to build models to predict chlorophyll-a and dissolved oxygen concentrations. Akaike's information criterion (AIC) was used as a criterion for model selection. Models were validated with independent data obtained in the same lakes in 2001. Predictor variables that significantly explained chlorophyll-a concentration were pH, electrical conductivity, total seston (positive correlation) and nitrate (negative correlation). This model explained 52% of chlorophyll variability. Variables that significantly explained dissolved oxygen concentration were pH, lake area and nitrate (all positive correlations); water temperature and electrical conductivity were negatively correlated with oxygen. This model explained 54% of oxygen variability. Validation with independent data showed that both models had the potential to predict algal biomass and dissolved oxygen concentration in these lakes. These findings suggest that multiple regression models are valuable and practical tools for understanding the dynamics of ecosystems and that predictive limnology may still be considered a powerful approach in aquatic ecology.

Determinants of Tree Assemblage Composition at the Mesoscale within a Subtropical Eucalypt Forest

PubMed Central

Hero, Jean-Marc; Butler, Sarah A.; Lollback, Gregory W.; Castley, James G.

2014-01-01

A variety of environmental processes, including topography, edaphic and disturbance factors can influence vegetation composition. The relative influence of these patterns has been known to vary with scale, however, few studies have focused on environmental drivers of composition at the mesoscale. This study examined the relative importance of topography, catchment flow and soil in influencing tree assemblages in Karawatha Forest Park; a South-East Queensland subtropical eucalypt forest embedded in an urban matrix that is part of the Terrestrial Ecosystem Research Network South-East Queensland Peri-urban SuperSite. Thirty-three LTER plots were surveyed at the mesoscale (909 ha), where all woody stems ≥1.3 m high rooted within plots were sampled. Vegetation was divided into three cohorts: small (≥1–10 cm DBH), intermediate (≥10–30 cm DBH), and large (≥30 cm DBH). Plot slope, aspect, elevation, catchment area and location and soil chemistry and structure were also measured. Ordinations and smooth surface modelling were used to determine drivers of vegetation assemblage in each cohort. Vegetation composition was highly variable among plots at the mesoscale (plots systematically placed at 500 m intervals). Elevation was strongly related to woody vegetation composition across all cohorts (R2: 0.69–0.75). Other topographic variables that explained a substantial amount of variation in composition were catchment area (R2: 0.43–0.45) and slope (R2: 0.23–0.61). Soil chemistry (R2: 0.09–0.75) was also associated with woody vegetation composition. While species composition differed substantially between cohorts, the environmental variables explaining composition did not. These results demonstrate the overriding importance of elevation and other topographic features in discriminating tree assemblage patterns irrespective of tree size. The importance of soil characteristics to tree assemblages was also influenced by topography, where ridge top sites were typically drier and had lower soil nutrient levels than riparian areas. PMID:25501866

Global patterns of declining temperature variability from the Last Glacial Maximum to the Holocene

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Münch, Thomas; Ho, Sze Ling; Laepple, Thomas

2018-02-01

Changes in climate variability are as important for society to address as are changes in mean climate. Contrasting temperature variability during the Last Glacial Maximum and the Holocene can provide insights into the relationship between the mean state of the climate and its variability. However, although glacial-interglacial changes in variability have been quantified for Greenland, a global view remains elusive. Here we use a network of marine and terrestrial temperature proxies to show that temperature variability decreased globally by a factor of four as the climate warmed by 3-8 degrees Celsius from the Last Glacial Maximum (around 21,000 years ago) to the Holocene epoch (the past 11,500 years). This decrease had a clear zonal pattern, with little change in the tropics (by a factor of only 1.6-2.8) and greater change in the mid-latitudes of both hemispheres (by a factor of 3.3-14). By contrast, Greenland ice-core records show a reduction in temperature variability by a factor of 73, suggesting influences beyond local temperature or a decoupling of atmospheric and global surface temperature variability for Greenland. The overall pattern of reduced variability can be explained by changes in the meridional temperature gradient, a mechanism that points to further decreases in temperature variability in a warmer future.

Global patterns of declining temperature variability from the Last Glacial Maximum to the Holocene.

PubMed

Rehfeld, Kira; Münch, Thomas; Ho, Sze Ling; Laepple, Thomas

2018-02-15

Changes in climate variability are as important for society to address as are changes in mean climate. Contrasting temperature variability during the Last Glacial Maximum and the Holocene can provide insights into the relationship between the mean state of the climate and its variability. However, although glacial-interglacial changes in variability have been quantified for Greenland, a global view remains elusive. Here we use a network of marine and terrestrial temperature proxies to show that temperature variability decreased globally by a factor of four as the climate warmed by 3-8 degrees Celsius from the Last Glacial Maximum (around 21,000 years ago) to the Holocene epoch (the past 11,500 years). This decrease had a clear zonal pattern, with little change in the tropics (by a factor of only 1.6-2.8) and greater change in the mid-latitudes of both hemispheres (by a factor of 3.3-14). By contrast, Greenland ice-core records show a reduction in temperature variability by a factor of 73, suggesting influences beyond local temperature or a decoupling of atmospheric and global surface temperature variability for Greenland. The overall pattern of reduced variability can be explained by changes in the meridional temperature gradient, a mechanism that points to further decreases in temperature variability in a warmer future.

Analysis of trends and dominant periodicities in drought variables in India: A wavelet transform based approach

NASA Astrophysics Data System (ADS)

Joshi, Nitin; Gupta, Divya; Suryavanshi, Shakti; Adamowski, Jan; Madramootoo, Chandra A.

2016-12-01

In this study, seasonal trends as well as dominant and significant periods of variability of drought variables were analyzed for 30 rainfall subdivisions in India over 141 years (1871-2012). Standardized precipitation index (SPI) was used as a meteorological drought indicator, and various drought variables (monsoon SPI, non-monsoon SPI, yearly SPI, annual drought duration, annual drought severity and annual drought peak) were analyzed. Discrete wavelet transform was used in conjunction with the Mann-Kendall test to analyze trends and dominant periodicities associated with the drought variables. Furthermore, continuous wavelet transform (CWT) based global wavelet spectrum was used to analyze significant periods of variability associated with the drought variables. From the trend analysis, we observed that over the second half of the 20th century, drought occurrences increased significantly in subdivisions of Northeast and Central India. In both short-term (2-8 years) and decadal (16-32 years) periodicities, the drought variables were found to influence the trend. However, CWT analysis indicated that the dominant periodic components were not significant for most of the geographical subdivisions. Although inter-annual and inter-decadal periodic components play an important role, they may not completely explain the variability associated with the drought variables across the country.

Response of algal metrics to nutrients and physical factors and identification of nutrient thresholds in agricultural streams

USGS Publications Warehouse

Black, R.W.; Moran, P.W.; Frankforter, J.D.

2011-01-01

Many streams within the United States are impaired due to nutrient enrichment, particularly in agricultural settings. The present study examines the response of benthic algal communities in agricultural and minimally disturbed sites from across the western United States to a suite of environmental factors, including nutrients, collected at multiple scales. The first objective was to identify the relative importance of nutrients, habitat and watershed features, and macroinvertebrate trophic structure to explain algal metrics derived from deposition and erosion habitats. The second objective was to determine if thresholds in total nitrogen (TN) and total phosphorus (TP) related to algal metrics could be identified and how these thresholds varied across metrics and habitats. Nutrient concentrations within the agricultural areas were elevated and greater than published threshold values. All algal metrics examined responded to nutrients as hypothesized. Although nutrients typically were the most important variables in explaining the variation in each of the algal metrics, environmental factors operating at multiple scales also were important. Calculated thresholds for TN or TP based on the algal metrics generated from samples collected from erosion and deposition habitats were not significantly different. Little variability in threshold values for each metric for TN and TP was observed. The consistency of the threshold values measured across multiple metrics and habitats suggest that the thresholds identified in this study are ecologically relevant. Additional work to characterize the relationship between algal metrics, physical and chemical features, and nuisance algal growth would be of benefit to the development of nutrient thresholds and criteria. ?? 2010 The Author(s).

Importance of spatial autocorrelation in modeling bird distributions at a continental scale

USGS Publications Warehouse

Bahn, V.; O'Connor, R.J.; Krohn, W.B.

2006-01-01

Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent. ?? Ecography.

Phenological adjustment in arctic bird species: relative importance of snow melt and ecological factors

USGS Publications Warehouse

Liebezeit, Joseph R.; Gurney, K. E. B.; Budde, Michael E.; Zack, Steve; Ward, David H.

2014-01-01

Previous studies have documented advancement in clutch initiation dates (CIDs) in response to climate change, most notably for temperate-breeding passerines. Despite accelerated climate change in the Arctic, few studies have examined nest phenology shifts in arctic breeding species. We investigated whether CIDs have advanced for the most abundant breeding shorebird and passerine species at a long-term monitoring site in arctic Alaska. We pooled data from three additional nearby sites to determine the explanatory power of snow melt and ecological variables (predator abundance, green-up) on changes in breeding phenology. As predicted, all species (semipalmated sandpiper, Calidris pusilla, pectoral sandpiper, Calidris melanotos, red-necked phalarope, Phalaropus lobatus, red phalarope, Phalaropus fulicarius, Lapland longspur, Calcarius lapponicus) exhibited advanced CIDs ranging from 0.40 to 0.80 days/year over 9 years. Timing of snow melt was the most important variable in explaining clutch initiation advancement (“climate/snow hypothesis”) for four of the five species, while green-up was a much less important explanatory factor. We found no evidence that high predator abundances led to earlier laying dates (“predator/re-nest hypothesis”). Our results support previous arctic studies in that climate change in the cryosphere will have a strong impact on nesting phenology although factors explaining changes in nest phenology are not necessarily uniform across the entire Arctic. Our results suggest some arctic-breeding shorebird and passerine species are altering their breeding phenology to initiate nesting earlier enabling them to, at least temporarily, avoid the negative consequences of a trophic mismatch.

Response of algal metrics to nutrients and physical factors and identification of nutrient thresholds in agricultural streams.

PubMed

Black, Robert W; Moran, Patrick W; Frankforter, Jill D

2011-04-01

Many streams within the United States are impaired due to nutrient enrichment, particularly in agricultural settings. The present study examines the response of benthic algal communities in agricultural and minimally disturbed sites from across the western United States to a suite of environmental factors, including nutrients, collected at multiple scales. The first objective was to identify the relative importance of nutrients, habitat and watershed features, and macroinvertebrate trophic structure to explain algal metrics derived from deposition and erosion habitats. The second objective was to determine if thresholds in total nitrogen (TN) and total phosphorus (TP) related to algal metrics could be identified and how these thresholds varied across metrics and habitats. Nutrient concentrations within the agricultural areas were elevated and greater than published threshold values. All algal metrics examined responded to nutrients as hypothesized. Although nutrients typically were the most important variables in explaining the variation in each of the algal metrics, environmental factors operating at multiple scales also were important. Calculated thresholds for TN or TP based on the algal metrics generated from samples collected from erosion and deposition habitats were not significantly different. Little variability in threshold values for each metric for TN and TP was observed. The consistency of the threshold values measured across multiple metrics and habitats suggest that the thresholds identified in this study are ecologically relevant. Additional work to characterize the relationship between algal metrics, physical and chemical features, and nuisance algal growth would be of benefit to the development of nutrient thresholds and criteria.

The transition to increased automaticity during finger sequence learning in adult males who stutter.

PubMed

Smits-Bandstra, Sarah; De Nil, Luc; Rochon, Elizabeth

2006-01-01

The present study compared the automaticity levels of persons who stutter (PWS) and persons who do not stutter (PNS) on a practiced finger sequencing task under dual task conditions. Automaticity was defined as the amount of attention required for task performance. Twelve PWS and 12 control subjects practiced finger tapping sequences under single and then dual task conditions. Control subjects performed the sequencing task significantly faster and less variably under single versus dual task conditions while PWS' performance was consistently slow and variable (comparable to the dual task performance of control subjects) under both conditions. Control subjects were significantly more accurate on a colour recognition distracter task than PWS under dual task conditions. These results suggested that control subjects transitioned to quick, accurate and increasingly automatic performance on the sequencing task after practice, while PWS did not. Because most stuttering treatment programs for adults include practice and automatization of new motor speech skills, findings of this finger sequencing study and future studies of speech sequence learning may have important implications for how to maximize stuttering treatment effectiveness. As a result of this activity, the participant will be able to: (1) Define automaticity and explain the importance of dual task paradigms to investigate automaticity; (2) Relate the proposed relationship between motor learning and automaticity as stated by the authors; (3) Summarize the reviewed literature concerning the performance of PWS on dual tasks; and (4) Explain why the ability to transition to automaticity during motor learning may have important clinical implications for stuttering treatment effectiveness.

Hydrodynamic conditioning of diversity and functional traits in subtidal estuarine macrozoobenthic communities

NASA Astrophysics Data System (ADS)

van der Wal, Daphne; Lambert, Gwladys I.; Ysebaert, Tom; Plancke, Yves M. G.; Herman, Peter M. J.

2017-10-01

Variations in abundance and diversity of estuarine benthic macrofauna are typically described along the salinity gradient. The influence of gradients in water depth, hydrodynamic energy and sediment properties are less well known. We studied how these variables influence the distribution of subtidal macrofauna in the polyhaline zone of a temperate estuary (Westerschelde, SW Netherlands). Macrofauna density, biomass and species richness, combined in a so-called ecological richness, decreased with current velocities and median grain-size and increased with organic carbon of the sediment, in total explaining 39% of the variation. The macrofauna community composition was less well explained by the three environmental variables (approx. 12-15% in total, with current velocity explaining approx. 8%). Salinity, water depth and distance to the intertidal zone had a very limited effect on both ecological richness and the macrofauna community. The proportion of (surface) deposit feeders (including opportunistic species), decreased relative to that of omnivores and carnivores with increasing current velocity and sediment grain-size. In parallel, the proportion of burrowing sessile benthic species decreased relative to that of mobile benthic species that are able to swim. Correspondingly, spatial variations in hydrodynamics yielded distinct hotspots and coldspots in ecological richness. The findings highlight the importance of local hydrodynamic conditions for estuarine restoration and conservation. The study provides a tool based on a hydrodynamic model to assess and predict ecological richness in estuaries.

Job demands-control-social support model and coping strategies: predicting burnout and wellbeing in a group of Italian nurses.

PubMed

Pisanti, R

2012-01-01

Nursing is generally considered to be a stressful profession. The purpose of the present study was to test the core hypotheses of the job demands-control-social support model (JDCS) of Karasek & Theorell (1990). In order to refine and extend the JDCS model, we also analyzed the direct and interactive role of three coping strategies: task- oriented, emotion-oriented, and avoidance-oriented coping. Questionnaire data from 1383 nurses (77%female) were collected. Controlling for demographic variables and non-linearity of the associations between job characteristics and outcomes (job satisfaction; burnout dimensions, psychological distress, and somatic complaints), hierarchical regression analyses indicated that job control and social support combined additively (p < 0.001) with job demands to explain the wellbeing outcomes (explained variance between 6% and 28%). Coping strategies accounted for additional variance (p < 0.001; explained variance between 4% and 15%) in all outcomes except in job satisfaction. Support was found for main effects of coping. Coping strategies did not moderate the impact of job characteristics on burnout and wellbeing. Emotion-oriented coping emerged as the most important predictor and was consistently associated with higher burnout levels and lower wellbeing levels. The results demonstrated the need to include the role of individual variables in the JDCS model. The limitations of the study, and theoretical and practical implications are discussed.

Assessing the Moderating Effect of the End User in Consumer Behavior: The Acceptance of Technological Implants to Increase Innate Human Capacities.

PubMed

Pelegrín-Borondo, Jorge; Reinares-Lara, Eva; Olarte-Pascual, Cristina; Garcia-Sierra, Marta

2016-01-01

Today, technological implants are being developed to increase innate human capacities, such as memory or calculation speed, and to endow us with new ones, such as the remote control of machines. This study's aim was two-fold: first, to introduce a Cognitive-Affective-Normative (CAN) model of technology acceptance to explain the intention to use this technology in the field of consumer behavior; and second, to analyze the differences in the intention to use it based on whether the intended implant recipient is oneself or one's child (i.e., the moderating effect of the end user). A multi-group analysis was performed to compare the results between the two groups: implant "for me" (Group 1) and implant "for my child" (Group 2). The model largely explains the intention to use the insideable technology for the specified groups [variance explained (R (2)) of over 0.70 in both cases]. The most important variables were found to be "positive emotions" and (positive) "subjective norm." This underscores the need to broaden the range of factors considered to be decisive in technology acceptance to include variables related to consumers' emotions. Moreover, statistically significant differences were found between the "for me" and "for my child" models for "perceived ease of use (PEU)" and "subjective norm." These findings confirm the moderating effect of the end user on new insideable technology acceptance.

Distant drivers or local signals: where do mercury trends in western Arctic belugas originate?

PubMed

Loseto, L L; Stern, G A; Macdonald, R W

2015-03-15

Temporal trends of contaminants are monitored in Arctic higher trophic level species to inform us on the fate, transport and risk of contaminants as well as advise on global emissions. However, monitoring mercury (Hg) trends in species such as belugas challenge us, as their tissue concentrations reflect complex interactions among Hg deposition and methylation, whale physiology, dietary exposure and foraging patterns. The Beaufort Sea beluga population showed significant increases in Hg during the 1990 s; since that time an additional 10 years of data have been collected. During this time of data collection, changes in the Arctic have affected many processes that underlie the Hg cycle. Here, we examine Hg in beluga tissues and investigate factors that could contribute to the observed trends after removing the effect of age and size on Hg concentrations and dietary factors. Finally, we examine available indicators of climate variability (Arctic Oscillation (AO), the Pacific Decadal Oscillation (PDO) and sea-ice minimum (SIM) concentration) to evaluate their potential to explain beluga Hg trends. Results reveal a decline in Hg concentrations from 2002 to 2012 in the liver of older whales and the muscle of large whales. The temporal increases in Hg in the 1990 s followed by recent declines do not follow trends in Hg emission, and are not easily explained by diet markers highlighting the complexity of feeding, food web dynamics and Hg uptake. Among the regional-scale climate variables the PDO exhibited the most significant relationship with beluga Hg at an eight year lag time. This distant signal points us to consider beluga winter feeding areas. Given that changes in climate will impact ecosystems; it is plausible that these climate variables are important in explaining beluga Hg trends. Such relationships require further investigation of the multiple connections between climate variables and beluga Hg. Copyright © 2014 Elsevier B.V. All rights reserved.

Workplace Determinants of Endotoxin Exposure in Dental Healthcare Facilities in South Africa

PubMed Central

Singh, Tanusha S.; Bello, Braimoh; Mabe, Onnicah D.; Renton, Kevin; Jeebhay, Mohamed F.

2010-01-01

Objectives: Aerosols generated during dental procedures have been reported to contain endotoxin as a result of bacterial contamination of dental unit water lines. This study investigated the determinants of airborne endotoxin exposure in dental healthcare settings. Methods: The study population included dental personnel (n = 454) from five academic dental institutions in South Africa. Personal air samples (n = 413) in various dental jobs and water samples (n = 403) from dental handpieces and basin taps were collected. The chromogenic-1000 limulus amebocyte lysate assay was used to determine endotoxin levels. Exposure metrics were developed on the basis of individually measured exposures and average levels within each job category. Analysis of variance and multivariate linear regression models were constructed to ascertain the determinants of exposure in the dental group. Results: There was a 2-fold variation in personal airborne endotoxin from the least exposed (administration) to the most exposed (laboratory) jobs (geometric mean levels: 2.38 versus 5.63 EU m−3). Three percent of personal samples were above DECOS recommended exposure limit (50 EU m−3). In the univariate linear models, the age of the dental units explained the most variability observed in the personal air samples (R2 = 0.20, P < 0.001), followed by the season of the year (R2 = 0.11, P < 0.001). Other variables such as institution and total number of dental units per institution also explained a modest degree of variability. A multivariate model explaining the greatest variability (adjusted R2 = 0.40, P < 0.001) included: the age of institution buildings, total number of dental units per institution, ambient temperature, ambient air velocity, endotoxin levels in water, job category (staff versus students), dental unit model type and age of dental unit. Conclusions: Apart from job type, dental unit characteristics are important predictors of airborne endotoxin levels in this setting. PMID:20044586

Clinical Insight Into Latent Variables of Psychiatric Questionnaires for Mood Symptom Self-Assessment

PubMed Central

Saunders, Kate; Bilderbeck, Amy; Palmius, Niclas; Goodwin, Guy; De Vos, Maarten

2017-01-01

Background We recently described a new questionnaire to monitor mood called mood zoom (MZ). MZ comprises 6 items assessing mood symptoms on a 7-point Likert scale; we had previously used standard principal component analysis (PCA) to tentatively understand its properties, but the presence of multiple nonzero loadings obstructed the interpretation of its latent variables. Objective The aim of this study was to rigorously investigate the internal properties and latent variables of MZ using an algorithmic approach which may lead to more interpretable results than PCA. Additionally, we explored three other widely used psychiatric questionnaires to investigate latent variable structure similarities with MZ: (1) Altman self-rating mania scale (ASRM), assessing mania; (2) quick inventory of depressive symptomatology (QIDS) self-report, assessing depression; and (3) generalized anxiety disorder (7-item) (GAD-7), assessing anxiety. Methods We elicited responses from 131 participants: 48 bipolar disorder (BD), 32 borderline personality disorder (BPD), and 51 healthy controls (HC), collected longitudinally (median [interquartile range, IQR]: 363 [276] days). Participants were requested to complete ASRM, QIDS, and GAD-7 weekly (all 3 questionnaires were completed on the Web) and MZ daily (using a custom-based smartphone app). We applied sparse PCA (SPCA) to determine the latent variables for the four questionnaires, where a small subset of the original items contributes toward each latent variable. Results We found that MZ had great consistency across the three cohorts studied. Three main principal components were derived using SPCA, which can be tentatively interpreted as (1) anxiety and sadness, (2) positive affect, and (3) irritability. The MZ principal component comprising anxiety and sadness explains most of the variance in BD and BPD, whereas the positive affect of MZ explains most of the variance in HC. The latent variables in ASRM were identical for the patient groups but different for HC; nevertheless, the latent variables shared common items across both the patient group and HC. On the contrary, QIDS had overall very different principal components across groups; sleep was a key element in HC and BD but was absent in BPD. In GAD-7, nervousness was the principal component explaining most of the variance in BD and HC. Conclusions This study has important implications for understanding self-reported mood. MZ has a consistent, intuitively interpretable latent variable structure and hence may be a good instrument for generic mood assessment. Irritability appears to be the key distinguishing latent variable between BD and BPD and might be useful for differential diagnosis. Anxiety and sadness are closely interlinked, a finding that might inform treatment effects to jointly address these covarying symptoms. Anxiety and nervousness appear to be amongst the cardinal latent variable symptoms in BD and merit close attention in clinical practice. PMID:28546141

Factors explaining children's responses to intravenous needle insertions.

PubMed

McCarthy, Ann Marie; Kleiber, Charmaine; Hanrahan, Kirsten; Zimmerman, M Bridget; Westhus, Nina; Allen, Susan

2010-01-01

Previous research shows that numerous child, parent, and procedural variables affect children's distress responses to procedures. Cognitive-behavioral interventions such as distraction are effective in reducing pain and distress for many children undergoing these procedures. The purpose of this report was to examine child, parent, and procedural variables that explain child distress during a scheduled intravenous insertion when parents are distraction coaches for their children. A total of 542 children, between 4 and 10 years of age, and their parents participated. Child age, gender, diagnosis, and ethnicity were measured by questions developed for this study. Standardized instruments were used to measure child experience with procedures, temperament, ability to attend, anxiety, coping style, and pain sensitivity. Questions were developed to measure parent variables, including ethnicity, gender, previous experiences, and expectations, and procedural variables, including use of topical anesthetics and difficulty of procedure. Standardized instruments were used to measure parenting style and parent anxiety, whereas a new instrument was developed to measure parent performance of distraction. Children's distress responses were measured with the Observation Scale of Behavioral Distress-Revised (behavioral), salivary cortisol (biological), Oucher Pain Scale (self-report), and parent report of child distress (parent report). Regression methods were used for data analyses. Variables explaining behavioral, child-report and parent-report measures include child age, typical coping response, and parent expectation of distress (p < .01). Level of parents' distraction coaching explained a significant portion of behavioral, biological, and parent-report distress measures (p < .05). Child impulsivity and special assistance at school also significantly explained child self-report of pain (p < .05). Additional variables explaining cortisol response were child's distress in the morning before clinic, diagnoses of attention deficit hyperactivity disorder or anxiety disorder, and timing of preparation for the clinic visit. The findings can be used to identify children at risk for high distress during procedures. This is the first study to find a relationship between child behavioral distress and level of parent distraction coaching.

Drought and Snow: Analysis of Drivers, Processes and Impacts of Streamflow Droughts in Snow-Dominated Regions

NASA Astrophysics Data System (ADS)

Van Loon, Anne; Laaha, Gregor; Van Lanen, Henny; Parajka, Juraj; Fleig, Anne; Ploum, Stefan

2016-04-01

Around the world, drought events with severe socio-economic impacts seem to have a link with winter snowpack. That is the case for the current California drought, but analysing historical archives and drought impact databases for the US and Europe we found many impacts that can be attributed to snowpack anomalies. Agriculture and electricity production (hydropower) were found to be the sectors that are most affected by drought related to snow. In this study, we investigated the processes underlying hydrological drought in snow-dominated regions. We found that drought drivers are different in different regions. In Norway, more than 90% of spring streamflow droughts were preceded by below-average winter precipitation, while both winter air temperature and spring weather were indifferent. In Austria, however, spring streamflow droughts could only be explained by a combination of factors. For most events, winter and spring air temperatures were above average (70% and 65% of events, respectively), and winter and spring precipitation was below average (75% and 80%). Because snow storage results from complex interactions between precipitation and temperature and these variables vary strongly with altitude, snow-related drought drivers have a large spatial variability. The weather input is subsequently modified by land properties. Multiple linear regression between drought severity variables and a large number of catchment characteristics for 44 catchments in Austria showed that storage influences both drought duration and deficit volume. The seasonal storage of water in snow and glaciers was found to be a statistically important variable explaining streamflow drought deficit. Our drought impact analysis in Europe also showed that 40% of the selected drought impacts was caused by a combination of snow-related and other drought types. For example, the combination of a winter drought with a preceding or subsequent summer drought was reported to have a large effect on reservoir levels and, consequently, on drinking water and electricity production. Snow storage therefore, is an important factor to consider in drought monitoring, prediction and management.

Drought and Snow: Analysis of Drivers, Processes and Impacts of Streamflow Droughts in Snow-Dominated Regions

NASA Astrophysics Data System (ADS)

Van Loon, A.; Laaha, G.; Van Lanen, H.; Parajka, J.; Fleig, A. K.; Ploum, S.

2015-12-01

Around the world, drought events with severe socio-economic impacts seem to have a link with winter snowpack. That is the case for the current California drought, but analysing historical archives and drought impact databases for the US and Europe we found many impacts that can be attributed to snowpack anomalies. Agriculture and electricity production (hydropower) were found to be the sectors that are most affected by drought related to snow. In this study, we investigated the processes underlying hydrological drought in snow-dominated regions. We found that drought drivers are different in different regions. In Norway, more than 90% of spring streamflow droughts were preceded by below-average winter precipitation, while both winter air temperature and spring weather were indifferent. In Austria, however, spring streamflow droughts could only be explained by a combination of factors. For most events, winter and spring air temperatures were above average (70% and 65% of events, respectively), and winter and spring precipitation was below average (75% and 80%). Because snow storage results from complex interactions between precipitation and temperature and these variables vary strongly with altitude, snow-related drought drivers have a large spatial variability. The weather input is subsequently modified by land properties. Multiple linear regression between drought severity variables and a large number of catchment characteristics for 44 catchments in Austria showed that storage influences both drought duration and deficit volume. The seasonal storage of water in snow and glaciers was found to be a statistically important variable explaining streamflow drought deficit. Our drought impact analysis in Europe also showed that 40% of the selected drought impacts was caused by a combination of snow-related and other drought types. For example, the combination of a winter drought with a preceding or subsequent summer drought was reported to have a large effect on reservoir levels and, consequently, on drinking water and electricity production. Snow storage therefore, is an important factor to consider in drought monitoring, prediction and management.

Impact of Québec's healthcare reforms on the organization of primary healthcare (PHC): a 2003-2010 follow-up.

PubMed

Pineault, Raynald; Borgès Da Silva, Roxane; Prud'homme, Alexandre; Fournier, Michel; Couture, Audrey; Provost, Sylvie; Levesque, Jean-Frédéric

2014-05-21

Healthcare reforms initiated in the early 2000s in Québec involved the implementation of new modes of primary healthcare (PHC) delivery and the creation of Health and Social Services Centers (HSSCs) to support it. The objective of this article is to assess and explain the degree of PHC organizational change achieved following these reforms. We conducted two surveys of PHC organizations, in 2005 and 2010, in two regions of the province of Québec, Canada. From the responses to these surveys, we derived a measure of organizational change based on an index of conformity to an ideal type (ICIT). One set of explanatory variables was contextual, related to coercive, normative and mimetic influences; the other consisted of organizational variables that measured receptivity towards new PHC models. Multilevel analyses were performed to examine the relationships between ICIT change in the post-reform period and the explanatory variables. Positive results were attained, as expressed by increase in the ICIT score in the post-reform period, mainly due to implementation of new types of PHC organizations (Family Medicine Groups and Network Clinics). Organizational receptivity was the main explanatory variable mediating the effect of coercive and mimetic influences. Normative influence was not a significant factor in explaining changes. Changes were modest at the system level but important with regard to new forms of PHC organizations. The top-down decreed reform was a determining factor in initiating change whereas local coercive and normative influences did not play a major role. The exemplar role played by certain PHC organizations through mimetic influence was more important. Receptivity of individual organizations was both a necessary condition and a mediating factor in influencing change. This supports the view that a combination of top-down and bottom-up strategy is best suited for achieving substantial changes in PHC local organization.

Impact of Québec’s healthcare reforms on the organization of primary healthcare (PHC): a 2003-2010 follow-up

PubMed Central

2014-01-01

Background Healthcare reforms initiated in the early 2000s in Québec involved the implementation of new modes of primary healthcare (PHC) delivery and the creation of Health and Social Services Centers (HSSCs) to support it. The objective of this article is to assess and explain the degree of PHC organizational change achieved following these reforms. Methods We conducted two surveys of PHC organizations, in 2005 and 2010, in two regions of the province of Québec, Canada. From the responses to these surveys, we derived a measure of organizational change based on an index of conformity to an ideal type (ICIT). One set of explanatory variables was contextual, related to coercive, normative and mimetic influences; the other consisted of organizational variables that measured receptivity towards new PHC models. Multilevel analyses were performed to examine the relationships between ICIT change in the post-reform period and the explanatory variables. Results Positive results were attained, as expressed by increase in the ICIT score in the post-reform period, mainly due to implementation of new types of PHC organizations (Family Medicine Groups and Network Clinics). Organizational receptivity was the main explanatory variable mediating the effect of coercive and mimetic influences. Normative influence was not a significant factor in explaining changes. Conclusion Changes were modest at the system level but important with regard to new forms of PHC organizations. The top-down decreed reform was a determining factor in initiating change whereas local coercive and normative influences did not play a major role. The exemplar role played by certain PHC organizations through mimetic influence was more important. Receptivity of individual organizations was both a necessary condition and a mediating factor in influencing change. This supports the view that a combination of top-down and bottom-up strategy is best suited for achieving substantial changes in PHC local organization. PMID:24886490

Sulfur dioxide in the Venus atmosphere: I. Vertical distribution and variability

NASA Astrophysics Data System (ADS)

Vandaele, A. C.; Korablev, O.; Belyaev, D.; Chamberlain, S.; Evdokimova, D.; Encrenaz, Th.; Esposito, L.; Jessup, K. L.; Lefèvre, F.; Limaye, S.; Mahieux, A.; Marcq, E.; Mills, F. P.; Montmessin, F.; Parkinson, C. D.; Robert, S.; Roman, T.; Sandor, B.; Stolzenbach, A.; Wilson, C.; Wilquet, V.

2017-10-01

Recent observations of sulfur containing species (SO2, SO, OCS, and H2SO4) in Venus' mesosphere have generated controversy and great interest in the scientific community. These observations revealed unexpected spatial patterns and spatial/temporal variability that have not been satisfactorily explained by models. Sulfur oxide chemistry on Venus is closely linked to the global-scale cloud and haze layers, which are composed primarily of concentrated sulfuric acid. Sulfur oxide observations provide therefore important insight into the on-going chemical evolution of Venus' atmosphere, atmospheric dynamics, and possible volcanism. This paper is the first of a series of two investigating the SO2 and SO variability in the Venus atmosphere. This first part of the study will focus on the vertical distribution of SO2, considering mostly observations performed by instruments and techniques providing accurate vertical information. This comprises instruments in space (SPICAV/SOIR suite on board Venus Express) and Earth-based instruments (JCMT). The most noticeable feature of the vertical profile of the SO2 abundance in the Venus atmosphere is the presence of an inversion layer located at about 70-75 km, with VMRs increasing above. The observations presented in this compilation indicate that at least one other significant sulfur reservoir (in addition to SO2 and SO) must be present throughout the 70-100 km altitude region to explain the inversion in the SO2 vertical profile. No photochemical model has an explanation for this behaviour. GCM modelling indicates that dynamics may play an important role in generating an inflection point at 75 km altitude but does not provide a definitive explanation of the source of the inflection at all local times or latitudes The current study has been carried out within the frame of the International Space Science Institute (ISSI) International Team entitled 'SO2 variability in the Venus atmosphere'.

Tree-, stand- and site-specific controls on landscape-scale patterns of transpiration

NASA Astrophysics Data System (ADS)

Hassler, Sibylle; Markus, Weiler; Theresa, Blume

2017-04-01

Transpiration is a key process in the hydrological cycle and a sound understanding and quantification of transpiration and its spatial variability is essential for management decisions as well as for improving the parameterisation of hydrological and soil-vegetation-atmosphere transfer models. For individual trees, transpiration is commonly estimated by measuring sap flow. Besides evaporative demand and water availability, tree-specific characteristics such as species, size or social status control sap flow amounts of individual trees. Within forest stands, properties such as species composition, basal area or stand density additionally affect sap flow, for example via competition mechanisms. Finally, sap flow patterns might also be influenced by landscape-scale characteristics such as geology, slope position or aspect because they affect water and energy availability; however, little is known about the dynamic interplay of these controls. We studied the relative importance of various tree-, stand- and site-specific characteristics with multiple linear regression models to explain the variability of sap velocity measurements in 61 beech and oak trees, located at 24 sites spread over a 290 km2-catchment in Luxembourg. For each of 132 consecutive days of the growing season of 2014 we modelled the daily sap velocities of these 61 trees and determined the importance of the different predictors. Results indicate that a combination of tree-, stand- and site-specific factors controls sap velocity patterns in the landscape, namely tree species, tree diameter, the stand density, geology and aspect. Compared to these predictors, spatial variability of atmospheric demand and soil moisture explains only a small fraction of the variability in the daily datasets. However, the temporal dynamics of the explanatory power of the tree-specific characteristics, especially species, are correlated to the temporal dynamics of potential evaporation. Thus, transpiration estimates at the landscape scale would benefit from not only considering hydro-meteorological drivers, but also including tree, stand and site characteristics in order to improve the spatial representation of transpiration for hydrological and soil-vegetation-atmosphere transfer models.

Correspondence of biological condition models of California streams at statewide and regional scales.

PubMed

May, Jason T; Brown, Larry R; Rehn, Andrew C; Waite, Ian R; Ode, Peter R; Mazor, Raphael D; Schiff, Kenneth C

2015-01-01

We used boosted regression trees (BRT) to model stream biological condition as measured by benthic macroinvertebrate taxonomic completeness, the ratio of observed to expected (O/E) taxa. Models were developed with and without exclusion of rare taxa at a site. BRT models are robust, requiring few assumptions compared with traditional modeling techniques such as multiple linear regression. The BRT models were constructed to provide baseline support to stressor delineation by identifying natural physiographic and human land use gradients affecting stream biological condition statewide and for eight ecological regions within the state, as part of the development of numerical biological objectives for California's wadeable streams. Regions were defined on the basis of ecological, hydrologic, and jurisdictional factors and roughly corresponded with ecoregions. Physiographic and land use variables were derived from geographic information system coverages. The model for the entire state (n = 1,386) identified a composite measure of anthropogenic disturbance (the sum of urban, agricultural, and unmanaged roadside vegetation land cover) within the local watershed as the most important variable, explaining 56% of the variance in O/E values. Models for individual regions explained between 51 and 84% of the variance in O/E values. Measures of human disturbance were important in the three coastal regions. In the South Coast and Coastal Chaparral, local watershed measures of urbanization were the most important variables related to biological condition, while in the North Coast the composite measure of human disturbance at the watershed scale was most important. In the two mountain regions, natural gradients were most important, including slope, precipitation, and temperature. The remaining three regions had relatively small sample sizes (n ≤ 75 sites) and had models that gave mixed results. Understanding the spatial scale at which land use and land cover affect taxonomic completeness is imperative for sound management. Our results suggest that invertebrate taxonomic completeness is affected by human disturbance at the statewide and regional levels, with some differences among regions in the importance of natural gradients and types of human disturbance. The construction and application of models similar to the ones presented here could be useful in the planning and prioritization of actions for protection and conservation of biodiversity in California streams.

Correspondence of biological condition models of California streams at statewide and regional scales

USGS Publications Warehouse

May, Jason T.; Brown, Larry R.; Rehn, Andrew C.; Waite, Ian R.; Ode, Peter R; Mazor, Raphael D; Schiff, Kenneth C

2015-01-01

We used boosted regression trees (BRT) to model stream biological condition as measured by benthic macroinvertebrate taxonomic completeness, the ratio of observed to expected (O/E) taxa. Models were developed with and without exclusion of rare taxa at a site. BRT models are robust, requiring few assumptions compared with traditional modeling techniques such as multiple linear regression. The BRT models were constructed to provide baseline support to stressor delineation by identifying natural physiographic and human land use gradients affecting stream biological condition statewide and for eight ecological regions within the state, as part of the development of numerical biological objectives for California’s wadeable streams. Regions were defined on the basis of ecological, hydrologic, and jurisdictional factors and roughly corresponded with ecoregions. Physiographic and land use variables were derived from geographic information system coverages. The model for the entire state (n = 1,386) identified a composite measure of anthropogenic disturbance (the sum of urban, agricultural, and unmanaged roadside vegetation land cover) within the local watershed as the most important variable, explaining 56 % of the variance in O/E values. Models for individual regions explained between 51 and 84 % of the variance in O/E values. Measures of human disturbance were important in the three coastal regions. In the South Coast and Coastal Chaparral, local watershed measures of urbanization were the most important variables related to biological condition, while in the North Coast the composite measure of human disturbance at the watershed scale was most important. In the two mountain regions, natural gradients were most important, including slope, precipitation, and temperature. The remaining three regions had relatively small sample sizes (n ≤ 75 sites) and had models that gave mixed results. Understanding the spatial scale at which land use and land cover affect taxonomic completeness is imperative for sound management. Our results suggest that invertebrate taxonomic completeness is affected by human disturbance at the statewide and regional levels, with some differences among regions in the importance of natural gradients and types of human disturbance. The construction and application of models similar to the ones presented here could be useful in the planning and prioritization of actions for protection and conservation of biodiversity in California streams.

Fish mucus metabolome reveals fish life-history traits

NASA Astrophysics Data System (ADS)

Reverter, M.; Sasal, P.; Banaigs, B.; Lecchini, D.; Lecellier, G.; Tapissier-Bontemps, N.

2017-06-01

Fish mucus has important biological and ecological roles such as defense against fish pathogens and chemical mediation among several species. A non-targeted liquid chromatography-mass spectrometry metabolomic approach was developed to study gill mucus of eight butterflyfish species in Moorea (French Polynesia), and the influence of several fish traits (geographic site and reef habitat, species taxonomy, phylogeny, diet and parasitism levels) on the metabolic variability was investigated. A biphasic extraction yielding two fractions (polar and apolar) was used. Fish diet (obligate corallivorous, facultative corallivorous or omnivorous) arose as the main driver of the metabolic differences in the gill mucus in both fractions, accounting for 23% of the observed metabolic variability in the apolar fraction and 13% in the polar fraction. A partial least squares discriminant analysis allowed us to identify the metabolites (variable important in projection, VIP) driving the differences between fish with different diets (obligate corallivores, facultative corallivores and omnivorous). Using accurate mass data and fragmentation data, we identified some of these VIP as glycerophosphocholines, ceramides and fatty acids. Level of monogenean gill parasites was the second most important factor shaping the gill mucus metabolome, and it explained 10% of the metabolic variability in the polar fraction and 5% in the apolar fraction. A multiple regression tree revealed that the metabolic variability due to parasitism in the polar fraction was mainly due to differences between non-parasitized and parasitized fish. Phylogeny and butterflyfish species were factors contributing significantly to the metabolic variability of the apolar fraction (10 and 3%, respectively) but had a less pronounced effect in the polar fraction. Finally, geographic site and reef habitat of butterflyfish species did not influence the gill mucus metabolome of butterflyfishes.

Combined role of heat and water stresses on wheat, maize and rice inter-annual variability and trend from 1980 to 2010.

NASA Astrophysics Data System (ADS)

Zampieri, M.; Ceglar, A., , Dr; Dentener, F., , Dr; van den Berg, M., , Dr; Toreti, A., , Dr

2017-12-01

Heat waves and drought are often considered the most damaging climatic stressors for wheat and maize. In this study, based on data derived from observations, we characterize and attribute the effects of these climate extremes on wheat and maize yield anomalies (at global and national scales) with respect to the mean trend from 1980 to 2010. Using a combination of up-to-date heat wave and drought indexes (i.e. the Heat Magnitude Day, HMD, and the Standardized Precipitation Evapotranspiration Index, SPEI), we have developed a composite indicator (i.e. the Combined Stress Index, CSI) that is able to capture the spatio-temporal characteristics of the underlying physical processes in the different agro-climatic regions of the world. At the global level, our diagnostic explains the 42% and the 50% of the inter-annual wheat and maize production variabilities, respectively. The relative importance of heat stress and drought in determining the yield anomalies depends on the region. Compared to maize, and in contrast to common perception, water excess affects wheat production more than drought in several countries. The index definition can be modified in order to quantify the role of combined heat and water stress events occurrence in determining the recorded yield trends as well. Climate change is increasingly limiting maize yields in several countries, especially in Europe and China. A comparable opposite signal, albeit less statistically significant, is found for the USA, which is the main world producer. As for rice, we provide a statistical evidence pointing out to the importance of considering the interactions with the horizontal surface waters fluxes carried out by the rivers. In fact, compared to wheat and maize, the CSI statistical skills in explaining rice production variability are quite reduced. This issue is particularly relevant in paddy fields and flooded lowlands where rice is mainly grown. Therefore, we have modified the procedure including a proxy for the surface freshwater availability i.e. the Standardized River Discharge Index (SRDI), defined in this study. The modified CSI explains the 35% of the global rice production inter-annual anomalies.

Quantitative research.

PubMed

Watson, Roger

2015-04-01

This article describes the basic tenets of quantitative research. The concepts of dependent and independent variables are addressed and the concept of measurement and its associated issues, such as error, reliability and validity, are explored. Experiments and surveys – the principal research designs in quantitative research – are described and key features explained. The importance of the double-blind randomised controlled trial is emphasised, alongside the importance of longitudinal surveys, as opposed to cross-sectional surveys. Essential features of data storage are covered, with an emphasis on safe, anonymous storage. Finally, the article explores the analysis of quantitative data, considering what may be analysed and the main uses of statistics in analysis.

Plant structure predicts leaf litter capture in the tropical montane bromeliad Tillandsia turneri.

PubMed

Ospina-Bautista, F; Estévez Varón, J V

2016-05-03

Leaves intercepted by bromeliads become an important energy and matter resource for invertebrate communities, bacteria, fungi, and the plant itself. The relationship between bromeliad structure, defined as its size and complexity, and accumulated leaf litter was studied in 55 bromeliads of Tillandsia turneri through multiple regression and the Akaike information criterion. Leaf litter accumulation in bromeliads was best explained by size and complexity variables such as plant cover, sheath length, and leaf number. In conclusion, plant structure determines the amount of litter that enters bromeliads, and changes in its structure could affect important processes within ecosystem functioning or species richness.

The Relative Importance of Spatial and Local Environmental Factors in Determining Beetle Assemblages in the Inner Mongolia Grassland.

PubMed

Yu, Xiao-Dong; Lü, Liang; Wang, Feng-Yan; Luo, Tian-Hong; Zou, Si-Si; Wang, Cheng-Bin; Song, Ting-Ting; Zhou, Hong-Zhang

2016-01-01

The aim of this paper is to increase understanding of the relative importance of the input of geographic and local environmental factors on richness and composition of epigaeic steppe beetles (Coleoptera: Carabidae and Tenebrionidae) along a geographic (longitudinal/precipitation) gradient in the Inner Mongolia grassland. Specifically, we evaluate the associations of environmental variables representing climate and environmental heterogeneity with beetle assemblages. Beetles were sampled using pitfall traps at 25 sites scattered across the full geographic extent of the study biome in 2011-2012. We used variance partitioning techniques and multi-model selection based on the Akaike information criterion to assess the relative importance of the spatial and environmental variables on beetle assemblages. Species richness and abundance showed unimodal patterns along the geographic gradient. Together with space, climate variables associated with precipitation, water-energy balance and harshness of climate had strong explanatory power in richness pattern. Abundance pattern showed strongest association with variation in temperature and environmental heterogeneity. Climatic factors associated with temperature and precipitation variables and the interaction between climate with space were able to explain a substantial amount of variation in community structure. In addition, the turnover of species increased significantly as geographic distances increased. We confirmed that spatial and local environmental factors worked together to shape epigaeic beetle communities along the geographic gradient in the Inner Mongolia grassland. Moreover, the climate features, especially precipitation, water-energy balance and temperature, and the interaction between climate with space and environmental heterogeneity appeared to play important roles on controlling richness and abundance, and species compositions of epigaeic beetles.

[Effects of environmental factors on β diversity of zooplankton community in thermal discharge seawaters near Guohua Power Plant in Xiangshan Bay, Zhejiang, China].

PubMed

Zhu, Yi-feng; Dai, Mei-xia; Zhou, Xiao-hong; Lin, Xia; Mao, Shuo-qian; Yan, Xiao-jun

2015-08-01

Zooplankton samples were seasonally collected at 10 stations in thermal discharge seawaters near Guohua Power Plant in Xiangshan Bay. The abundance data from these samples were pooled and further combined with field environmental factors, then generalised dissimilarity modelling (GDM) was used to explore the effects of environmental factors on β diversity of zooplankton community. The results showed that altogether 95 species of zooplankton belonging to 14 taxa were found. In these taxa, small zooplankton with 62.6% of abundance was the main taxa, while copepods dominated in adult groups, which abundance accounted for 35.3%. According to Whittaker's definition and additive partition, a diversity accounted for 36.3% and β diversity 63.7%. Environmental factors explained 43.8% of β diversity, and geographical distance between sampling sites had no effect on β diversity. However, there were still 19.9% of β diversity remained to be explained. After GDM fitting, there were nine environmental variables affecting zooplankton β diversity and explaining 68.8% of β diversity. The variables contributing to β diversity from high to low were seasonal water temperature, dissolved oxygen, seawater temperature increment, conductivity, suspended particulate matter, salinity, transparency, water depth and redox potential, respectively. Seasonal water temperature, dissolved oxygen and seawater temperature increment were the most important factors for driving β diversity changes, and accounted for 23.9%, 13.7% and 9.7% of absolute contribution to the interpretable portion of the β diversity, respectively. When seasonal water temperature, dissolved oxygen and seawater temperature increment were below 25 °C, greater than 5 mg · L(-1) and over 1 °C, respectively, β diversity rapidly increased with the increasing variable gradients. Furthermore, other predictors had little effect on β diversity.

Antarctic Ice Mass Balance from GRACE

NASA Astrophysics Data System (ADS)

Boening, C.; Firing, Y. L.; Wiese, D. N.; Watkins, M. M.; Schlegel, N.; Larour, E. Y.

2014-12-01

The Antarctic ice mass balance and rates of change of ice mass over the past decade are analyzed based on observations from the Gravity Recovery and Climate Experiment (GRACE) satellites, in the form of JPL RL05M mascon solutions. Surface mass balance (SMB) fluxes from ERA-Interim and other atmospheric reanalyses successfully account for the seasonal GRACE-measured mass variability, and explain 70-80% of the continent-wide mass variance at interannual time scales. Trends in the residual (GRACE mass - SMB accumulation) mass time series in different Antarctic drainage basins are consistent with time-mean ice discharge rates based on radar-derived ice velocities and thicknesses. GRACE also resolves accelerations in regional ice mass change rates, including increasing rates of mass gain in East Antarctica and accelerating ice mass loss in West Antarctica. The observed East Antarctic mass gain is only partially explained by anomalously large SMB events in the second half of the record, potentially implying that ice discharge rates are also decreasing in this region. Most of the increasing mass loss rate in West Antarctica, meanwhile, is explained by decreasing SMB (principally precipitation) over this time period, part of the characteristic decadal variability in regional SMB. The residual acceleration of 2+/-1 Gt/yr, which is concentrated in the Amundsen Sea Embayment (ASE) basins, represents the contribution from increasing ice discharge rates. An Ice Sheet System Model (ISSM) run with constant ocean forcing and stationary grounding lines both underpredicts the largest trends in the ASE and produces negligible acceleration or interannual variability in discharge, highlighting the potential importance of ocean forcing for setting ice discharge rates at interannual to decadal time scales.

Characterizing Individual Differences in Functional Connectivity Using Dual-Regression and Seed-Based Approaches

PubMed Central

Smith, David V.; Utevsky, Amanda V.; Bland, Amy R.; Clement, Nathan; Clithero, John A.; Harsch, Anne E. W.; Carter, R. McKell; Huettel, Scott A.

2014-01-01

A central challenge for neuroscience lies in relating inter-individual variability to the functional properties of specific brain regions. Yet, considerable variability exists in the connectivity patterns between different brain areas, potentially producing reliable group differences. Using sex differences as a motivating example, we examined two separate resting-state datasets comprising a total of 188 human participants. Both datasets were decomposed into resting-state networks (RSNs) using a probabilistic spatial independent components analysis (ICA). We estimated voxelwise functional connectivity with these networks using a dual-regression analysis, which characterizes the participant-level spatiotemporal dynamics of each network while controlling for (via multiple regression) the influence of other networks and sources of variability. We found that males and females exhibit distinct patterns of connectivity with multiple RSNs, including both visual and auditory networks and the right frontal-parietal network. These results replicated across both datasets and were not explained by differences in head motion, data quality, brain volume, cortisol levels, or testosterone levels. Importantly, we also demonstrate that dual-regression functional connectivity is better at detecting inter-individual variability than traditional seed-based functional connectivity approaches. Our findings characterize robust—yet frequently ignored—neural differences between males and females, pointing to the necessity of controlling for sex in neuroscience studies of individual differences. Moreover, our results highlight the importance of employing network-based models to study variability in functional connectivity. PMID:24662574

China's Air Quality and Respiratory Disease Mortality Based on the Spatial Panel Model.

PubMed

Cao, Qilong; Liang, Ying; Niu, Xueting

2017-09-18

Background : Air pollution has become an important factor restricting China's economic development and has subsequently brought a series of social problems, including the impact of air pollution on the health of residents, which is a topical issue in China. Methods : Taking into account this spatial imbalance, the paper is based on the spatial panel data model PM 2.5 . Respiratory disease mortality in 31 Chinese provinces from 2004 to 2008 is taken as the main variable to study the spatial effect and impact of air quality and respiratory disease mortality on a large scale. Results : It was found that there is a spatial correlation between the mortality of respiratory diseases in Chinese provinces. The spatial correlation can be explained by the spatial effect of PM 2.5 pollutions in the control of other variables. Conclusions : Compared with the traditional non-spatial model, the spatial model is better for describing the spatial relationship between variables, ensuring the conclusions are scientific and can measure the spatial effect between variables.

Computation of Standard Errors

PubMed Central

Dowd, Bryan E; Greene, William H; Norton, Edward C

2014-01-01

Objectives We discuss the problem of computing the standard errors of functions involving estimated parameters and provide the relevant computer code for three different computational approaches using two popular computer packages. Study Design We show how to compute the standard errors of several functions of interest: the predicted value of the dependent variable for a particular subject, and the effect of a change in an explanatory variable on the predicted value of the dependent variable for an individual subject and average effect for a sample of subjects. Empirical Application Using a publicly available dataset, we explain three different methods of computing standard errors: the delta method, Krinsky–Robb, and bootstrapping. We provide computer code for Stata 12 and LIMDEP 10/NLOGIT 5. Conclusions In most applications, choice of the computational method for standard errors of functions of estimated parameters is a matter of convenience. However, when computing standard errors of the sample average of functions that involve both estimated parameters and nonstochastic explanatory variables, it is important to consider the sources of variation in the function's values. PMID:24800304

Spike-Threshold Adaptation Predicted by Membrane Potential Dynamics In Vivo

PubMed Central

Fontaine, Bertrand; Peña, José Luis; Brette, Romain

2014-01-01

Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo. PMID:24722397

Relevance of Student and Contextual School Variables in Explaining a Student's Severity of Violence Experienced

ERIC Educational Resources Information Center

Mooij, Ton

2015-01-01

Teachers conceptualise and interpret violent behaviour of secondary students in different ways. They also differ in their estimates of the relevance of student and contextual school variables when explaining the severity of violence experienced by students. Research can assist here by explicating the role of different types of contextual school…

A study into psychosocial factors as predictors of work-related fatigue.

PubMed

Rahman, Hanif Abdul; Abdul-Mumin, Khadizah; Naing, Lin

2016-07-14

To explore and determine relationship between psychosocial factors and work-related fatigue among emergency and critical care nurses in Brunei. Cross-sectional study conducted on all emergency and critical care nurses across Brunei public hospitals from February to April 2016. 201 nurses participated in the study (82% response rate). A total of 36% of the variance of chronic fatigue was explained by stress, trust in management, decision latitude, self-rated health, and work-family conflict. Burnout, self-rated health, commitment to workplace, and trust in management explained 30% of the variance of acute fatigue. Stress, work-family conflict and reward explained 28% of the variance of intershift recovery after controlling for significant sociodemographic variables. Smoking was identified as an important sociodemographic factor for work-related fatigue. Psychosocial factors were good predictors of work-related fatigue. A range of psychosocial factors were established, however more research is required to determine all possible causation factors of nurses' work-related fatigue.

Oral health care activities performed by caregivers for institutionalized elderly in Barcelona-Spain

PubMed Central

Cornejo-Ovalle, Marco; Costa-de-Lima, Kenio; Pérez, Glória; Borrell, Carme; Casals-Peidro, Elías

2013-01-01

Objectives: To describe the frequency of brushing teeth and cleaning of dentures, performed by caregivers, for institutionalized elderly people. Methods: A cross-sectional study in a sample of 196 caregivers of 31 health centers in Barcelona. The dependent variables were frequency of dental brushing and frequency of cleaning of dentures of the elderly by caregivers. The independent variables were characteristics of caregivers and institutions. We performed bivariate and multivariate descriptive analyses. Robust Poisson regression models were fitted to determine factors associated with the dependent variables and to assess the strength of the association. Results: 83% of caregivers were women, 79% worked on more than one shift, 42% worked only out of necessity, 92% were trained to care for elderly persons, 67% were trained in oral hygiene care for the elderly, and 73% recognized the existence of institutional protocols on oral health among residents. The variables explaining the lower frequency of brushing teeth by caregivers for the elderly, adjusted for the workload, were: no training in the care of elderly persons (PRa 1.7 CI95%: 1.6-1.8), not fully agreeing with the importance of oral health care of the elderly (PRa 2.5 CI95%: 1.5-4.1) and not knowing of the existence of oral health protocols (PRa 1.8 CI95%: 1.2-2.6). The variables that explain the lower frequency of cleaning dentures, adjusted for the workload, were lack of training in elderly care (PRa 1.7 CI95%: 1.3-1.9) and not knowing of the existence of protocols (PRa 3.7 CI95%: 1.6-8.7). Conclusion: The majority of caregivers perform activities of oral health care for the elderly at least once per day. The frequency of this care depends mainly on whether caregivers are trained to perform these activities, the importance given to oral health, the workload of caregivers and the existence of institutional protocols on oral health of institutionalized elderly persons. Key words:Institutionalized elderly, caregivers, oral hygiene, long-term care, oral health. PMID:23524433

What explains usage of mobile physician-rating apps? Results from a web-based questionnaire.

PubMed

Bidmon, Sonja; Terlutter, Ralf; Röttl, Johanna

2014-06-11

Consumers are increasingly accessing health-related information via mobile devices. Recently, several apps to rate and locate physicians have been released in the United States and Germany. However, knowledge about what kinds of variables explain usage of mobile physician-rating apps is still lacking. This study analyzes factors influencing the adoption of and willingness to pay for mobile physician-rating apps. A structural equation model was developed based on the Technology Acceptance Model and the literature on health-related information searches and usage of mobile apps. Relationships in the model were analyzed for moderating effects of physician-rating website (PRW) usage. A total of 1006 randomly selected German patients who had visited a general practitioner at least once in the 3 months before the beginning of the survey were randomly selected and surveyed. A total of 958 usable questionnaires were analyzed by partial least squares path modeling and moderator analyses. The suggested model yielded a high model fit. We found that perceived ease of use (PEOU) of the Internet to gain health-related information, the sociodemographic variables age and gender, and the psychographic variables digital literacy, feelings about the Internet and other Web-based applications in general, patients' value of health-related knowledgeability, as well as the information-seeking behavior variables regarding the amount of daily private Internet use for health-related information, frequency of using apps for health-related information in the past, and attitude toward PRWs significantly affected the adoption of mobile physician-rating apps. The sociodemographic variable age, but not gender, and the psychographic variables feelings about the Internet and other Web-based applications in general and patients' value of health-related knowledgeability, but not digital literacy, were significant predictors of willingness to pay. Frequency of using apps for health-related information in the past and attitude toward PRWs, but not the amount of daily Internet use for health-related information, were significant predictors of willingness to pay. The perceived usefulness of the Internet to gain health-related information and the amount of daily Internet use in general did not have any significant effect on both of the endogenous variables. The moderation analysis with the group comparisons for users and nonusers of PRWs revealed that the attitude toward PRWs had significantly more impact on the adoption and willingness to pay for mobile physician-rating apps in the nonuser group. Important variables that contribute to the adoption of a mobile physician-rating app and the willingness to pay for it were identified. The results of this study are important for researchers because they can provide important insights about the variables that influence the acceptance of apps that allow for ratings of physicians. They are also useful for creators of mobile physician-rating apps because they can help tailor mobile physician-rating apps to the consumers' characteristics and needs.

What Explains Usage of Mobile Physician-Rating Apps? Results From a Web-Based Questionnaire

PubMed Central

Terlutter, Ralf; Röttl, Johanna

2014-01-01

Background Consumers are increasingly accessing health-related information via mobile devices. Recently, several apps to rate and locate physicians have been released in the United States and Germany. However, knowledge about what kinds of variables explain usage of mobile physician-rating apps is still lacking. Objective This study analyzes factors influencing the adoption of and willingness to pay for mobile physician-rating apps. A structural equation model was developed based on the Technology Acceptance Model and the literature on health-related information searches and usage of mobile apps. Relationships in the model were analyzed for moderating effects of physician-rating website (PRW) usage. Methods A total of 1006 randomly selected German patients who had visited a general practitioner at least once in the 3 months before the beginning of the survey were randomly selected and surveyed. A total of 958 usable questionnaires were analyzed by partial least squares path modeling and moderator analyses. Results The suggested model yielded a high model fit. We found that perceived ease of use (PEOU) of the Internet to gain health-related information, the sociodemographic variables age and gender, and the psychographic variables digital literacy, feelings about the Internet and other Web-based applications in general, patients’ value of health-related knowledgeability, as well as the information-seeking behavior variables regarding the amount of daily private Internet use for health-related information, frequency of using apps for health-related information in the past, and attitude toward PRWs significantly affected the adoption of mobile physician-rating apps. The sociodemographic variable age, but not gender, and the psychographic variables feelings about the Internet and other Web-based applications in general and patients’ value of health-related knowledgeability, but not digital literacy, were significant predictors of willingness to pay. Frequency of using apps for health-related information in the past and attitude toward PRWs, but not the amount of daily Internet use for health-related information, were significant predictors of willingness to pay. The perceived usefulness of the Internet to gain health-related information and the amount of daily Internet use in general did not have any significant effect on both of the endogenous variables. The moderation analysis with the group comparisons for users and nonusers of PRWs revealed that the attitude toward PRWs had significantly more impact on the adoption and willingness to pay for mobile physician-rating apps in the nonuser group. Conclusions Important variables that contribute to the adoption of a mobile physician-rating app and the willingness to pay for it were identified. The results of this study are important for researchers because they can provide important insights about the variables that influence the acceptance of apps that allow for ratings of physicians. They are also useful for creators of mobile physician-rating apps because they can help tailor mobile physician-rating apps to the consumers’ characteristics and needs. PMID:24918859

Modelling latrine diffusion in Benin: towards a community typology of demand for improved sanitation in developing countries.

PubMed

Jenkins, Marion W; Cairncross, Sandy

2010-03-01

Latrine diffusion patterns across 502 villages in Benin, West Africa, were analysed to explore factors driving initial and increasing levels of household adoption in low-coverage rural areas of sub-Saharan Africa. Variables explaining adoption related to population density, size, infrastructure/services, non-agricultural occupations, road and urban proximity, and the nearby latrine adoption rate, capturing differences in the physical and social environment, lifestyles and latrine exposure involved in stimulating status/prestige and well-being reasons for latrine adoption. Contagion was most important in explaining adoption initiation. Cluster analysis revealed four distinct village typologies of demand for latrines which provide a framework for tailoring promotional interventions to better match the different sanitation demand characteristics of communities in scaling-up sanitation development and promotion programmes.

Pathways from education to depression.

PubMed

Lee, Jinkook

2011-06-01

We examine educational gradients in depression and identify underlying mechanisms of how education might affect depression. We use a nationally representative sample of community-residing adults aged 45 and older from the 2006 Korean Longitudinal Study of Aging, which collected information about depressive symptoms and education. Using tobit regression, we estimate the effect of education on depression and examine what can explain the education gradients by controlling for proxy variables of different pathways linking education to depression. We found cognitive ability, economic resources, social status, social network, and health behavior explain all of the education gradients. Education affects depression through different underlying mechanisms, and the single most important pathway is through developing cognitive ability. Through these pathways, educational attainment influences not only depression for an individual but also for one's spouse, particularly for women, and parents.

Joint Control: A Discussion of Recent Research

PubMed Central

Palmer, David C

2006-01-01

The discrimination of the onset of joint control is an important interpretive tool in explaining matching behavior and other complex phenomena, but the difficulty of getting experimental control of all relevant variables stands in the way of a definitive experiment. The studies in the present issue of The Analysis of Verbal Behavior illustrate how modest experiments can take their place in a web of interpretation to make a strong case that joint control is a necessary element of such phenomena. PMID:22477357

The cumulative effects of life event, personal and social resources on subjective well-being of elderly widowers.

PubMed

Balaswamy, S; Richardson, V E

2001-01-01

A multidimensional Life Stress Model was used to test the independent contributions of background characteristics, personal resources, life event, and environmental influences on 200 widowers' levels of well-being, measured by the Affect Balance Scale. Stepwise regression analyses revealed that environmental resources were unrelated to negative affect which is influenced more by the life event and personal resource variables. The environmental resource variables, particularly interactions with friends and neighbors, mostly influenced positive affect. The explanatory model for well-being included multiple variables and explained 33 percent of the variance. Although background characteristics had the greatest impact, absence of hospitalization, higher mastery, higher self-esteem, contacts with friends, and interaction with neighbors enhanced well-being. The results support previous speculations on the importance of positive exchanges for positive affect. African-American widowers showed higher levels of well-being than Caucasian widowers did. The results advance knowledge about differences among elderly men.

Long term variability of the annual hydrological regime and sensitivity to temperature phase shifts in Saxony/Germany

NASA Astrophysics Data System (ADS)

Renner, M.; Bernhofer, C.

2011-01-01

The timing of the seasons strongly effects ecosystems and human activities. Recently, there is increasing evidence of changes in the timing of the seasons, such as earlier spring seasons detected in phenological records, advanced seasonal timing of surface temperature, earlier snow melt or streamflow timing. For water resources management there is a need to quantitatively describe the variability in the timing of hydrological regimes and to understand how climatic changes control the seasonal water budget of river basins on the regional scale. In this study, changes of the annual cycle of hydrological variables are analysed for 27 river basins in Saxony/Germany. Thereby monthly series of basin runoff ratios, the ratio of runoff and basin precipitation are investigated for changes and variability of their annual periodicity over the period 1930-2009. Approximating the annual cycle by the means of harmonic functions gave acceptable results, while only two parameters, phase and amplitude, are required. It has been found that the annual phase of runoff ratio, representing the timing of the hydrological regime, is subject to considerable year-to-year variability, being concurrent with basins in similar hydro-climatic conditions. Two distinct basin classes have been identified, whereby basin elevation has been found to be the delimiting factor. An increasing importance of snow on the basin water balance with elevation is apparent and mainly governs the temporal variability of the annual timing of hydrological regimes. Further there is evidence of coincident changes in trend direction (change points in 1971 and 1988) in snow melt influenced basins. In these basins the timing of the runoff ratio is significantly correlated with the timing of temperature, and effects on runoff by temperature phase changes are even amplified. Interestingly, temperature effects may explain the low frequent variability of the second change point until today. However, the first change point can not be explained by temperature alone and other causes have to be considered.

Costs and Benefits of Orthographic Inconsistency in Reading: Evidence from a Cross-Linguistic Comparison

PubMed Central

Marinelli, Chiara Valeria; Romani, Cristina; Burani, Cristina; McGowan, Victoria A.; Zoccolotti, Pierluigi

2016-01-01

We compared reading acquisition in English and Italian children up to late primary school analyzing RTs and errors as a function of various psycholinguistic variables and changes due to experience. Our results show that reading becomes progressively more reliant on larger processing units with age, but that this is modulated by consistency of the language. In English, an inconsistent orthography, reliance on larger units occurs earlier on and it is demonstrated by faster RTs, a stronger effect of lexical variables and lack of length effect (by fifth grade). However, not all English children are able to master this mode of processing yielding larger inter-individual variability. In Italian, a consistent orthography, reliance on larger units occurs later and it is less pronounced. This is demonstrated by larger length effects which remain significant even in older children and by larger effects of a global factor (related to speed of orthographic decoding) explaining changes of performance across ages. Our results show the importance of considering not only overall performance, but inter-individual variability and variability between conditions when interpreting cross-linguistic differences. PMID:27355364

Costs and Benefits of Orthographic Inconsistency in Reading: Evidence from a Cross-Linguistic Comparison.

PubMed

Marinelli, Chiara Valeria; Romani, Cristina; Burani, Cristina; McGowan, Victoria A; Zoccolotti, Pierluigi

2016-01-01

We compared reading acquisition in English and Italian children up to late primary school analyzing RTs and errors as a function of various psycholinguistic variables and changes due to experience. Our results show that reading becomes progressively more reliant on larger processing units with age, but that this is modulated by consistency of the language. In English, an inconsistent orthography, reliance on larger units occurs earlier on and it is demonstrated by faster RTs, a stronger effect of lexical variables and lack of length effect (by fifth grade). However, not all English children are able to master this mode of processing yielding larger inter-individual variability. In Italian, a consistent orthography, reliance on larger units occurs later and it is less pronounced. This is demonstrated by larger length effects which remain significant even in older children and by larger effects of a global factor (related to speed of orthographic decoding) explaining changes of performance across ages. Our results show the importance of considering not only overall performance, but inter-individual variability and variability between conditions when interpreting cross-linguistic differences.

Predictors of Sun-Protective Practices among Iranian Female College Students: Application of Protection Motivation Theory.

PubMed

Dehbari, Samaneh Rooshanpour; Dehdari, Tahereh; Dehdari, Laleh; Mahmoudi, Maryam

2015-01-01

Given the importance of sun protection in the prevention of skin cancer, this study was designed to determine predictors of sun-protective practices among a sample of Iranian female college students based on protection motivation theory (PMT) variables. In this cross-sectional study, a total of 201 female college students in Iran University of Medical Sciences were selected. Demographic and PMT variables were assessed with a 67-item questionnaire. Multiple linear regression was used to identify demographic and PMT variables that were associated with sun-protective practices and intention. one percent of participants always wore a hat with a brim, 3.5% gloves and 15.9% sunglasses while outdoors. Only 10.9% regularly had their skin checked by a doctor. Perceived rewards, response efficacy, fear, self-efficacy and marital status were the five variables which could predict 39% variance of participants intention to perform sun-protective practices. Also, intention and response cost explained 31% of the variance of sun-protective practices. These predictive variables may be used to develop theory-based education interventions interventions to prevent skin cancer among college students.

Multivariate Analysis of Solar Spectral Irradiance Measurements

NASA Technical Reports Server (NTRS)

Pilewskie, P.; Rabbette, M.

2001-01-01

Principal component analysis is used to characterize approximately 7000 downwelling solar irradiance spectra retrieved at the Southern Great Plains site during an Atmospheric Radiation Measurement (ARM) shortwave intensive operating period. This analysis technique has proven to be very effective in reducing a large set of variables into a much smaller set of independent variables while retaining the information content. It is used to determine the minimum number of parameters necessary to characterize atmospheric spectral irradiance or the dimensionality of atmospheric variability. It was found that well over 99% of the spectral information was contained in the first six mutually orthogonal linear combinations of the observed variables (flux at various wavelengths). Rotation of the principal components was effective in separating various components by their independent physical influences. The majority of the variability in the downwelling solar irradiance (380-1000 nm) was explained by the following fundamental atmospheric parameters (in order of their importance): cloud scattering, water vapor absorption, molecular scattering, and ozone absorption. In contrast to what has been proposed as a resolution to a clear-sky absorption anomaly, no unexpected gaseous absorption signature was found in any of the significant components.

Effect size for the main cognitive function determinants in a large cross-sectional study.

PubMed

Mura, T; Amieva, H; Goldberg, M; Dartigues, J-F; Ankri, J; Zins, M; Berr, C

2016-11-01

The aim of our study was to examine the effect sizes of different cognitive function determinants in middle and early old age. Cognitive functions were assessed in 11 711 volunteers (45 to 75 years old), included in the French CONSTANCES cohort between January 2012 and May 2014, using the free and cued selective reminding test (FCSRT), verbal fluency tasks, digit-symbol substitution test (DSST) and trail making test (TMT), parts A and B. The effect sizes of socio-demographic (age, sex, education), lifestyle (alcohol, tobacco, physical activity), cardiovascular (diabetes, blood pressure) and psychological (depressive symptomatology) variables were computed as omega-squared coefficients (ω 2 ; part of the variation of a neuropsychological score that is independently explained by a given variable). These sets of variables explained from R 2 = 10% (semantic fluency) to R 2 = 26% (DSST) of the total variance. In all tests, socio-demographic variables accounted for the greatest part of the explained variance. Age explained from ω 2 = 0.5% (semantic fluency) to ω 2 = 7.5% (DSST) of the total score variance, gender from ω 2 = 5.2% (FCSRT) to a negligible part (semantic fluency or TMT) and education from ω 2 = 7.2% (DSST) to ω 2 = 1.4% (TMT-A). Behavioral, cardiovascular and psychological variables only slightly influenced the cognitive test results (all ω 2 < 0.8%, most ω 2 < 0.1%). Socio-demographic variables (age, gender and education) are the main variables associated with cognitive performance variations between 45 and 75 years of age in the general population. © 2016 EAN.

Effects of post-migration factors on PTSD outcomes among immigrant survivors of political violence.

PubMed

Chu, Tracy; Keller, Allen S; Rasmussen, Andrew

2013-10-01

This study examined the predictors of posttraumatic stress disorder (PTSD) in a clinical sample of 875 immigrant survivors of political violence resettled in the United States, with a specific aim of comparing the relative predictive power of pre-migration and post-migration experiences. Results from a hierarchical OLS regression indicated that pre-migration experiences such as rape/sexual assault were significantly associated with worse PTSD outcomes, as were post-migration factors such as measures of financial and legal insecurity. Post-migration variables, which included immigration status in the US, explained significantly more variance in PTSD outcomes than premigration variables alone. Discussion focused on the importance of looking at postmigration living conditions when treating trauma in this population.

Testing Components of a Self-Management Theory in Adolescents With Type 1 Diabetes Mellitus.

PubMed

Verchota, Gwen; Sawin, Kathleen J

The role of self-management in adolescents with type 1 diabetes mellitus is not well understood. The purpose of the research was to examine the relationship of key individual and family self-management theory, context, and process variables on proximal (self-management behaviors) and distal (hemoglobin A1c and diabetes-specific health-related quality of life) outcomes in adolescents with type 1 diabetes. A correlational, cross-sectional study was conducted to identify factors contributing to outcomes in adolescents with Type 1 diabetes and examine potential relationships between context, process, and outcome variables delineated in individual and family self-management theory. Participants were 103 adolescent-parent dyads (adolescents ages 12-17) with Type 1 diabetes from a Midwest, outpatient, diabetes clinic. The dyads completed a self-report survey including instruments intended to measure context, process, and outcome variables from individual and family self-management theory. Using hierarchical multiple regression, context (depressive symptoms) and process (communication) variables explained 37% of the variance in self-management behaviors. Regimen complexity-the only significant predictor-explained 11% of the variance in hemoglobin A1c. Neither process variables nor self-management behaviors were significant. For the diabetes-specific health-related quality of life outcome, context (regimen complexity and depressive symptoms) explained 26% of the variance at step 1; an additional 9% of the variance was explained when process (self-efficacy and communication) variables were added at step 2; and 52% of the variance was explained when self-management behaviors were added at Step 3. In the final model, three variables were significant predictors: depressive symptoms, self-efficacy, and self-management behaviors. The individual and family self-management theory can serve as a cogent theory for understanding key concepts, processes, and outcomes essential to self-management in adolescents and families dealing with Type 1 diabetes mellitus.

Flow and residence times of dynamic river bank storage and sinuosity-driven hyporheic exchange

USGS Publications Warehouse

Gomez-Velez, J.D.; Wilson, J.L.; Cardenas, M.B.; Harvey, Judson

2017-01-01

Hydrologic exchange fluxes (HEFs) vary significantly along river corridors due to spatiotemporal changes in discharge and geomorphology. This variability results in the emergence of biogeochemical hot-spots and hot-moments that ultimately control solute and energy transport and ecosystem services from the local to the watershed scales. In this work, we use a reduced-order model to gain mechanistic understanding of river bank storage and sinuosity-driven hyporheic exchange induced by transient river discharge. This is the first time that a systematic analysis of both processes is presented and serves as an initial step to propose parsimonious, physics-based models for better predictions of water quality at the large watershed scale. The effects of channel sinuosity, alluvial valley slope, hydraulic conductivity, and river stage forcing intensity and duration are encapsulated in dimensionless variables that can be easily estimated or constrained. We find that the importance of perturbations in the hyporheic zone's flux, residence times, and geometry is mainly explained by two-dimensionless variables representing the ratio of the hydraulic time constant of the aquifer and the duration of the event (Γd) and the importance of the ambient groundwater flow ( ). Our model additionally shows that even systems with small sensitivity, resulting in small changes in the hyporheic zone extent, are characterized by highly variable exchange fluxes and residence times. These findings highlight the importance of including dynamic changes in hyporheic zones for typical HEF models such as the transient storage model.

Variability and regulation of denitrification in an Upper Mississippi River backwater

USGS Publications Warehouse

Strauss, E.A.; Richardson, W.B.; Cavanaugh, J.C.; Bartsch, L.A.; Kreiling, Rebecca M.; Standorf, A.J.

2006-01-01

Sediments in the backwaters of the Upper Mississippi River (UMR) are highly organic and provide an optimal environment for N removal. We monitored an 8.6-ha UMR backwater site near La Crosse, Wisconsin, for nearly 3 y to assess temporal variability, seasonal trends, and the factors regulating denitrification. We measured rates of unamended denitrification (DEN) and denitrification enzyme activity (DEA) rates at ambient temperature and DEA at 30 degrees C (DEA30). Seasonal mean (+/- 1 SE) DEN rates ranged from 0.041 +/- 0.015 to 0.47 +/- 0.23 mu g N cm(-2) h(-1)and were highest in winter and lowest in autumn. Seasonal rates of DEA exhibited a different pattern with the highest rates in summer (25.6 +/- 3.4 mu g N cm(-2) h(-1)) and the lowest rates in winter (10.6 +/- 2.1 mu g N cm(-2) h(-1)). The overall mean DEA30 rate was 31.0 +/- 1.9 mu g N cm(-2) h(-1) but showed no significant seasonal pattern. Short-term (weekly) and seasonal variability exhibited by rates of DEN and DEA were best explained by water-column NO3- concentration and temperature, respectively. No environmental variables explained a significant amount of variability in DEA30. Our results suggest that nutrient (i.e., NO3-) availability and temperature are both regulators of denitrification, with NO3- concentration being the most important limiting factor in this system. The high DEN rates during winter were in response to elevated NO3- concentrations resulting from a chain reaction beginning with algal blooms creating oxic conditions that stimulated nitrification. Increasing hydrological connectivity in large rivers as a river management tool to reduce N flux to downstream areas may be beneficial.

Flows, droughts, and aliens: factors affecting the fish assemblage in a Sierra Nevada, California, stream.

PubMed

Kiernan, Joseph D; Moyle, Peter B

2012-06-01

The fishes of Martis Creek, in the Sierra Nevada of California (USA), were sampled at four sites annually over 30 years, 1979-2008. This long-term data set was used to examine (1) the persistence and stability of the Martis Creek fish assemblage in the face of environmental stochasticity; (2) whether native and alien fishes responded differently to a natural hydrologic regime (e.g., timing and magnitude of high and low flows); and (3) the importance of various hydrologic and physical habitat variables in explaining the abundances of native and alien fish species through time. Our results showed that fish assemblages were persistent at all sample sites, but individual species exhibited marked interannual variability in density, biomass, and relative abundance. The density and biomass of native fishes generally declined over the period of study, whereas most alien species showed no significant long-term trends. Only alien rainbow trout increased in both density and biomass at all sites over time. Redundancy analysis identified three hydrologic variables (annual 7-day minimum discharge, maximum winter discharge, and number of distinct winter floods) and two habitat variables (percentage of pool habitat and percentage of gravel substrate) that each explained a significant portion of the annual variation in fish assemblage structure. For alien taxa, their proportional contribution to the total fish assemblage was inversely related to mean annual streamflow, one-day maximum discharge in both winter and spring, and the frequency of springtime floods. Results of this study highlight the need for continuous annual monitoring of streams with highly variable flow regimes to evaluate shifts in fish community structure. Apparent successes or failures in stream management may appear differently depending on the time series of available data.

Can temperature explain the latitudinal gradient of ulcerative colitis? Cohort of Norway

PubMed Central

2013-01-01

Background Incidence and prevalence of ulcerative colitis follow a north–south (latitudinal) gradient and increases northwards at the northern hemisphere or southwards at the southern hemisphere. The disease has increased during the last decades. The temporal trend has been explained by the hygiene hypothesis, but few parallel explanations exist for the spatial variability. Many factors are linked to latitude such as climate. Our purpose was to investigate the association between variables governing the climate and prospectively identified patients. Methods In this study, we used a subset of the population-based Cohort of Norway (n = 80412) where 370 prevalent cases of ulcerative colitis were identified through self-reported medication. The meteorological and climatic variables temperature, precipitation, and altitude were recorded from weather stations of the Norwegian Meteorological Institute. Summer temperature was used to capture environmental temperature. Results Summer temperature was significantly related to the prevalence of ulcerative colitis. For each one-degree increase in temperature the odds for ulcerative colitis decreased with about 9% (95% CI: 3%-15%). None of the other climatic factors were significantly associated to the risk of ulcerative colitis. Contextual variables did not change the association to the prevalence of ulcerative colitis. Conclusions The present results show that the prevalence of ulcerative colitis is associated to summer temperature. Our speculation is that summer temperature works as an instrumental variable for the effect of microbial species richness on the development of ulcerative colitis. Environmental temperature is one of the main forces governing microbial species richness and the microbial composition of the commensal gut flora is known to be an important part in the process leading to ulcerative colitis. PMID:23724802

Speech sequence skill learning in adults who stutter.

PubMed

Bauerly, Kim R; De Nil, Luc F

2011-12-01

The present study compared the ability of 12 people who stutter (PWS) and 12 people who do not stutter (PNS) to consolidate a novel sequential speech task. Participants practiced 100 repetitions of a single, monosyllabic, nonsense word sequence during an initial practice session and returned 24-h later to perform an additional 50 repetitions. Results showed significantly slower sequence durations in the PWS compared to PNS following extensive practice and consolidation. However, the hypothesis that poor performance gains in PWS compared to PNS during practice would be maintained following a 24-h consolidation period was not supported. Further descriptive analysis revealed large within group differences in PWS which to some extent were attributed to a subgroup of PWS who failed to show any improvements in performance following practice or consolidation. The results and the possible presence of subgroups of PWS are discussed with regard to their limitations in motor learning abilities. The reader will be able to (1) explain the difference between practice and learning, (2) define consolidation and explain the importance of measuring performance following a consolidation period, (3) understand past research on PWS' performance during both speech and nonspeech motor tasks, and (4) explain why individual differences in practice effects and learning may have important implications for client variability in treatment outcome. Copyright © 2011 Elsevier Inc. All rights reserved.

A genome scan revealed significant associations of growth traits with a major QTL and GHR2 in tilapia

PubMed Central

Liu, Feng; Sun, Fei; Xia, Jun Hong; Li, Jian; Fu, Gui Hong; Lin, Grace; Tu, Rong Jian; Wan, Zi Yi; Quek, Delia; Yue, Gen Hua

2014-01-01

Growth is an important trait in animal breeding. However, the genetic effects underpinning fish growth variability are still poorly understood. QTL mapping and analysis of candidate genes are effective methods to address this issue. We conducted a genome-wide QTL analysis for growth in tilapia. A total of 10, 7 and 8 significant QTLs were identified for body weight, total length and standard length at 140 dph, respectively. The majority of these QTLs were sex-specific. One major QTL for growth traits was identified in the sex-determining locus in LG1, explaining 71.7%, 67.2% and 64.9% of the phenotypic variation (PV) of body weight, total length and standard length, respectively. In addition, a candidate gene GHR2 in a QTL was significantly associated with body weight, explaining 13.1% of PV. Real-time qPCR revealed that different genotypes at the GHR2 locus influenced the IGF-1 expression level. The markers located in the major QTL for growth traits could be used in marker-assisted selection of tilapia. The associations between GHR2 variants and growth traits suggest that the GHR2 gene should be an important gene that explains the difference in growth among tilapia species. PMID:25435025

Explaining and forecasting interannual variability in the flow of the Nile River

NASA Astrophysics Data System (ADS)

Siam, M. S.; Eltahir, E. A. B.

2014-05-01

The natural interannual variability in the flow of Nile River had a significant impact on the ancient civilizations and cultures that flourished on the banks of the river. This is evident from stories in the Bible and Koran, and from the numerous Nilometers discovered near ancient temples. Here, we analyze extensive data sets collected during the 20th century and define four modes of natural variability in the flow of Nile River, identifying a new significant potential for improving predictability of floods and droughts. Previous studies have identified a significant teleconnection between the Nile flow and the Eastern Pacific Ocean. El Niño-Southern Oscillation (ENSO) explains about 25% of the interannual variability in the Nile flow. Here, we identify, for the first time, a region in the southern Indian Ocean with similarly strong teleconnection to the Nile flow. Sea Surface Temperature (SST) in the region (50-80° E and 25-35° S) explains 28% of the interannual variability in the Nile flow. During those years with anomalous SST conditions in both Oceans, we estimate that indices of the SSTs in the Pacific and Indian Oceans can collectively explain up to 84% of the interannual variability in the flow of Nile. Building on these findings, we use classical Bayesian theorem to develop a new hybrid forecasting algorithm that predicts the Nile flow based on global models predictions of indices of the SST in the Eastern Pacific and Southern Indian Oceans.

Organic carbon source and salinity shape sediment bacterial composition in two China marginal seas and their major tributaries.

PubMed

Wang, Kai; Zou, Li; Lu, Xinxin; Mou, Xiaozhen

2018-08-15

Marginal sea sediments receive organic substrates of different origins, but whether and to what extent sediment microbial communities are reflective of the different sources of organic substrates remain unclear. To address these questions, sediment samples were collected in two connected China marginal seas, i.e., Bohai Sea and Yellow Sea, and their two major tributaries (Yellow River and Liao River). Sediment bacterial community composition (BCC) was examined using 16S rRNA gene pyrosequencing. In addition, physicochemical variables that describe environmental conditions and sediment features were measured. Our results revealed that BCCs changed with salinity and organic carbon (OC) content. Members of Gaiellaceae and Comamonadaceae showed a rapid decrease as salinity and phytoplankton-derived OC increased, while Piscirickettsiaceae and Desulfobulbaceae exhibited an opposite distribution pattern. Differences of riverine vs. marginal sea sediment BCCs could be mostly explained by salinity. However, within the marginal seas, sediment BCC variations were mainly explained by OC-related variables, including terrestrial-derived fatty acids (Terr_FA), phytoplankton-derived polyunsaturated fatty acids (Phyto_PUFA), stable carbon isotopes (δ 13 C), and carbon to nitrogen ratio (C/N). In addition to environmental variables, network analysis suggested that interactions among individual bacterial taxa might be important in shaping sediment BCCs in the studied areas. Copyright © 2018 Elsevier B.V. All rights reserved.

Wind-induced interannual variability of sea level slope, along-shelf flow, and surface salinity on the Northwest Atlantic shelf

NASA Astrophysics Data System (ADS)

Li, Yun; Ji, Rubao; Fratantoni, Paula S.; Chen, Changsheng; Hare, Jonathan A.; Davis, Cabell S.; Beardsley, Robert C.

2014-04-01

In this study, we examine the importance of regional wind forcing in modulating advective processes and hydrographic properties along the Northwest Atlantic shelf, with a focus on the Nova Scotian Shelf (NSS)-Gulf of Maine (GoM) region. Long-term observational data of alongshore wind stress, sea level slope, and along-shelf flow are analyzed to quantify the relationship between wind forcing and hydrodynamic responses on interannual time scales. Additionally, a simplified momentum balance model is used to examine the underlying mechanisms. Our results show significant correlation among the observed interannual variability of sea level slope, along-shelf flow, and alongshore wind stress in the NSS-GoM region. A mechanism is suggested to elucidate the role of wind in modulating the sea level slope and along-shelf flow: stronger southwesterly (northeastward) winds tend to weaken the prevailing southwestward flow over the shelf, building sea level in the upstream Newfoundland Shelf region, whereas weaker southwesterly winds allow stronger southwestward flow to develop, raising sea level in the GoM region. The wind-induced flow variability can influence the transport of low-salinity water from the Gulf of St. Lawrence to the GoM, explaining interannual variations in surface salinity distributions within the region. Hence, our results offer a viable mechanism, besides the freshening of remote upstream sources, to explain interannual patterns of freshening in the GoM.

Research article: Watershed management councils and scientific models: Using diffusion literature to explain adoption

USGS Publications Warehouse

King, M.D.; Burkardt, N.; Clark, B.T.

2006-01-01

Recent literature on the diffusion of innovations concentrates either specifically on public adoption of policy, where social or environmental conditions are the dependent variables for adoption, or on private adoption of an innovation, where emphasis is placed on the characteristics of the innovation itself. This article uses both the policy diffusion literature and the diffusion of innovation literature to assess watershed management councils' decisions to adopt, or not adopt, scientific models. Watershed management councils are a relevant case study because they possess both public and private attributes. We report on a survey of councils in the United States that was conducted to determine the criteria used when selecting scientific models for studying watershed conditions. We found that specific variables from each body of literature play a role in explaining the choice to adopt scientific models by these quasi-public organizations. The diffusion of innovation literature contributes to an understanding of how organizations select models by confirming the importance of a model's ability to provide better data. Variables from the policy diffusion literature showed that watershed management councils that employ consultants are more likely to use scientific models. We found a gap between those who create scientific models and those who use these models. We recommend shrinking this gap through more communication between these actors and advancing the need for developers to provide more technical assistance.

Sources and transport of phosphorus to rivers in California and adjacent states, U.S., as determined by SPARROW modeling

USGS Publications Warehouse

Domagalski, Joseph L.; Saleh, Dina

2015-01-01

The SPARROW (SPAtially Referenced Regression on Watershed attributes) model was used to simulate annual phosphorus loads and concentrations in unmonitored stream reaches in California, U.S., and portions of Nevada and Oregon. The model was calibrated using de-trended streamflow and phosphorus concentration data at 80 locations. The model explained 91% of the variability in loads and 51% of the variability in yields for a base year of 2002. Point sources, geological background, and cultivated land were significant sources. Variables used to explain delivery of phosphorus from land to water were precipitation and soil clay content. Aquatic loss of phosphorus was significant in streams of all sizes, with the greatest decay predicted in small- and intermediate-sized streams. Geological sources, including volcanic rocks and shales, were the principal control on concentrations and loads in many regions. Some localized formations such as the Monterey shale of southern California are important sources of phosphorus and may contribute to elevated stream concentrations. Many of the larger point source facilities were located in downstream areas, near the ocean, and do not affect inland streams except for a few locations. Large areas of cultivated land result in phosphorus load increases, but do not necessarily increase the loads above those of geological background in some cases because of local hydrology, which limits the potential of phosphorus transport from land to streams.

Sources of variability in childhood obesity indicators and related behaviors.

PubMed

Katzmarzyk, P T; Broyles, S T; Chaput, J-P; Fogelholm, M; Hu, G; Lambert, E V; Maher, C; Maia, J; Olds, T; Onywera, V; Sarmiento, O L; Standage, M; Tremblay, M S; Tudor-Locke, C

2018-01-01

The purpose of this study was to describe sources of variability in obesity-related variables in 6022 children aged 9-11 years from 12 countries. The study design involved recruitment of students, nested within schools, which were nested within study sites. Height, weight and waist circumference (WC) were measured and body mass index (BMI) was calculated; sleep duration and total and in-school moderate-to-vigorous physical activity (MVPA) and sedentary time were measured by accelerometry; and diet scores were obtained by questionnaire. Variance in most variables was largely explained at the student level: BMI (91.9%), WC (93.5%), sleep (75.3%), MVPA (72.5%), sedentary time (76.9%), healthy diet score (88.3%), unhealthy diet score (66.2%), with the exception of in-school MVPA (53.8%) and in-school sedentary time (25.1%). Variance explained at the school level ranged from 3.3% for BMI to 29.8% for in-school MVPA, and variance explained at the site level ranged from 3.2% for WC to 54.2% for in-school sedentary time. In general, more variance was explained at the school and site levels for behaviors than for anthropometric traits. Given the variance in obesity-related behaviors in primary school children explained at school and site levels, interventions that target policy and environmental changes may enhance obesity intervention efforts.

Postglacial migration supplements climate in determining plant species ranges in Europe

PubMed Central

Normand, Signe; Ricklefs, Robert E.; Skov, Flemming; Bladt, Jesper; Tackenberg, Oliver; Svenning, Jens-Christian

2011-01-01

The influence of dispersal limitation on species ranges remains controversial. Considering the dramatic impacts of the last glaciation in Europe, species might not have tracked climate changes through time and, as a consequence, their present-day ranges might be in disequilibrium with current climate. For 1016 European plant species, we assessed the relative importance of current climate and limited postglacial migration in determining species ranges using regression modelling and explanatory variables representing climate, and a novel species-specific hind-casting-based measure of accessibility to postglacial colonization. Climate was important for all species, while postglacial colonization also constrained the ranges of more than 50 per cent of the species. On average, climate explained five times more variation in species ranges than accessibility, but accessibility was the strongest determinant for one-sixth of the species. Accessibility was particularly important for species with limited long-distance dispersal ability, with southern glacial ranges, seed plants compared with ferns, and small-range species in southern Europe. In addition, accessibility explained one-third of the variation in species' disequilibrium with climate as measured by the realized/potential range size ratio computed with niche modelling. In conclusion, we show that although climate is the dominant broad-scale determinant of European plant species ranges, constrained dispersal plays an important supplementary role. PMID:21543356

Aircrew coordination and decisionmaking: Peer ratings of video tapes made during a full mission simulation

NASA Technical Reports Server (NTRS)

Murphy, M. R.; Awe, C. A.

1986-01-01

Six professionally active, retired captains rated the coordination and decisionmaking performances of sixteen aircrews while viewing videotapes of a simulated commercial air transport operation. The scenario featured a required diversion and a probable minimum fuel situation. Seven point Likert-type scales were used in rating variables on the basis of a model of crew coordination and decisionmaking. The variables were based on concepts of, for example, decision difficulty, efficiency, and outcome quality; and leader-subordin ate concepts such as person and task-oriented leader behavior, and competency motivation of subordinate crewmembers. Five-front-end variables of the model were in turn dependent variables for a hierarchical regression procedure. The variance in safety performance was explained 46%, by decision efficiency, command reversal, and decision quality. The variance of decision quality, an alternative substantive dependent variable to safety performance, was explained 60% by decision efficiency and the captain's quality of within-crew communications. The variance of decision efficiency, crew coordination, and command reversal were in turn explained 78%, 80%, and 60% by small numbers of preceding independent variables. A principle component, varimax factor analysis supported the model structure suggested by regression analyses.

Identification of major and minor QTL for ecologically important morphological traits in three-spined sticklebacks (Gasterosteus aculeatus).

PubMed

Liu, Jun; Shikano, Takahito; Leinonen, Tuomas; Cano, José Manuel; Li, Meng-Hua; Merilä, Juha

2014-04-16

Quantitative trait locus (QTL) mapping studies of Pacific three-spined sticklebacks (Gasterosteus aculeatus) have uncovered several genomic regions controlling variability in different morphological traits, but QTL studies of Atlantic sticklebacks are lacking. We mapped QTL for 40 morphological traits, including body size, body shape, and body armor, in a F2 full-sib cross between northern European marine and freshwater three-spined sticklebacks. A total of 52 significant QTL were identified at the 5% genome-wide level. One major QTL explaining 74.4% of the total variance in lateral plate number was detected on LG4, whereas several major QTL for centroid size (a proxy for body size), and the lengths of two dorsal spines, pelvic spine, and pelvic girdle were mapped on LG21 with the explained variance ranging from 27.9% to 57.6%. Major QTL for landmark coordinates defining body shape variation also were identified on LG21, with each explaining ≥15% of variance in body shape. Multiple QTL for different traits mapped on LG21 overlapped each other, implying pleiotropy and/or tight linkage. Thus, apart from providing confirmatory data to support conclusions born out of earlier QTL studies of Pacific sticklebacks, this study also describes several novel QTL of both major and smaller effect for ecologically important traits. The finding that many major QTL mapped on LG21 suggests that this linkage group might be a hotspot for genetic determinants of ecologically important morphological traits in three-spined sticklebacks.

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis.

PubMed

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-04

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c  = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis

NASA Astrophysics Data System (ADS)

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-01

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

Setting the Revisit Interval in Primary Care

PubMed Central

Schwartz, Lisa M; Woloshin, Steven; Wasson, John H; Renfrew, Roger A; Welch, H Gilbert

1999-01-01

OBJECTIVE Although longitudinal care constitutes the bulk of primary care, physicians receive little guidance on the fundamental question of how to time follow-up visits. We sought to identify important predictors of the revisit interval and to describe the variability in how physicians set these intervals when caring for patients with common medical conditions. DESIGN Cross-sectional survey of physicians performed at the end of office visits for consecutive patients with hypertension, angina, diabetes, or musculoskeletal pain. PARTICIPANTS/SETTING One hundred sixty-four patients under the care of 11 primary care physicians in the Dartmouth Primary Care Cooperative Research Network. MEASUREMENTS The main outcome measures were the variability in mean revisit intervals across physicians and the proportion of explained variance by potential determinants of revisit intervals. We assessed the relation between the revisit interval (dependent variable) and three groups of independent variables, patient characteristics (e.g., age, physician perception of patient health), identification of individual physician, and physician characterization of the visit (e.g., routine visit, visit requiring a change in management, or visit occurring on a “hectic” day), using multiple regression that accounted for the natural grouping of patients within physician. MAIN RESULTS Revisit intervals ranged from 1 week to over 1 year. The most common intervals were 12 and 16 weeks. Physicians’ perception of fair-poor health status and visits involving a change in management were most strongly related to shorter revisit intervals. In multivariate analyses, patient characteristics explained about 18% of the variance in revisit intervals, and adding identification of the individual provider doubled the explained variance to about 40%. Physician characterization of the visit increased explained variance to 57%. The average revisit interval adjusted for patient characteristics for each of the 11 physicians varied from 4 to 20 weeks. Although all physicians lengthened revisit intervals for routine visits and shortened them when changing management, the relative ranking of mean revisit intervals for each physician changed little for different visit characterizations—some physicians were consistently long and others were consistently short. CONCLUSION Physicians vary widely in their recommendations for office revisits. Patient factors accounted for only a small part of this variation. Although physicians responded to visits in predictable ways, each physician appeared to have a unique set point for the length of the revisits interval. PMID:10203635

Variability of the western Galician upwelling system (NW Spain) during an intensively sampled annual cycle. An EOF analysis approach

NASA Astrophysics Data System (ADS)

Herrera, J. L.; Rosón, G.; Varela, R. A.; Piedracoba, S.

2008-07-01

The key features of the western Galician shelf hydrography and dynamics are analyzed on a solid statistical and experimental basis. The results allowed us to gather together information dispersed in previous oceanographic works of the region. Empirical orthogonal functions analysis and a canonical correlation analysis were applied to a high-resolution dataset collected from 47 surveys done on a weekly frequency from May 2001 to May 2002. The main results of these analyses are summarized bellow. Salinity, temperature and the meridional component of the residual current are correlated with the relevant local forcings (the meridional coastal wind component and the continental run-off) and with a remote forcing (the meridional temperature gradient at latitude 37°N). About 80% of the salinity and temperature total variability over the shelf, and 37% of the residual meridional current total variability are explained by two EOFs for each variable. Up to 22% of the temperature total variability and 14% of the residual meridional current total variability is devoted to the set up of cross-shore gradients of the thermohaline properties caused by the wind-induced Ekman transport. Up to 11% and 10%, respectively, is related to the variability of the meridional temperature gradient at the Western Iberian Winter Front. About 30% of the temperature total variability can be explained by the development and erosion of the seasonal thermocline and by the seasonal variability of the thermohaline properties of the central waters. This thermocline presented unexpected low salinity values due to the trapping during spring and summer of the high continental inputs from the River Miño recorded in 2001. The low salinity plumes can be traced on the Galician shelf during almost all the annual cycle; they tend to be extended throughout the entire water column under downwelling conditions and concentrate in the surface layer when upwelling favourable winds blow. Our evidences point to the meridional temperature gradient acting as an important controlling factor of the central waters thermohaline properties and in the development and decay of the Iberian Poleward Current.

[Prediction of the nutritional status by anthropometrical variables and food safety at homes of pregnant women from Caracas, Venezuela].

PubMed

Pérez Guillén, A; Bernal Rivas, J

2006-01-01

The objective of this research is to analyze the nutritional status and household food security of a sample of healthy pregnant women who attend to external medicine service at Concepcion Palacios Maternity located in Caracas, Venezuela, and identify variables, which could predict the nutritional status of the evaluated group. This cross sectional, descriptive, comparative study evaluates a sample of 89 pregnant women, between 14 and 44 years of age. Economical, social, demographic and alimentary consumption variables and nutritional conditions were studied. On the way, anthropometrics like weight, height, and middle-arm circumference and Household food security scale were obtained. In order to perform the descriptive statistic, bivariate, and multiple linear regression analysis required during the investigation, the software SPSS, version 12, was used. The predictive variables considered for the evaluation of the actual nutritional status in pregnant women were: right middle-arm circumference, household food security level and the supplementation with vitamins and/or minerals. These variables explain 78.2% of the actual nutritional status variation in this sample. Therefore, this investigation highlights the importance of the research on simple variables, as a good prediction of the actual nutritional status in pregnant women, with acceptable precision values and without requiring high-trained personnel to perform it. Under these findings, is very important the study of more predictive variables to evaluate the nutritional and alimentary conditions, with practical and easy mechanisms that can be applied by non-technical personnel. It is recommended to go deep into the study of methods, which evaluate the nutrition in an easy and practical way, applied by non-technical personnel, besides continuing the validation process of the variable combinations determined as predictive of the nutritional status.

Referring patients to specialists: A structured vignette survey of Australian and British GPs

PubMed Central

Jiwa, Moyez; Gordon, Michael; Arnet, Hayley; Ee, Hooi; Bulsara, Max; Colwell, Brigitte

2008-01-01

Background In Australia and in the United Kingdom (UK) access to specialists is sanctioned by General Practitioners (GPs). It is important to understand how practitioners determine which patients warrant referral. Methods A self-administered structured vignette postal survey of General Practitioners in Western Australia and the United Kingdom. Sixty-four vignettes describing patients with colorectal symptoms were constructed encompassing six clinical details. Nine vignettes, chosen at random, were presented to each individual. Respondents were asked if they would refer the patient to a specialist and how urgently. Logistic regression and parametric tests were used to analyse the data Results We received 260 completed questionnaires. 58% of 'cancer vignettes' were selected for 'urgent' referral. 1632/2367 or 69% of all vignettes were selected for referral. After adjusting for clustering the model suggests that 38.4% of the variability is explained by all the clinical variables as well as the age and experience of the respondents. 1012 or 42.8 % of vignettes were referred 'urgently'. After adjusting for clustering the data suggests that 31.3 % of the variability is explained by the model. The age of the respondents, the location of the practice and all the clinical variables were significant in the decision to refer urgently. Conclusion GPs' referral decisions for patients with lower bowel symptoms are similar in the two countries. We question the wisdom of streaming referrals from primary care without a strong evidence base and an effective intervention for implementing guidelines. We conclude that implementation must take into account the profile of patients but also the characteristics of GPs and referral policies. PMID:18194578

Relationship between extrinsic factors and the acromio-humeral distance.

PubMed

Mackenzie, Tanya Anne; Herrington, Lee; Funk, Lenard; Horsley, Ian; Cools, Ann

2016-06-01

Maintenance of the subacromial space is important in impingement syndromes. Research exploring the correlation between biomechanical factors and the subacromial space would be beneficial. To establish if relationship exists between the independent variables of scapular rotation, shoulder internal rotation, shoulder external rotation, total arc of shoulder rotation, pectoralis minor length, thoracic curve, and shoulder activity level with the dependant variables: AHD in neutral, AHD in 60° arm abduction, and percentage reduction in AHD. Controlled laboratory study. Data from 72 male control shoulders (24.28years STD 6.81 years) and 186 elite sportsmen's shoulders (25.19 STD 5.17 years) were included in the analysis. The independent variables were quantified and real time ultrasound was used to measure the dependant variable acromio-humeral distance. Shoulder internal rotation and pectoralis minor length, explained 8% and 6% respectively of variance in acromio-humeral distance in neutral. Pectoralis minor length accounted for 4% of variance in 60° arm abduction. Total arc of rotation, shoulder external rotation range, and shoulder activity levels explained 9%, 15%, and 16%-29% of variance respectively in percentage reduction in acromio-humeral distance during arm abduction to 60°. Pectorals minor length, shoulder rotation ranges, total arc of shoulder rotation, and shoulder activity levels were found to have weak to moderate relationships with acromio-humeral distance. Existence and strength of relationship was population specific and dependent on arm position. Relationships only accounted for small variances in AHD indicating that in addition to these factors there are other factors involved in determining AHD. Copyright © 2016 Elsevier Ltd. All rights reserved.

Human impact on sediment fluxes within the Blue Nile and Atbara River basins

NASA Astrophysics Data System (ADS)

Balthazar, Vincent; Vanacker, Veerle; Girma, Atkilt; Poesen, Jean; Golla, Semunesh

2013-01-01

A regional assessment of the spatial variability in sediment yields allows filling the gap between detailed, process-based understanding of erosion at field scale and empirical sediment flux models at global scale. In this paper, we focus on the intrabasin variability in sediment yield within the Blue Nile and Atbara basins as biophysical and anthropogenic factors are presumably acting together to accelerate soil erosion. The Blue Nile and Atbara River systems are characterized by an important spatial variability in sediment fluxes, with area-specific sediment yield (SSY) values ranging between 4 and 4935 t/km2/y. Statistical analyses show that 41% of the observed variation in SSY can be explained by remote sensing proxy data of surface vegetation cover, rainfall intensity, mean annual temperature, and human impact. The comparison of a locally adapted regression model with global predictive sediment flux models indicates that global flux models such as the ART and BQART models are less suited to capture the spatial variability in area-specific sediment yields (SSY), but they are very efficient to predict absolute sediment yields (SY). We developed a modified version of the BQART model that estimates the human influence on sediment yield based on a high resolution composite measure of local human impact (human footprint index) instead of countrywide estimates of GNP/capita. Our modified version of the BQART is able to explain 80% of the observed variation in SY for the Blue Nile and Atbara basins and thereby performs only slightly less than locally adapted regression models.

Understanding the weather signal in national crop-yield variability

NASA Astrophysics Data System (ADS)

Frieler, Katja; Schauberger, Bernhard; Arneth, Almut; Balkovič, Juraj; Chryssanthacopoulos, James; Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Khabarov, Nikolay; Müller, Christoph; Olin, Stefan; Pugh, Thomas A. M.; Schaphoff, Sibyll; Schewe, Jacob; Schmid, Erwin; Warszawski, Lila; Levermann, Anders

2017-06-01

Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced crop-yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here, we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state-of-the-art, process-based crop model simulations. We find that observed weather variations can explain more than 50% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50% in seven countries, including the United States. The explained variance exceeds 50% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop-yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process-based crop models not only account for weather influences on crop yields, but also provide options to represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.

Open communication with terminally ill cancer patients about illness and death: a comparison between spouses of Ashkenazi and Sephardi ethnic origins.

PubMed

Bachner, Yaacov G; Yosef-Sela, Nili; Carmel, Sara

2014-01-01

Studies document that caregivers face severe difficulties in communicating with their loved ones about both illness and death. To date, a paucity of studies has examined caregiver-patient communication at the end of life within the context of ethnic origin. This study compares the level of open communication between caregivers from 2 ethnic groups and examines the contribution of different caregiver characteristics and situational variables to the explanation of open communication. A total of 77 spouse caregivers of terminally ill cancer patients (comprising 41 Jews of Sephardi origin and 36 Jews of Ashkenazi origin) participated in the study. The questionnaire included measures of caregiver communication, caregiver characteristics (ie, age, gender, education level, optimism, self-efficacy), and situational variables (ie, duration and intensity of care). Spouses of Ashkenazi origin communicated more with their loved ones about illness and death compared with their Sephardi counterparts. Ethnic origin accounted for 16.6% of the explained variance, caregiver characteristics added 20.3%, and situation variables lent a modest contribution of 3.5%. Four variables emerged as significant predictors of caregivers' level of open communication: self-efficacy (β = .33, P < .05), gender (β = .32, P < .01), ethnic origin (β = .25, P <.05), and duration of care (β = .20, P < .05). These findings demonstrate the importance of ethnic origin to caregivers' open communication with terminal cancer patients about illness and death. Moreover, communication level with patients is mostly explained by the caregiver characteristics. Caregiver characteristics should be considered by nurses when developing intervention programs for increasing caregivers' level of open communication with dying patients.

Differential Impacts of Climate Change on Crops and Agricultural Regions in India

NASA Astrophysics Data System (ADS)

Sharma, A. N.

2015-12-01

As India's farmers and policymakers consider potential adaptation strategies to climate change, some questions loom large: - Which climate variables best explain the variability of crop yields? - How does the vulnerability of crop yields to climate vary regionally? - How are these risks likely to change in the future? While process-based crop modelling has started to answer many of these questions, we believe statistical approaches can complement these in improving our understanding of climate vulnerabilities and appropriate responses. We use yield data collected over three decades for more than ten food crops grown in India along with a variety of statistical approaches to answer the above questions. The ability of climate variables to explain yield variation varies greatly by crop and season, which is expected. Equally important, the ability of models to predict crop yields as well as their coefficients varies greatly by district even for districts which are relatively close to each other and similar in their agricultural practices. We believe these results encourage caution and nuance when making projections about climate impacts on crop yields in the future. Most studies about climate impacts on crop yields focus on a handful of major food crops. By extending our analysis to all the crops with long-term district level data in India as well as two growing seasons we gain a more comprehensive picture. Our results indicate that there is a great deal of variability even at relatively small scales, and that this must be taken into account if projections are to be made useful to policymakers.

Do nurses wish to continue working for the UK National Health Service? A comparative study of three generations of nurses.

PubMed

Robson, Andrew; Robson, Fiona

2015-01-01

To identify the combination of variables that explain nurses' continuation intention in the UK National Health Service. This alternative arena has permitted the replication of a private sector Australian study. This study provides understanding about the issues that affect nurse retention in a sector where employee attrition is a key challenge, further exacerbated by an ageing workforce. A quantitative study based on a self-completion survey questionnaire completed in 2010. Nurses employed in two UK National Health Service Foundation Trusts were surveyed and assessed using seven work-related constructs and various demographics including age generation. Through correlation, multiple regression and stepwise regression analysis, the potential combined effect of various explanatory variables on continuation intention was assessed, across the entire nursing cohort and in three age-generation groups. Three variables act in combination to explain continuation intention: work-family conflict, work attachment and importance of work to the individual. This combination of significant explanatory variables was consistent across the three generations of nursing employee. Work attachment was identified as the strongest marginal predictor of continuation intention. Work orientation has a greater impact on continuation intention compared with employer-directed interventions such as leader-member exchange, teamwork and autonomy. UK nurses are homogeneous across the three age-generations regarding explanation of continuation intention, with the significant explanatory measures being recognizably narrower in their focus and more greatly concentrated on the individual. This suggests that differentiated approaches to retention should perhaps not be pursued in this sectoral context. © 2014 John Wiley & Sons Ltd.

Prediction of Biological Motion Perception Performance from Intrinsic Brain Network Regional Efficiency

PubMed Central

Wang, Zengjian; Zhang, Delong; Liang, Bishan; Chang, Song; Pan, Jinghua; Huang, Ruiwang; Liu, Ming

2016-01-01

Biological motion perception (BMP) refers to the ability to perceive the moving form of a human figure from a limited amount of stimuli, such as from a few point lights located on the joints of a moving body. BMP is commonplace and important, but there is great inter-individual variability in this ability. This study used multiple regression model analysis to explore the association between BMP performance and intrinsic brain activity, in order to investigate the neural substrates underlying inter-individual variability of BMP performance. The resting-state functional magnetic resonance imaging (rs-fMRI) and BMP performance data were collected from 24 healthy participants, for whom intrinsic brain networks were constructed, and a graph-based network efficiency metric was measured. Then, a multiple linear regression model was used to explore the association between network regional efficiency and BMP performance. We found that the local and global network efficiency of many regions was significantly correlated with BMP performance. Further analysis showed that the local efficiency rather than global efficiency could be used to explain most of the BMP inter-individual variability, and the regions involved were predominately located in the Default Mode Network (DMN). Additionally, discrimination analysis showed that the local efficiency of certain regions such as the thalamus could be used to classify BMP performance across participants. Notably, the association pattern between network nodal efficiency and BMP was different from the association pattern of static directional/gender information perception. Overall, these findings show that intrinsic brain network efficiency may be considered a neural factor that explains BMP inter-individual variability. PMID:27853427

Macroalgal diversity along an inshore-offshore environmental gradient in the Jakarta Bay - Thousand Islands reef complex, Indonesia

NASA Astrophysics Data System (ADS)

Draisma, Stefano G. A.; Prud'homme van Reine, Willem F.; Herandarudewi, Sekar M. C.; Hoeksema, Bert W.

2018-01-01

The Jakarta Bay - Thousand Islands reef complex extends to more than 80 km in northwest direction from the major conurbation Jakarta (Indonesia) along a pronounced inshore to offshore environmental gradient. The present study aims to determine to what extent environmental factors can explain the composition of macroalgal communities on the reefs off Jakarta. Therefore, the presence-absence of 67 macroalgal taxa was recorded for 27 sampling sites along the inshore-offshore disturbance gradient and analysed with substrate variables and water quality variables. The macroalgal richness pattern matches the pattern of other reef taxa. The 27 sites could be assigned to one of four geographical zones with 85% certainty based on their macroalgal taxon assemblages. These four zones (i.e., Jakarta Bay and, respectively, South, Central, and North Thousand Islands) had significantly different macroalgal assemblages, except for the North and South zones. Along the nearshore gradient there was a greater shift in taxon composition than within the central Thousand Islands. The patterns of ten habitat and water quality variables resembled the macroalgal diversity patterns by 56%. All ten variables together explained 69% of the variation in macroalgal composition. Shelf depth, % sand cover, gelbstoff/detrital material, chlorophyll a concentration, seawater surface temperature, and % dead coral cover were the best predictors of seaweed flora composition. Furthermore, 44 macroalgal species represented new records for the area. The present study provides important baseline data of macroalgae in the area for comparison in future biodiversity assessments in the area and elsewhere in the region.

Quantitative Estimation of the Impact of European Teleconnections on Interannual Variation of East Asian Winter Temperature and Monsoon

NASA Technical Reports Server (NTRS)

Lim, Young-Kwon; Kim, Hae-Dong

2014-01-01

The impact of European teleconnections including the East AtlanticWest Russia (EA-WR), the Scandinavia (SCA), and the East Atlantic (EA) on East Asian winter temperature variability was quantified and compared with the combined effect of the Arctic Oscillation (AO), the Western Pacific (WP), and the El-Nino Southern Oscillation (ENSO), which are originated in the Northern Hemispheric high-latitudes or the Pacific. Three European teleconnections explained 22-25 percent of the total monthly upper-tropospheric height variance over Eurasia. Regression analysis revealed warming by EA-WR and EA and cooling by SCA over mid-latitude East Asia during their positive phase and vice versa. Temperature anomalies were largely explained by the advective temperature change process at the lower troposphere. The average spatial correlation over East Asia (90-180E, 10-80N) for the last 34 winters between observed and reconstructed temperature comprised of AO, WP and ENSO effect (AWE) was approximately 0.55, and adding the European teleconnection components (ESE) to the reconstructed temperature improved the correlation up to approximately 0.64. Lower level atmospheric structure demonstrated that approximately five of the last 34 winters were significantly better explained by ESE than AWE to determine East Asian seasonal winter temperatures. We also compared the impact between EA-WR and AO on the 1) East Asian winter monsoon, 2) cold surge, and 3) the Siberian high. These three were strongly coupled, and their spatial features and interannual variation were somewhat better explained by EA-WR than AO. Results suggest that the EA-WR impact must be treated more importantly than previously thought for a better understanding of East Asian winter temperature and monsoon variability.

Linkages Between Nutrients and Assemblages of Macroinvertebrates and Fish in Wadeable Streams: Implication to Nutrient Criteria Development

NASA Astrophysics Data System (ADS)

Wang, Lizhu; Robertson, Dale M.; Garrison, Paul J.

2007-02-01

We sampled 240 wadeable streams across Wisconsin for different forms of phosphorus and nitrogen, and assemblages of macroinvertebrates and fish to (1) examine how macroinvertebrate and fish measures correlated with the nutrients; (2) quantify relationships between key biological measures and nutrient forms to identify potential threshold levels of nutrients to support nutrient criteria development; and (3) evaluate the importance of nutrients in influencing biological assemblages relative to other physicochemical factors at different spatial scales. Twenty-three of the 35 fish and 18 of the 26 macroinvertebrate measures significantly correlated ( P < 0.05) with at least one nutrient measure. Percentages of carnivorous, intolerant, and omnivorous fishes, index of biotic integrity, and salmonid abundance were fish measures correlated with the most nutrient measures and had the highest correlation coefficients. Percentages of Ephemeroptera-Plecoptera-Trichoptera individuals and taxa, Hilsenhoff biotic index, and mean tolerance value were macroinvertebrate measures that most strongly correlated with the most nutrient measures. Selected biological measures showed clear trends toward degradation as concentrations of phosphorus and nitrogen increased, and some measures showed clear thresholds where biological measures changed drastically with small changes in nutrient concentrations. Our selected environmental factors explained 54% of the variation in the fish assemblages. Of this explained variance, 46% was attributed to catchment and instream habitat, 15% to nutrients, 3% to other water quality measures, and 36% to the interactions among all the environmental variables. Selected environmental factors explained 53% of the variation in macroinvertebrate assemblages. Of this explained variance, 42% was attributed to catchment and instream habitat, 22% to nutrients, 5% to other water quality measures, and 32% to the interactions among all the environmental variables.

Linkages between nutrients and assemblages of macroinvertebrates and fish in wadeable streams: Implication to nutrient criteria development

USGS Publications Warehouse

Wang, L.; Robertson, Dale M.; Garrison, P.J.

2007-01-01

We sampled 240 wadeable streams across Wisconsin for different forms of phosphorus and nitrogen, and assemblages of macroinvertebrates and fish to (1) examine how macroinvertebrate and fish measures correlated with the nutrients; (2) quantify relationships between key biological measures and nutrient forms to identify potential threshold levels of nutrients to support nutrient criteria development; and (3) evaluate the importance of nutrients in influencing biological assemblages relative to other physicochemical factors at different spatial scales. Twenty-three of the 35 fish and 18 of the 26 macroinvertebrate measures significantly correlated (P < 0.05) with at least one nutrient measure. Percentages of carnivorous, intolerant, and omnivorous fishes, index of biotic integrity, and salmonid abundance were fish measures correlated with the most nutrient measures and had the highest correlation coefficients. Percentages of Ephemeroptera-Plecoptera-Trichoptera individuals and taxa, Hilsenhoff biotic index, and mean tolerance value were macroinvertebrate measures that most strongly correlated with the most nutrient measures. Selected biological measures showed clear trends toward degradation as concentrations of phosphorus and nitrogen increased, and some measures showed clear thresholds where biological measures changed drastically with small changes in nutrient concentrations. Our selected environmental factors explained 54% of the variation in the fish assemblages. Of this explained variance, 46% was attributed to catchment and instream habitat, 15% to nutrients, 3% to other water quality measures, and 36% to the interactions among all the environmental variables. Selected environmental factors explained 53% of the variation in macroinvertebrate assemblages. Of this explained variance, 42% was attributed to catchment and instream habitat, 22% to nutrients, 5% to other water quality measures, and 32% to the interactions among all the environmental variables. ?? 2006 Springer Science+Business Media, Inc.

Fetal Environment Is a Major Determinant of the Neonatal Blood Thyroxine Level: Results of a Large Dutch Twin Study.

PubMed

Zwaveling-Soonawala, Nitash; van Beijsterveldt, Catharina E M; Mesfum, Ertirea T; Wiedijk, Brenda; Oomen, Petra; Finken, Martijn J J; Boomsma, Dorret I; van Trotsenburg, A S Paul

2015-06-01

The interindividual variability in thyroid hormone function parameters is much larger than the intraindividual variability, suggesting an individual set point for these parameters. There is evidence to suggest that environmental factors are more important than genetic factors in the determination of this individual set point. This study aimed to quantify the effect of genetic factors and (fetal) environment on the early postnatal blood T4 concentration. This was a classical twin study comparing the resemblance of neonatal screening blood T4 concentrations in 1264 mono- and 2566 dizygotic twin pairs retrieved from the population-based Netherlands Twin Register. Maximum-likelihood estimates of variance explained by genetic and environmental influences were obtained by structural equation modeling in data from full-term and preterm twin pairs. In full-term infants, genetic factors explained 40%/31% of the variance in standardized T4 scores in boys/girls, and shared environment, 27%/22%. The remaining variance of 33%/47% was due to environmental factors not shared by twins. For preterm infants, genetic factors explained 34%/0% of the variance in boys/girls, shared environment 31%/57%, and unique environment 35%/43%. In very preterm twins, no significant contribution of genetic factors was observed. Environment explains a large proportion of the resemblance of the postnatal blood T4 concentration in twin pairs. Because we analyzed neonatal screening results, the fetal environment is the most likely candidate for these environmental influences. Genetic influences on the T4 set point diminished with declining gestational age, especially in girls. This may be due to major environmental influences such as immaturity and nonthyroidal illness in very preterm infants.

Relationships between Adaptive Behaviours, Personal Factors, and Participation of Young Children.

PubMed

Killeen, Hazel; Shiel, Agnes; Law, Mary; O'Donovan, Donough J; Segurado, Ricardo; Anaby, Dana

2017-12-19

To examine the extent to which personal factors (age, socioeconomic grouping, and preterm birth) and adaptive behaviour explain the participation patterns of young children. 65 Children 2-5 years old with and without a history of preterm birth and no physical or intellectual disability were selected by convenience sampling from Galway University Hospital, Ireland. Interviews with parents were conducted using the Adaptive Behaviour Assessment System, Second Edition (ABAS-II) and the Assessment of Preschool Children's Participation (APCP). Linear regression models were used to identify associations between the ABAS-II scores, personal factors, and APCP scores for intensity and diversity of participation. Adaptive behaviour explained 21% of variance in intensity of play, 18% in intensity of Skill Development, 7% in intensity of Active Physical Recreation, and 6% in intensity of Social Activities controlling for age, preterm birth, and socioeconomic grouping. Age explained between 1% and 11% of variance in intensity of participation scores. Adapted behaviour (13%), Age (17%), and socioeconomic grouping (5%) explained a significant percentage of variance in diversity of participation controlling for the other variables.  Adaptive behaviour had a unique contribution to children's intensity and diversity of participation, suggesting its importance.

Prediction of Short-Distance Aerial Movement of Phakopsora pachyrhizi Urediniospores Using Machine Learning.

PubMed

Wen, L; Bowen, C R; Hartman, G L

2017-10-01

Dispersal of urediniospores by wind is the primary means of spread for Phakopsora pachyrhizi, the cause of soybean rust. Our research focused on the short-distance movement of urediniospores from within the soybean canopy and up to 61 m from field-grown rust-infected soybean plants. Environmental variables were used to develop and compare models including the least absolute shrinkage and selection operator regression, zero-inflated Poisson/regular Poisson regression, random forest, and neural network to describe deposition of urediniospores collected in passive and active traps. All four models identified distance of trap from source, humidity, temperature, wind direction, and wind speed as the five most important variables influencing short-distance movement of urediniospores. The random forest model provided the best predictions, explaining 76.1 and 86.8% of the total variation in the passive- and active-trap datasets, respectively. The prediction accuracy based on the correlation coefficient (r) between predicted values and the true values were 0.83 (P < 0.0001) and 0.94 (P < 0.0001) for the passive and active trap datasets, respectively. Overall, multiple machine learning techniques identified the most important variables to make the most accurate predictions of movement of P. pachyrhizi urediniospores short-distance.

A study on the causal effect of urban population growth and international trade on environmental pollution: evidence from China.

PubMed

Boamah, Kofi Baah; Du, Jianguo; Boamah, Angela Jacinta; Appiah, Kingsley

2018-02-01

This study seeks to contribute to the recent literature by empirically investigating the causal effect of urban population growth and international trade on environmental pollution of China, for the period 1980-2014. The Johansen cointegration confirmed a long-run cointegration association among the utilised variables for the case of China. The direction of causality among the variables was, consequently, investigated using the recent bootstrapped Granger causality test. This bootstrapped Granger causality approach is preferred as it provides robust and accurate critical values for statistical inferences. The findings from the causality analysis revealed the existence of a bi-directional causality between import and urban population. The three most paramount variables that explain the environmental pollution in China, according to the impulse response function, are imports, urbanisation and energy consumption. Our study further established the presence of an N-shaped environmental Kuznets curve relationship between economic growth and environmental pollution of China. Hence, our study recommends that China should adhere to stricter environmental regulations in international trade, as well as enforce policies that promote energy efficiency in the urban residential and commercial sector, in the quest to mitigate environmental pollution issues as the economy advances.

Dynamic Modeling of the Main Blow in Basic Oxygen Steelmaking Using Measured Step Responses

NASA Astrophysics Data System (ADS)

Kattenbelt, Carolien; Roffel, B.

2008-10-01

In the control and optimization of basic oxygen steelmaking, it is important to have an understanding of the influence of control variables on the process. However, important process variables such as the composition of the steel and slag cannot be measured continuously. The decarburization rate and the accumulation rate of oxygen, which can be derived from the generally measured waste gas flow and composition, are an indication of changes in steel and slag composition. The influence of the control variables on the decarburization rate and the accumulation rate of oxygen can best be determined in the main blow period. In this article, the measured step responses of the decarburization rate and the accumulation rate of oxygen to step changes in the oxygen blowing rate, lance height, and the addition rate of iron ore during the main blow are presented. These measured step responses are subsequently used to develop a dynamic model for the main blow. The model consists of an iron oxide and a carbon balance and an additional equation describing the influence of the lance height and the oxygen blowing rate on the decarburization rate. With this simple dynamic model, the measured step responses can be explained satisfactorily.

Belonging and doing: important factors for satisfaction with sexual relations as perceived by people with persistent mental illness.

PubMed

Eklund, Mona; Ostman, Margareta

2010-07-01

It is increasingly acknowledged that satisfaction with sexual relations forms an important aspect of people's lives, but little is known of factors associated with this phenomenon among people with mental illness. This study aimed to investigate how demographic, social, clinical, and health-related factors were related to satisfaction with sexual relations. Patients with persistent mental illness (N = 103), recruited from an outpatient unit, were assessed regarding the target variables. No clinical variable, and only one demographic factor, namely being a cohabitant, was found to be important to satisfaction with sexual relations. Several social factors, pertaining to how everyday occupations were valued and how the social network was perceived, were shown to be of importance. General quality of life, but not self-rated health or interviewer-assessed psychopathology, was also important for satisfaction with sexual relations. A multivariate analysis showed that the most significant factor for satisfaction with sexual relations was how everyday activities were valued, and being a cohabitant explained some additional variation. Previous research indicates that the mental health care services largely neglect sexual problems among people with mental illness, and the findings may provide additional knowledge that may be used in the support of this target group.

Associations between complex OHC mixtures and thyroid and cortisol hormone levels in East Greenland polar bears

PubMed Central

TØ, Bechshøft; Sonne, C; Dietz, R; Born, EW; Muir, DCG; Letcher, RJ; Novak, MA; Henchey, E; Meyer, JS; Jenssen, BM; Villanger, GD

2012-01-01

The multivariate relationship between hair cortisol, whole blood thyroid hormones, and the complex mixtures of organohalogen contaminant (OHC) levels measured in subcutaneous adipose of 23 East Greenland polar bears (eight males and 15 females, all sampled between the years 1999 and 2001) was analyzed using projection to latent structure (PLS) regression modeling. In the resulting PLS model, most important variables with a negative influence on cortisol levels were particularly BDE-99, but also CB-180, -201, BDE-153, and CB-170/190. The most important variables with a positive influence on cortisol were CB-66/95, α-HCH, TT3, as well as heptachlor epoxide, dieldrin, BDE-47, p,p′-DDD. Although statistical modeling does not necessarily fully explain biological cause-effect relationships, relationships indicate that (1) the hypothalamic-pituitary-adrenal (HPA) axis in East Greenland polar bears is likely to be affected by OHC-contaminants and (2) the association between OHCs and cortisol may be linked with the hypothalamus-pituitary-thyroid (HPT) axis. PMID:22575327

The factors controlling species density in herbaceous plant communities: An assessment

USGS Publications Warehouse

Grace, J.B.

1999-01-01

This paper evaluates both the ideas and empirical evidence pertaining to the control of species density in herbaceous plant communities. While most theoretical discussions of species density have emphasized the importance of habitat productivity and disturbance regimes, many other factors (e.g. species pools, plant litter accumulation, plant morphology) have been proposed to be important. A review of literature presenting observations on the density of species in small plots (in the vicinity of a few square meters or less), as well as experimental studies, suggests several generalizations: (1) Available data are consistent with an underlying unimodal relationship between species density and total community biomass. While variance in species density is often poorly explained by predictor variables, there is strong evidence that high levels of community biomass are antagonistic to high species density. (2) Community biomass is just one of several factors affecting variations in species density. Multivariate analyses typically explain more than twice as much variance in species density as can be explained by community biomass alone. (3) Disturbance has important and sometimes complex effects on species density. In general, the evidence is consistent with the intermediate disturbance hypothesis but exceptions exist and effects can be complex. (4) Gradients in the species pool can have important influences on patterns of species density. Evidence is mounting that a considerable amount of the observed variability in species density within a landscape or region may result from environmental effects on the species pool. (5) Several additional factors deserve greater consideration, including time lags, species composition, plant morphology, plant density and soil microbial effects. Based on the available evidence, a conceptual model of the primary factors controlling species density is presented here. This model suggests that species density is controlled by the effects of disturbance, total community biomass, colonization, the species pool and spatial heterogeneity. The structure of the model leads to two main expectations: (1) while community biomass is important, multivariate approaches will be required to understand patterns of variation in species density, and (2) species density will be more highly correlated with light penetration to the soil surface, than with above-ground biomass, and even less well correlated with plant growth rates (productivity) or habitat fertility. At present, data are insufficient to evaluate the relative importance of the processes controlling species density. Much more work is needed if we are to adequately predict the effects of environmental changes on plant communities and species diversity.

Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage

USGS Publications Warehouse

Mattsson, Brady J.; Zipkin, Elise F.; Gardner, Beth; Blank, Peter J.; Sauer, John R.; Royle, J. Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage.

PubMed

Mattsson, Brady J; Zipkin, Elise F; Gardner, Beth; Blank, Peter J; Sauer, John R; Royle, J Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

Explaining Local-Scale Species Distributions: Relative Contributions of Spatial Autocorrelation and Landscape Heterogeneity for an Avian Assemblage

PubMed Central

Mattsson, Brady J.; Zipkin, Elise F.; Gardner, Beth; Blank, Peter J.; Sauer, John R.; Royle, J. Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition. PMID:23393564

Probabilistic prediction of barrier-island response to hurricanes

USGS Publications Warehouse

Plant, Nathaniel G.; Stockdon, Hilary F.

2012-01-01

Prediction of barrier-island response to hurricane attack is important for assessing the vulnerability of communities, infrastructure, habitat, and recreational assets to the impacts of storm surge, waves, and erosion. We have demonstrated that a conceptual model intended to make qualitative predictions of the type of beach response to storms (e.g., beach erosion, dune erosion, dune overwash, inundation) can be reformulated in a Bayesian network to make quantitative predictions of the morphologic response. In an application of this approach at Santa Rosa Island, FL, predicted dune-crest elevation changes in response to Hurricane Ivan explained about 20% to 30% of the observed variance. An extended Bayesian network based on the original conceptual model, which included dune elevations, storm surge, and swash, but with the addition of beach and dune widths as input variables, showed improved skill compared to the original model, explaining 70% of dune elevation change variance and about 60% of dune and shoreline position change variance. This probabilistic approach accurately represented prediction uncertainty (measured with the log likelihood ratio), and it outperformed the baseline prediction (i.e., the prior distribution based on the observations). Finally, sensitivity studies demonstrated that degrading the resolution of the Bayesian network or removing data from the calibration process reduced the skill of the predictions by 30% to 40%. The reduction in skill did not change conclusions regarding the relative importance of the input variables, and the extended model's skill always outperformed the original model.

Using geomorphological variables to predict the spatial distribution of plant species in agricultural drainage networks

PubMed Central

Bailly, Jean-Stéphane; Vinatier, Fabrice

2018-01-01

To optimize ecosystem services provided by agricultural drainage networks (ditches) in headwater catchments, we need to manage the spatial distribution of plant species living in these networks. Geomorphological variables have been shown to be important predictors of plant distribution in other ecosystems because they control the water regime, the sediment deposition rates and the sun exposure in the ditches. Whether such variables may be used to predict plant distribution in agricultural drainage networks is unknown. We collected presence and absence data for 10 herbaceous plant species in a subset of a network of drainage ditches (35 km long) within a Mediterranean agricultural catchment. We simulated their spatial distribution with GLM and Maxent model using geomorphological variables and distance to natural lands and roads. Models were validated using k-fold cross-validation. We then compared the mean Area Under the Curve (AUC) values obtained for each model and other metrics issued from the confusion matrices between observed and predicted variables. Based on the results of all metrics, the models were efficient at predicting the distribution of seven species out of ten, confirming the relevance of geomorphological variables and distance to natural lands and roads to explain the occurrence of plant species in this Mediterranean catchment. In particular, the importance of the landscape geomorphological variables, ie the importance of the geomorphological features encompassing a broad environment around the ditch, has been highlighted. This suggests that agro-ecological measures for managing ecosystem services provided by ditch plants should focus on the control of the hydrological and sedimentological connectivity at the catchment scale. For example, the density of the ditch network could be modified or the spatial distribution of vegetative filter strips used for sediment trapping could be optimized. In addition, the vegetative filter strips could constitute new seed bank sources for species that are affected by the distance to natural lands and roads. PMID:29360857

Using geomorphological variables to predict the spatial distribution of plant species in agricultural drainage networks.

PubMed

Rudi, Gabrielle; Bailly, Jean-Stéphane; Vinatier, Fabrice

2018-01-01

To optimize ecosystem services provided by agricultural drainage networks (ditches) in headwater catchments, we need to manage the spatial distribution of plant species living in these networks. Geomorphological variables have been shown to be important predictors of plant distribution in other ecosystems because they control the water regime, the sediment deposition rates and the sun exposure in the ditches. Whether such variables may be used to predict plant distribution in agricultural drainage networks is unknown. We collected presence and absence data for 10 herbaceous plant species in a subset of a network of drainage ditches (35 km long) within a Mediterranean agricultural catchment. We simulated their spatial distribution with GLM and Maxent model using geomorphological variables and distance to natural lands and roads. Models were validated using k-fold cross-validation. We then compared the mean Area Under the Curve (AUC) values obtained for each model and other metrics issued from the confusion matrices between observed and predicted variables. Based on the results of all metrics, the models were efficient at predicting the distribution of seven species out of ten, confirming the relevance of geomorphological variables and distance to natural lands and roads to explain the occurrence of plant species in this Mediterranean catchment. In particular, the importance of the landscape geomorphological variables, ie the importance of the geomorphological features encompassing a broad environment around the ditch, has been highlighted. This suggests that agro-ecological measures for managing ecosystem services provided by ditch plants should focus on the control of the hydrological and sedimentological connectivity at the catchment scale. For example, the density of the ditch network could be modified or the spatial distribution of vegetative filter strips used for sediment trapping could be optimized. In addition, the vegetative filter strips could constitute new seed bank sources for species that are affected by the distance to natural lands and roads.

Determinants of single family residential water use across scales in four western US cities.

PubMed

Chang, Heejun; Bonnette, Matthew Ryan; Stoker, Philip; Crow-Miller, Britt; Wentz, Elizabeth

2017-10-15

A growing body of literature examines urban water sustainability with increasing evidence that locally-based physical and social spatial interactions contribute to water use. These studies however are based on single-city analysis and often fail to consider whether these interactions occur more generally. We examine a multi-city comparison using a common set of spatially-explicit water, socioeconomic, and biophysical data. We investigate the relative importance of variables for explaining the variations of single family residential (SFR) water uses at Census Block Group (CBG) and Census Tract (CT) scales in four representative western US cities - Austin, Phoenix, Portland, and Salt Lake City, - which cover a wide range of climate and development density. We used both ordinary least squares regression and spatial error regression models to identify the influence of spatial dependence on water use patterns. Our results show that older downtown areas show lower water use than newer suburban areas in all four cities. Tax assessed value and building age are the main determinants of SFR water use across the four cities regardless of the scale. Impervious surface area becomes an important variable for summer water use in all cities, and it is important in all seasons for arid environments such as Phoenix. CT level analysis shows better model predictability than CBG analysis. In all cities, seasons, and spatial scales, spatial error regression models better explain the variations of SFR water use. Such a spatially-varying relationship of urban water consumption provides additional evidence for the need to integrate urban land use planning and municipal water planning. Copyright © 2017 Elsevier B.V. All rights reserved.

Subacute casemix classification for stroke rehabilitation in Australia. How well does AN-SNAP v2 explain variance in outcomes?

PubMed

Kohler, Friedbert; Renton, Roger; Dickson, Hugh G; Estell, John; Connolly, Carol E

2011-02-01

We sought the best predictors for length of stay, discharge destination and functional improvement for inpatients undergoing rehabilitation following a stroke and compared these predictors against AN-SNAP v2. The Oxfordshire classification subgroup, sociodemographic data and functional data were collected for patients admitted between 1997 and 2007, with a diagnosis of recent stroke. The data were factor analysed using Principal Components Analysis for categorical data (CATPCA). Categorical regression analyses was performed to determine the best predictors of length of stay, discharge destination, and functional improvement. A total of 1154 patients were included in the study. Principal components analysis indicated that the data were effectively unidimensional, with length of stay being the most important component. Regression analysis demonstrated that the best predictor was the admission motor FIM score, explaining 38.9% of variance for length of stay, 37.4%.of variance for functional improvement and 16% of variance for discharge destination. The best explanatory variable in our inpatient rehabilitation service is the admission motor FIM. AN- SNAP v2 classification is a less effective explanatory variable. This needs to be taken into account when using AN-SNAP v2 classification for clinical or funding purposes.

Risk factors for childhood obesity in elementary school-age Taiwanese children.

PubMed

Chen, Jyu-Lin; Kennedy, Christine; Yeh, Chao-Hsing; Kools, Susan

2005-01-01

A cross-sectional study design was used to examine factors that contribute to high relative weight in children in Taiwan. A total sample of 331 Chinese children (ages 7 and 8) and their parents participated in the study. Parents completed questionnaires regarding demographic information, family functioning, parenting styles, physical activity, and dietary intake. Children completed physical fitness tests and questionnaires regarding physical activity, dietary intake, coping strategies, and self-esteem. The weight-for-length index was used to measure children's relative weight. The findings revealed that four variables contributed to higher weight-for-length index in boys compared with girls and explained 37.7% of the variance: high maternal body mass index, poor aerobic capacity, healthy family role functioning, and poor family affective responsiveness. Two variables were found to contribute to higher weight-for-length index in girls and explained 12.8% of the variance: high household income and high maternal body mass index. Taken together, the results indicate the importance of assessment of children's weight status, maternal weight status, and family functioning as part of routine child health care and the need for developmentally appropriate and gender-specific approaches to prevent childhood obesity.

Coping styles as moderating the relationships between terrorist attacks and well-being outcomes.

PubMed

Braun-Lewensohn, Orna; Celestin-Westreich, Smadar; Celestin, Leon-Patrice; Verleye, Gino; Verté, Dominique; Ponjaert-Kristoffersen, Ingrid

2009-06-01

This study aims to explore use of coping strategies among adolescents and their relationships with well being in the context of ongoing terrorism. Furthermore, we aim to explore to what extent coping styles in addition to exposure variables explain well being of adolescents facing ongoing terror. During September 2003, after three years of ongoing terror attacks, 913 Israeli adolescents aged 12-18 years, completed the following questionnaires during regular class sessions: Demographics, Achenbach's Youth Self Report; Exposure to Terror and Post Traumatic Stress (PTS) questionnaire; Adolescent Coping Scale (ACS) and Brief Symptoms Inventory. Adolescents employed mainly problem solving strategies which mean they have the capacity to cope well in spite of stressful events. Emotional focused coping was associated with PTS and mental health problems. Regression analysis of different exposure and coping variables revealed that exposure, appraisal (subjective exposure) and coping styles explained 26-37% of the variance of different psychological problems. The findings highlight the importance of appraisal (subjective exposure) and coping strategies, for understanding adolescents' mental health outcomes. Moreover, these findings are relevant to the development of prevention/intervention programs that facilitate youth's cognitive and emotional adjustments to ongoing trauma risks and terror threats.

Optimization of biomass composition explains microbial growth-stoichiometry relationships

USGS Publications Warehouse

Franklin, O.; Hall, E.K.; Kaiser, C.; Battin, T.J.; Richter, A.

2011-01-01

Integrating microbial physiology and biomass stoichiometry opens far-reaching possibilities for linking microbial dynamics to ecosystem processes. For example, the growth-rate hypothesis (GRH) predicts positive correlations among growth rate, RNA content, and biomass phosphorus (P) content. Such relationships have been used to infer patterns of microbial activity, resource availability, and nutrient recycling in ecosystems. However, for microorganisms it is unclear under which resource conditions the GRH applies. We developed a model to test whether the response of microbial biomass stoichiometry to variable resource stoichiometry can be explained by a trade-off among cellular components that maximizes growth. The results show mechanistically why the GRH is valid under P limitation but not under N limitation. We also show why variability of growth rate-biomass stoichiometry relationships is lower under P limitation than under N or C limitation. These theoretical results are supported by experimental data on macromolecular composition (RNA, DNA, and protein) and biomass stoichiometry from two different bacteria. In addition, compared to a model with strictly homeostatic biomass, the optimization mechanism we suggest results in increased microbial N and P mineralization during organic-matter decomposition. Therefore, this mechanism may also have important implications for our understanding of nutrient cycling in ecosystems.

A Little Knowledge of Ground Motion: Explaining 3-D Physics-Based Modeling to Engineers

NASA Astrophysics Data System (ADS)

Porter, K.

2014-12-01

Users of earthquake planning scenarios require the ground-motion map to be credible enough to justify costly planning efforts, but not all ground-motion maps are right for all uses. There are two common ways to create a map of ground motion for a hypothetical earthquake. One approach is to map the median shaking estimated by empirical attenuation relationships. The other uses 3-D physics-based modeling, in which one analyzes a mathematical model of the earth's crust near the fault rupture and calculates the generation and propagation of seismic waves from source to ground surface by first principles. The two approaches produce different-looking maps. The more-familiar median maps smooth out variability and correlation. Using them in a planning scenario can lead to a systematic underestimation of damage and loss, and could leave a community underprepared for realistic shaking. The 3-D maps show variability, including some very high values that can disconcert non-scientists. So when the USGS Science Application for Risk Reduction's (SAFRR) Haywired scenario project selected 3-D maps, it was necessary to explain to scenario users—especially engineers who often use median maps—the differences, advantages, and disadvantages of the two approaches. We used authority, empirical evidence, and theory to support our choice. We prefaced our explanation with SAFRR's policy of using the best available earth science, and cited the credentials of the maps' developers and the reputation of the journal in which they published the maps. We cited recorded examples from past earthquakes of extreme ground motions that are like those in the scenario map. We explained the maps on theoretical grounds as well, explaining well established causes of variability: directivity, basin effects, and source parameters. The largest mapped motions relate to potentially unfamiliar extreme-value theory, so we used analogies to human longevity and the average age of the oldest person in samples of varying sizes to illustrate extreme values to non-scientists. We explained the importance of nonlinearity in the relationship between shaking and loss. This was the second time SAFRR encountered skeptics of 3-D maps among scenario consumers, so a short manuscript was prepared that would serve similar uses in the future.

Exploring biological, chemical and geomorphological patterns in fluvial ecosystems with Structural Equation Modelling

NASA Astrophysics Data System (ADS)

Bizzi, S.; Surridge, B.; Lerner, D. N.:

2009-04-01

River ecosystems represent complex networks of interacting biological, chemical and geomorphological processes. These processes generate spatial and temporal patterns in biological, chemical and geomorphological variables, and a growing number of these variables are now being used to characterise the status of rivers. However, integrated analyses of these biological-chemical-geomorphological networks have rarely been undertaken, and as a result our knowledge of the underlying processes and how they generate the resulting patterns remains weak. The apparent complexity of the networks involved, and the lack of coherent datasets, represent two key challenges to such analyses. In this paper we describe the application of a novel technique, Structural Equation Modelling (SEM), to the investigation of biological, chemical and geomorphological data collected from rivers across England and Wales. The SEM approach is a multivariate statistical technique enabling simultaneous examination of direct and indirect relationships across a network of variables. Further, SEM allows a-priori conceptual or theoretical models to be tested against available data. This is a significant departure from the solely exploratory analyses which characterise other multivariate techniques. We took biological, chemical and river habitat survey data collected by the Environment Agency for 400 sites in rivers spread across England and Wales, and created a single, coherent dataset suitable for SEM analyses. Biological data cover benthic macroinvertebrates, chemical data relate to a range of standard parameters (e.g. BOD, dissolved oxygen and phosphate concentration), and geomorphological data cover factors such as river typology, substrate material and degree of physical modification. We developed a number of a-priori conceptual models, reflecting current research questions or existing knowledge, and tested the ability of these conceptual models to explain the variance and covariance within the dataset. The conceptual models we developed were able to explain correctly the variance and covariance shown by the datasets, proving to be a relevant representation of the processes involved. The models explained 65% of the variance in indices describing benthic macroinvertebrate communities. Dissolved oxygen was of primary importance, but geomorphological factors, including river habitat type and degree of habitat degradation, also had significant explanatory power. The addition of spatial variables, such as latitude or longitude, did not provide additional explanatory power. This suggests that the variables already included in the models effectively represented the eco-regions across which our data were distributed. The models produced new insights into the relative importance of chemical and geomorphological factors for river macroinvertebrate communities. The SEM technique proved a powerful tool for exploring complex biological-chemical-geomorphological networks, for example able to deal with the co-correlations that are common in rivers due to multiple feedback mechanisms.

Modelling dengue fever risk in the State of Yucatan, Mexico using regional-scale satellite-derived sea surface temperature.

PubMed

Laureano-Rosario, Abdiel E; Garcia-Rejon, Julian E; Gomez-Carro, Salvador; Farfan-Ale, Jose A; Muller-Karger, Frank E

2017-08-01

Accurately predicting vector-borne diseases, such as dengue fever, is essential for communities worldwide. Changes in environmental parameters such as precipitation, air temperature, and humidity are known to influence dengue fever dynamics. Furthermore, previous studies have shown how oceanographic variables, such as El Niño Southern Oscillation (ENSO)-related sea surface temperature from the Pacific Ocean, influences dengue fever in the Americas. However, literature is lacking on the use of regional-scale satellite-derived sea surface temperature (SST) to assess its relationship with dengue fever in coastal areas. Data on confirmed dengue cases, demographics, precipitation, and air temperature were collected. Incidence of weekly dengue cases was examined. Stepwise multiple regression analyses (AIC model selection) were used to assess which environmental variables best explained increased dengue incidence rates. SST, minimum air temperature, precipitation, and humidity substantially explained 42% of the observed variation (r 2 =0.42). Infectious diseases are characterized by the influence of past cases on current cases and results show that previous dengue cases alone explained 89% of the variation. Ordinary least-squares analyses showed a positive trend of 0.20±0.03°C in SST from 2006 to 2015. An important element of this study is to help develop strategic recommendations for public health officials in Mexico by providing a simple early warning capability for dengue incidence. Copyright © 2017 Elsevier B.V. All rights reserved.

Assessing the Moderating Effect of the End User in Consumer Behavior: The Acceptance of Technological Implants to Increase Innate Human Capacities

PubMed Central

Pelegrín-Borondo, Jorge; Reinares-Lara, Eva; Olarte-Pascual, Cristina; Garcia-Sierra, Marta

2016-01-01

Today, technological implants are being developed to increase innate human capacities, such as memory or calculation speed, and to endow us with new ones, such as the remote control of machines. This study's aim was two-fold: first, to introduce a Cognitive-Affective-Normative (CAN) model of technology acceptance to explain the intention to use this technology in the field of consumer behavior; and second, to analyze the differences in the intention to use it based on whether the intended implant recipient is oneself or one's child (i.e., the moderating effect of the end user). A multi-group analysis was performed to compare the results between the two groups: implant “for me” (Group 1) and implant “for my child” (Group 2). The model largely explains the intention to use the insideable technology for the specified groups [variance explained (R2) of over 0.70 in both cases]. The most important variables were found to be “positive emotions” and (positive) “subjective norm.” This underscores the need to broaden the range of factors considered to be decisive in technology acceptance to include variables related to consumers' emotions. Moreover, statistically significant differences were found between the “for me” and “for my child” models for “perceived ease of use (PEU)” and “subjective norm.” These findings confirm the moderating effect of the end user on new insideable technology acceptance. PMID:26941662

Colony geometry and structural complexity of the endangered species Acropora cervicornis partly explains the structure of their associated fish assemblage.

PubMed

Agudo-Adriani, Esteban A; Cappelletto, Jose; Cavada-Blanco, Francoise; Croquer, Aldo

2016-01-01

In the past decade, significant efforts have been made to describe fish-habitat associations. However, most studies have oversimplified actual connections between fish assemblages and their habitats by using univariate correlations. The purpose of this study was to identify the features of habitat forming corals that facilitate and influences assemblages of associated species such as fishes. For this we developed three-dimensional models of colonies of Acropora cervicornis to estimate geometry (length and height), structural complexity (i.e., volume, density of branches, etc.) and biological features of the colonies (i.e., live coral tissue, algae). We then correlated these colony characteristics with the associated fish assemblage using multivariate analyses. We found that geometry and complexity were better predictors of the structure of fish community, compared to other variables such as percentage of live coral tissue or algae. Combined, the geometry of each colony explained 40% of the variability of the fish assemblage structure associated with this coral species; 61% of the abundance and 69% of fish richness, respectively. Our study shows that three-dimensional reconstructions of discrete colonies of Acropora cervicornis provides a useful description of the colonial structural complexity and may explain a great deal of the variance in the structure of the associated coral reef fish community. This demonstration of the strongly trait-dependent ecosystem role of this threatened species has important implications for restoration and conservation efforts.

Colony geometry and structural complexity of the endangered species Acropora cervicornis partly explains the structure of their associated fish assemblage

PubMed Central

Cappelletto, Jose; Cavada-Blanco, Francoise; Croquer, Aldo

2016-01-01

In the past decade, significant efforts have been made to describe fish-habitat associations. However, most studies have oversimplified actual connections between fish assemblages and their habitats by using univariate correlations. The purpose of this study was to identify the features of habitat forming corals that facilitate and influences assemblages of associated species such as fishes. For this we developed three-dimensional models of colonies of Acropora cervicornis to estimate geometry (length and height), structural complexity (i.e., volume, density of branches, etc.) and biological features of the colonies (i.e., live coral tissue, algae). We then correlated these colony characteristics with the associated fish assemblage using multivariate analyses. We found that geometry and complexity were better predictors of the structure of fish community, compared to other variables such as percentage of live coral tissue or algae. Combined, the geometry of each colony explained 40% of the variability of the fish assemblage structure associated with this coral species; 61% of the abundance and 69% of fish richness, respectively. Our study shows that three-dimensional reconstructions of discrete colonies of Acropora cervicornis provides a useful description of the colonial structural complexity and may explain a great deal of the variance in the structure of the associated coral reef fish community. This demonstration of the strongly trait-dependent ecosystem role of this threatened species has important implications for restoration and conservation efforts. PMID:27069801

Sorafenib metabolism, transport, and enterohepatic recycling: physiologically based modeling and simulation in mice.

PubMed

Edginton, Andrea N; Zimmerman, Eric I; Vasilyeva, Aksana; Baker, Sharyn D; Panetta, John C

2016-05-01

This study used uncertainty and sensitivity analysis to evaluate a physiologically based pharmacokinetic (PBPK) model of the complex mechanisms of sorafenib and its two main metabolites, sorafenib glucuronide and sorafenib N-oxide in mice. A PBPK model for sorafenib and its two main metabolites was developed to explain disposition in mice. It included relevant influx (Oatp) and efflux (Abcc2 and Abcc3) transporters, hepatic metabolic enzymes (CYP3A4 and UGT1A9), and intestinal β-glucuronidase. Parameterization of drug-specific processes was based on in vitro, ex vivo, and in silico data along with plasma and liver pharmacokinetic data from single and multiple transporter knockout mice. Uncertainty analysis demonstrated that the model structure and parameter values could explain the observed variability in the pharmacokinetic data. Global sensitivity analysis demonstrated the global effects of metabolizing enzymes on sorafenib and metabolite disposition and the local effects of transporters on their respective substrate exposures. In addition, through hypothesis testing, the model supported that the influx transporter Oatp is a weak substrate for sorafenib and a strong substrate for sorafenib glucuronide and that the efflux transporter Abcc2 is not the only transporter affected in the Abcc2 knockout mouse. Translation of the mouse model to humans for the purpose of explaining exceptionally high human pharmacokinetic variability and its relationship with exposure-dependent dose-limiting toxicities will require delineation of the importance of these processes on disposition.

Advantage of hyperspectral EO-1 Hyperion over multispectral IKONOS, GeoEye-1, WorldView-2, Landsat ETM+, and MODIS vegetation indices in crop biomass estimation

USGS Publications Warehouse

Marshall, Michael T.; Thenkabail, Prasad S.

2015-01-01

Crop biomass is increasingly being measured with surface reflectance data derived from multispectral broadband (MSBB) and hyperspectral narrowband (HNB) space-borne remotely sensed data to increase the accuracy and efficiency of crop yield models used in a wide array of agricultural applications. However, few studies compare the ability of MSBBs versus HNBs to capture crop biomass variability. Therefore, we used standard data mining techniques to identify a set of MSBB data from the IKONOS, GeoEye-1, Landsat ETM+, MODIS, WorldView-2 sensors and compared their performance with HNB data from the EO-1 Hyperion sensor in explaining crop biomass variability of four important field crops (rice, alfalfa, cotton, maize). The analysis employed two-band (ratio) vegetation indices (TBVIs) and multiband (additive) vegetation indices (MBVIs) derived from Singular Value Decomposition (SVD) and stepwise regression. Results demonstrated that HNB-derived TBVIs and MBVIs performed better than MSBB-derived TBVIs and MBVIs on a per crop basis and for the pooled data: overall, HNB TBVIs explained 5–31% greater variability when compared with various MSBB TBVIs; and HNB MBVIs explained 3–33% greater variability when compared with various MSBB MBVIs. The performance of MSBB MBVIs and TBVIs improved mildly, by combining spectral information across multiple sensors involving IKONOS, GeoEye-1, Landsat ETM+, MODIS, and WorldView-2. A number of HNBs that advance crop biomass modeling were determined. Based on the highest factor loadings on the first component of the SVD, the “red-edge” spectral range (700–740 nm) centered at 722 nm (bandwidth = 10 nm) stood out prominently, while five additional and distinct portions of the recorded spectral range (400–2500 nm) centered at 539 nm, 758 nm, 914 nm, 1130 nm, 1320 nm (bandwidth = 10 nm) were also important. The best HNB vegetation indices for crop biomass estimation involved 549 and 752 nm for rice (R2 = 0.91); 925 and 1104 nm for alfalfa (R2 = 0.81); 722 and 732 nm for cotton (R2 = 0.97); and 529 and 895 nm for maize (R2 = 0.94). The higher spectral resolution of the EO-1 Hyperion hyperspectral sensor and the ability of users to choose distinct HNBs for improved crop biomass estimation outweigh the benefits that come with higher spatial resolution of MSBBs.

Complexity in Climatic Controls on Plant Species Distribution: Satellite Data Reveal Unique Climate for Giant Sequoia in the California Sierra Nevada

NASA Astrophysics Data System (ADS)

Waller, Eric Kindseth

A better understanding of the environmental controls on current plant species distribution is essential if the impacts of such diverse challenges as invasive species, changing fire regimes, and global climate change are to be predicted and important diversity conserved. Climate, soil, hydrology, various biotic factors fire, history, and chance can all play a role, but disentangling these factors is a daunting task. Increasingly sophisticated statistical models relying on existing distributions and mapped climatic variables, among others, have been developed to try to answer these questions. Any failure to explain pattern with existing mapped climatic variables is often taken as a referendum on climate as a whole, rather than on the limitations of the particular maps or models. Every location has a unique and constantly changing climate so that any distribution could be explained by some aspect of climate. Chapter 1 of this dissertation reviews some of the major flaws in species distribution modeling and addresses concerns that climate may therefore not be predictive of, or even relevant to, species distributions. Despite problems with climate-based models, climate and climate-derived variables still have substantial merit for explaining species distribution patterns. Additional generation of relevant climate variables and improvements in other climate and climate-derived variables are still needed to demonstrate this more effectively. Satellite data have a long history of being used for vegetation mapping and even species distribution mapping. They have great potential for being used for additional climatic information, and for improved mapping of other climate and climate-derived variables. Improving the characterization of cloud cover frequency with satellite data is one way in which the mapping of important climate and climate-derived variables can be improved. An important input to water balance models, solar radiation maps could be vastly improved with a better mapping of spatial and temporal patterns in cloud cover. Chapter 2 of this dissertation describes the generation of custom daily cloud cover maps from Advanced Very High Resolution Radiometer (AVHRR) satellite data from 1981-1999 at ~5 km resolution and Moderate Resolution Imagine Spectroradiomter (MODIS) satellite reflectance data at ~500 meter resolution for much of the western U.S., from 2000 to 2012. Intensive comparisons of reflectance spectra from a variety of cloud and snow-covered scenes from the southwestern United States allowed the generation of new rules for the classification of clouds and snow in both the AVHRR and MODIS data. The resulting products avoid many of the problems that plague other cloud mapping efforts, such as the tendency for snow cover and bright desert soils to be mapped as cloud. This consistency in classification across cover types is critically important for any distribution modeling of a plant species that might be dependent on cloud cover. In Chapter 3, monthly cloud frequencies derived from the daily classifications were used directly in species distribution models for giant sequoia and were found to be the strongest predictors of giant sequoia distribution. A high frequency of cloud cover, especially in the spring, differentiated the climate of the west slope of the southern Sierra Nevada, where giant sequoia are prolific, from central and northern parts of the range, where the tree is rare and generally absent. Other mapped cloud products, contaminated by confusion with high elevation snow, would likely not have found this important result. The result illustrates the importance of accuracy in mapping as well as the importance of previously overlooked aspects of climate for species distribution modeling. But it also raises new questions about why the clouds form where they do and whether they might be associated with other aspects of climate important to giant sequoia distribution. What are the exact climatic mechanisms governing the distribution? Detailed aspects of the local climate warranted more investigation. Chapter 4 investigates the climate associated with the frequent cloud formation over the western slopes of the southern Sierra Nevada: the "sequoia belt". This region is climatically distinct in a number of ways, all of which could be factors in influencing the distribution of giant sequoia and other species. Satellite and micrometeorological flux tower data reveal characteristics of the sequoia belt that were not evident with surface climate measurements and maps derived from them. Results have implications for species distributions everywhere, but especially in rugged mountains, where climates are complex and poorly mapped. Chapter 5 summarizes some of the main conclusions from the work and suggests directions for related future research. (Abstract shortened by UMI.).

Functional traits help predict post-disturbance demography of tropical trees.

PubMed

Flores, Olivier; Hérault, Bruno; Delcamp, Matthieu; Garnier, Éric; Gourlet-Fleury, Sylvie

2014-01-01

How tropical tree species respond to disturbance is a central issue of forest ecology, conservation and resource management. We define a hierarchical model to investigate how functional traits measured in control plots relate to the population change rate and to demographic rates for recruitment and mortality after disturbance by logging operations. Population change and demographic rates were quantified on a 12-year period after disturbance and related to seven functional traits measured in control plots. The model was calibrated using a Bayesian Network approach on 53 species surveyed in permanent forest plots (37.5 ha) at Paracou in French Guiana. The network analysis allowed us to highlight both direct and indirect relationships among predictive variables. Overall, 89% of interspecific variability in the population change rate after disturbance were explained by the two demographic rates, the recruitment rate being the most explicative variable. Three direct drivers explained 45% of the variability in recruitment rates, including leaf phosphorus concentration, with a positive effect, and seed size and wood density with negative effects. Mortality rates were explained by interspecific variability in maximum diameter only (25%). Wood density, leaf nitrogen concentration, maximum diameter and seed size were not explained by variables in the analysis and thus appear as independent drivers of post-disturbance demography. Relationships between functional traits and demographic parameters were consistent with results found in undisturbed forests. Functional traits measured in control conditions can thus help predict the fate of tropical tree species after disturbance. Indirect relationships also suggest how different processes interact to mediate species demographic response.

Can Process Understanding Help Elucidate The Structure Of The Critical Zone? Comparing Process-Based Soil Formation Models With Digital Soil Mapping.

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Peña, A.; Laguna, A.; Giráldez, J. V.

2017-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties in the critical zone. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of traditional digital soil mapping versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

Added-values of high spatiotemporal remote sensing data in crop yield estimation

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.

2017-12-01

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing derived parameters have been used for estimating crop yield by using either empirical or crop growth models. The uses of remote sensing vegetation index (VI) in crop yield modeling have been typically evaluated at regional and country scales using coarse spatial resolution (a few hundred to kilo-meters) data or assessed over a small region at field level using moderate resolution spatial resolution data (10-100m). Both data sources have shown great potential in capturing spatial and temporal variability in crop yield. However, the added value of data with both high spatial and temporal resolution data has not been evaluated due to the lack of such data source with routine, global coverage. In recent years, more moderate resolution data have become freely available and data fusion approaches that combine data acquired from different spatial and temporal resolutions have been developed. These make the monitoring crop condition and estimating crop yield at field scale become possible. Here we investigate the added value of the high spatial and temporal VI for describing variability of crop yield. The explanatory ability of crop yield based on high spatial and temporal resolution remote sensing data was evaluated in a rain-fed agricultural area in the U.S. Corn Belt. Results show that the fused Landsat-MODIS (high spatial and temporal) VI explains yield variability better than single data source (Landsat or MODIS alone), with EVI2 performing slightly better than NDVI. The maximum VI describes yield variability better than cumulative VI. Even though VI is effective in explaining yield variability within season, the inter-annual variability is more complex and need additional information (e.g. weather, water use and management). Our findings augment the importance of high spatiotemporal remote sensing data and supports new moderate resolution satellite missions for agricultural applications.

Understanding Coupling of Global and Diffuse Solar Radiation with Climatic Variability

NASA Astrophysics Data System (ADS)

Hamdan, Lubna

Global solar radiation data is very important for wide variety of applications and scientific studies. However, this data is not readily available because of the cost of measuring equipment and the tedious maintenance and calibration requirements. Wide variety of models have been introduced by researchers to estimate and/or predict the global solar radiations and its components (direct and diffuse radiation) using other readily obtainable atmospheric parameters. The goal of this research is to understand the coupling of global and diffuse solar radiation with climatic variability, by investigating the relationships between these radiations and atmospheric parameters. For this purpose, we applied multilinear regression analysis on the data of National Solar Radiation Database 1991--2010 Update. The analysis showed that the main atmospheric parameters that affect the amount of global radiation received on earth's surface are cloud cover and relative humidity. Global radiation correlates negatively with both variables. Linear models are excellent approximations for the relationship between atmospheric parameters and global radiation. A linear model with the predictors total cloud cover, relative humidity, and extraterrestrial radiation is able to explain around 98% of the variability in global radiation. For diffuse radiation, the analysis showed that the main atmospheric parameters that affect the amount received on earth's surface are cloud cover and aerosol optical depth. Diffuse radiation correlates positively with both variables. Linear models are very good approximations for the relationship between atmospheric parameters and diffuse radiation. A linear model with the predictors total cloud cover, aerosol optical depth, and extraterrestrial radiation is able to explain around 91% of the variability in diffuse radiation. Prediction analysis showed that the linear models we fitted were able to predict diffuse radiation with efficiency of test adjusted R2 values equal to 0.93, using the data of total cloud cover, aerosol optical depth, relative humidity and extraterrestrial radiation. However, for prediction purposes, using nonlinear terms or nonlinear models might enhance the prediction of diffuse radiation.

Analysis of the influence of rainfall variables on urban effluents concentrations and fluxes in wet weather

NASA Astrophysics Data System (ADS)

Gooré Bi, Eustache; Monette, Frédéric; Gasperi, Johnny

2015-04-01

Urban rainfall runoff has been a topic of increasing importance over the past years, a result of both the increase in impervious land area arising from constant urban growth and the effects of climate change on urban drainage. The main goal of the present study is to assess and analyze the correlations between rainfall variables and common indicators of urban water quality, namely event mean concentrations (EMCs) and event fluxes (EFs), in order to identify and explain the impacts of each of the main rainfall variables on the generation process of urban pollutants during wet periods. To perform this analysis, runoff from eight summer rainfall events that resulted in combined sewer overflow (CSO) was sampled simultaneously from two distinct catchment areas in order to quantify discharges at the respective outfalls. Pearson statistical analysis of total suspended solids (TSS), chemical oxygen demand (COD), carbonaceous biochemical oxygen demand at 5 days (CBOD5), total phosphorus (Ptot) and total kedjal nitrogen (N-TKN) showed significant correlations (ρ = 0.05) between dry antecedent time (DAT) and EMCs on one hand, and between total rainfall (TR) and the volume discharged (VD) during EFs, on the other. These results show that individual rainfall variables strongly affect either EMCs or EFs and are good predictors to consider when selecting variables for statistical modeling of urban runoff quality. The results also show that in a combined sewer network, there is a linear relationship between TSS event fluxes and COD, CBOD5, Ptot, and N-TKN event fluxes; this explains 97% of the variability of these pollutants which adsorb onto TSS during wet weather, which therefore act as tracers. Consequently, the technological solution selected for TSS removal will also lead to a reduction of these pollutants. Given the huge volumes involved, urban runoffs contribute substantially to pollutant levels in receiving water bodies, a situation which, in a climate change context, may get much worse as a result of more frequent, shorter, but more intense rainfall events.

Thaw depth spatial and temporal variability at the Limnopolar Lake CALM-S site, Byers Peninsula, Livingston Island, Antarctica.

PubMed

de Pablo, M A; Ramos, M; Molina, A; Prieto, M

2018-02-15

A new Circumpolar Active Layer Monitoring (CALM) site was established in 2009 at the Limnopolar Lake watershed in Byers Peninsula, Livingston Island, Antarctica, to provide a node in the western Antarctic Peninsula, one of the regions that recorded the highest air temperature increase in the planet during the last decades. The first detailed analysis of the temporal and spatial evolution of the thaw depth at the Limnopolar Lake CALM-S site is presented here, after eight years of monitoring. The average values range between 48 and 29cm, decreasing at a ratio of 16cm/decade. The annual thaw depth observations in the 100×100 m CALM grid are variable (Variability Index of 34 to 51%), although both the Variance Coefficient and the Climate Matrix Analysis Residual point to the internal consistency of the data. Those differences could be explained then by the terrain complexity and node-specific variability due to the ground properties. The interannual variability was about 60% during 2009-2012, increasing to 124% due to the presence of snow in 2013, 2015 and 2016. The snow has been proposed here as one of the most important factors controlling the spatial variability of ground thaw depth, since its values correlate with the snow thickness but also with the ground surface temperature and unconfined compression resistance, as measured in 2010. The topography explains the thaw depth spatial distribution pattern, being related to snowmelt water and its accumulation in low-elevation areas (downslope-flow). Patterned grounds and other surface features correlate well with high thaw depth patterns as well. The edaphic factor (E=0.05842m 2 /°C·day; R 2 =0.63) is in agreement with other permafrost environments, since frozen index (F>0.67) and MAAT (<-2°C) denote a continuous permafrost existence in the area. All these characteristics provided the basis for further comparative analyses between others nearby CALM sites. Copyright © 2017 Elsevier B.V. All rights reserved.

Characterizing individual differences in functional connectivity using dual-regression and seed-based approaches.

PubMed

Smith, David V; Utevsky, Amanda V; Bland, Amy R; Clement, Nathan; Clithero, John A; Harsch, Anne E W; McKell Carter, R; Huettel, Scott A

2014-07-15

A central challenge for neuroscience lies in relating inter-individual variability to the functional properties of specific brain regions. Yet, considerable variability exists in the connectivity patterns between different brain areas, potentially producing reliable group differences. Using sex differences as a motivating example, we examined two separate resting-state datasets comprising a total of 188 human participants. Both datasets were decomposed into resting-state networks (RSNs) using a probabilistic spatial independent component analysis (ICA). We estimated voxel-wise functional connectivity with these networks using a dual-regression analysis, which characterizes the participant-level spatiotemporal dynamics of each network while controlling for (via multiple regression) the influence of other networks and sources of variability. We found that males and females exhibit distinct patterns of connectivity with multiple RSNs, including both visual and auditory networks and the right frontal-parietal network. These results replicated across both datasets and were not explained by differences in head motion, data quality, brain volume, cortisol levels, or testosterone levels. Importantly, we also demonstrate that dual-regression functional connectivity is better at detecting inter-individual variability than traditional seed-based functional connectivity approaches. Our findings characterize robust-yet frequently ignored-neural differences between males and females, pointing to the necessity of controlling for sex in neuroscience studies of individual differences. Moreover, our results highlight the importance of employing network-based models to study variability in functional connectivity. Copyright © 2014 Elsevier Inc. All rights reserved.

Jamaica Bay studies III: Abiotic determinants of distribution and abundance of gulls ( Larus)

NASA Astrophysics Data System (ADS)

Burger, Joanna

1983-02-01

The distribution and abundance of gulls were examined at Jamaica Bay Wildlife Refuge (New York) from 31 May 1978 to 31 May 1979. Gulls were found to be affected by tidal, temporal and weather-related factors. The distribution of gulls was affected primarily by tidal factors on the bay, and by temporal (seasonal, circadian) and weather-related factors on the freshwater ponds. The most important weather-related factors were temperature, wind velocity and wind direction. Herring ( L. argentatus), great black-backed ( L. fuscus) and ring-billed gulls ( L. delawarensis) fed on the bay at low tides, and used the ponds at high tide. Laughing gulls ( L. atricilla) fed on the bay at low tide and on rising tides. Herring and great black-backed gulls were present all year, but were most abundant in the winter, ring-billed gulls were abundant in spring and early fall, and laughing gulls were present in the summer following the breeding season but were absent in winter. Gulls used the ponds during high velocity, north winds, when they usually rested or preened. Multiple regression models were used to determine the factors explaining the variability in the numbers of gulls. Temporal variables were important contributors to accounting for the variability in the numbers of great black-backed and herring gulls only; tidal variables were significant for great black-backed and herring gulls on the bay, and for ring-billed and laughing gulls on all areas; and weather variables were significant for all species.

[Adjustment of the Andersen's model to the Mexican context: access to prenatal care].

PubMed

Tamez-González, Silvia; Valle-Arcos, Rosa Irene; Eibenschutz-Hartman, Catalina; Méndez-Ramírez, Ignacio

2006-01-01

The aim of this work was to propose an adjustment to the Model of Andersen who answers better to the social inequality of the population in the Mexico City and allows to evaluate the effect of socioeconomic factors in the access to the prenatal care of a sample stratified according to degree of marginalization. The data come from a study of 663 women, randomly selected from a framework sample of 21,421 homes in Mexico City. This work collects information about factors that affect utilization of health services, as well as predisposing factors (age and socioeconomic level), as enabling factors (education, social support, entitlement, pay out of pocket and opinion of health services), and need factors. The sample was ranked according to exclusion variables into three stratums. The data were analyzed through the technique of path analysis. The results indicate that socioeconomic level takes part like predisposed variable for utilization of prenatal care services into three stratums. Otherwise, education and social support were the most important enabling variables for utilization of prenatal care services in the same three groups. In regard to low stratum, the most important enabling variables were education and entitlement. For high stratum the principal enabling variables were pay out of pocket and social support. The medium stratum shows atypical behavior which it was difficult to explain and understand. There was not mediating role with need variable in three models. This indicated absence of equality in all stratums. However, the most correlations in high stratum perhaps indicate less inequitable conditions regarding other stratums.

Interannual and seasonal variability of winter-spring cohort of neon flying squid abundance in the Northwest Pacific Ocean during 1995-2011

NASA Astrophysics Data System (ADS)

Yu, Wei; Chen, Xinjun; Yi, Qian

2016-06-01

The neon flying squid, Ommastrephes bartramii, is a species of economically important cephalopod in the Northwest Pacific Ocean. Its short lifespan increases the susceptibility of the distribution and abundance to the direct impact of the environmental conditions. Based on the generalized linear model (GLM) and generalized additive model (GAM), the commercial fishery data from the Chinese squid-jigging fleets during 1995 to 2011 were used to examine the interannual and seasonal variability in the abundance of O. bartramii, and to evaluate the influences of variables on the abundance (catch per unit effort, CPUE). The results from GLM suggested that year, month, latitude, sea surface temperature (SST), mixed layer depth (MLD), and the interaction term ( SST×MLD) were significant factors. The optimal model based on GAM included all the six significant variables and could explain 42.43% of the variance in nominal CPUE. The importance of the six variables was ranked by decreasing magnitude: year, month, latitude, SST, MLD and SST×MLD. The squid was mainly distributed in the waters between 40°N and 44°N in the Northwest Pacific Ocean. The optimal ranges of SST and MLD were from 14 to 20°C and from 10 to 30 m, respectively. The squid abundance greatly fluctuated from 1995 to 2011. The CPUE was low during 1995-2002 and high during 2003-2008. Furthermore, the squid abundance was typically high in August. The interannual and seasonal variabilities in the squid abundance were associated with the variations of marine environmental conditions and the life history characteristics of squid.

Neuroticism Combined With Slower and More Variable Reaction Time: Synergistic Risk Factors for 7-Year Cognitive Decline in Females

PubMed Central

Shickle, Darren A.; Roberts, Beverly A.; Deary, Ian J.

2012-01-01

Objective. Among adults, slower and more variable reaction times are associated with worse cognitive function and increased mortality risk. Therefore, it is important to elucidate risk factors for reaction time change over the life course. Method. Data from the Health and Lifestyle Survey (HALS) were used to examine predictors of 7-year decline in reaction time (N = 4,260). Regression-derived factor scores were used to summarize general change across 4 reaction time variables: simple mean, 4-choice mean, simple variability, and 4-choice variability (53.52% of variance). Results. Age (B = .02, p < .001) and HALS1 baseline reaction time (B = −.10, p = .001) were significant risk factors for males (N = 1,899). In addition to these variables, in females (N = 2,361), neuroticism was significant and interacted synergistically with baseline reaction time (B = .06, p = .04). Adjustment for physiological variables explained the interaction with neuroticism, suggesting that candidate mechanisms had been identified. Discussion. A priority for future research is to replicate interactions between personality and reaction time in other samples and find specific mechanisms. Stratification of population data on cognitive health by personality and reaction time could improve strategies for identifying those at greater risk of cognitive decline. PMID:22367712

Qualitatively Assessing Randomness in SVD Results

NASA Astrophysics Data System (ADS)

Lamb, K. W.; Miller, W. P.; Kalra, A.; Anderson, S.; Rodriguez, A.

2012-12-01

Singular Value Decomposition (SVD) is a powerful tool for identifying regions of significant co-variability between two spatially distributed datasets. SVD has been widely used in atmospheric research to define relationships between sea surface temperatures, geopotential height, wind, precipitation and streamflow data for myriad regions across the globe. A typical application for SVD is to identify leading climate drivers (as observed in the wind or pressure data) for a particular hydrologic response variable such as precipitation, streamflow, or soil moisture. One can also investigate the lagged relationship between a climate variable and the hydrologic response variable using SVD. When performing these studies it is important to limit the spatial bounds of the climate variable to reduce the chance of random co-variance relationships being identified. On the other hand, a climate region that is too small may ignore climate signals which have more than a statistical relationship to a hydrologic response variable. The proposed research seeks to identify a qualitative method of identifying random co-variability relationships between two data sets. The research identifies the heterogeneous correlation maps from several past results and compares these results with correlation maps produced using purely random and quasi-random climate data. The comparison identifies a methodology to determine if a particular region on a correlation map may be explained by a physical mechanism or is simply statistical chance.

Statistically extracted fundamental watershed variables for estimating the loads of total nitrogen in small streams

USGS Publications Warehouse

Kronholm, Scott C.; Capel, Paul D.; Terziotti, Silvia

2016-01-01

Accurate estimation of total nitrogen loads is essential for evaluating conditions in the aquatic environment. Extrapolation of estimates beyond measured streams will greatly expand our understanding of total nitrogen loading to streams. Recursive partitioning and random forest regression were used to assess 85 geospatial, environmental, and watershed variables across 636 small (<585 km2) watersheds to determine which variables are fundamentally important to the estimation of annual loads of total nitrogen. Initial analysis led to the splitting of watersheds into three groups based on predominant land use (agricultural, developed, and undeveloped). Nitrogen application, agricultural and developed land area, and impervious or developed land in the 100-m stream buffer were commonly extracted variables by both recursive partitioning and random forest regression. A series of multiple linear regression equations utilizing the extracted variables were created and applied to the watersheds. As few as three variables explained as much as 76 % of the variability in total nitrogen loads for watersheds with predominantly agricultural land use. Catchment-scale national maps were generated to visualize the total nitrogen loads and yields across the USA. The estimates provided by these models can inform water managers and help identify areas where more in-depth monitoring may be beneficial.

Evaluation of the satellite derived snow cover area - Runoff forecasting models for the inaccessible basins of western Himalayas

NASA Technical Reports Server (NTRS)

Dey, B.

1985-01-01

In this study, the existing seasonal snow cover area runoff forecasting models of the Indus, Kabul, Sutlej and Chenab basins were evaluated with the concurrent flow correlation model for the period 1975-79. In all the basins under study, correlation of concurrent flow model explained the variability in flow better than by the snow cover area runoff models. Actually, the concurrent flow correlation model explained more than 90 percent of the variability in the flow of these rivers. Compared to this model, the snow cover area runoff models explained less of the variability in flow. In the Himalayan river basins under study and at least for the period under observation, the concurrent flow correlation model provided a set of results with which to compare the estimates from the snow cover area runoff models.

Explaining the sense of family coherence among husbands and wives: the Israeli case.

PubMed

Kulik, Liat

2009-12-01

This study examined variables belonging to the family environment that explain the sense of family coherence among husbands (n = 133) and wives (n = 133) in Israel. Specifically, the explanatory variables tested were spousal power relations (as expressed in equality in the division of household labor and decision making), and perceived family conflict. In general, the sense of family coherence among spouses was found to be high. Perceived family conflict contributed to explaining the sense of family coherence for both husbands and wives. Equality in the division of household labor and in decision making had a greater impact on husbands than wives. Family coherence correlated negatively with age for husbands and positively with income for wives. The explanatory variables had a greater impact on the sense of family coherence among husbands than among wives.

Natural gas projects in the developing world: An empirical evaluation of merits, obstacles, and risks

NASA Astrophysics Data System (ADS)

Mor, Amit

Significant amounts of natural gas have been discovered in developing countries throughout the years during the course of oil exploration. The vast majority of these resources have not been utilized. Some developing countries may benefit from a carefully planned utilization of their indigenous resources, which can either be exported or used domestically to substitute imported or exportable fuels or feedstock. Governments, potential private sector investors, and financiers have been searching for strategies to promote natural gas schemes, some of which have been in the pipeline for more than two decades. The purpose of this thesis is to identify the crucial factors determining the success or failure of launching natural gas projects in the developing world. The methodology used to evaluate these questions included: (1) establishing a representative sample of natural gas projects in developing countries that were either implemented or failed to materialize during the 1980-1995 period, (2) utilizing a Probit limited dependent variable econometric model in which the explained variable is project success or failure, and (3) choosing representing indicators to reflect the assumed factors affecting project success. The study identified two conditions for project success: (1) the economic viability of the project and (2) securing financing for the investment. The factors that explain the ability or inability of the sponsors to secure financing were: (1) the volume of investment that represented the large capital costs of gas transportation, distribution, and storage, (2) the level of foreign exchange constraint in the host country, and (3) the level of development of the country. The conditions for private sector participation in natural gas projects in developing countries were identified in the study by a Probit model in which the explained variable was private sector participation. The results showed that a critical condition for private sector participation is the financial profitability of a project. Other factors that explained private sector participation and the ability of the private-sector sponsor to secure financing for a project were: (1) the political risk associated with the project, (2) the foreign exchange constraint associated with the project, and (3) whether the project was domestic or export-oriented.

Semi-arid vegetation response to antecedent climate and water balance windows

USGS Publications Warehouse

Thoma, David P.; Munson, Seth M.; Irvine, Kathryn M.; Witwicki, Dana L.; Bunting, Erin

2016-01-01

Questions Can we improve understanding of vegetation response to water availability on monthly time scales in semi-arid environments using remote sensing methods? What climatic or water balance variables and antecedent windows of time associated with these variables best relate to the condition of vegetation? Can we develop credible near-term forecasts from climate data that can be used to prepare for future climate change effects on vegetation? Location Semi-arid grasslands in Capitol Reef National Park, Utah, USA. Methods We built vegetation response models by relating the normalized difference vegetation index (NDVI) from MODIS imagery in Mar–Nov 2000–2013 to antecedent climate and water balance variables preceding the monthly NDVI observations. We compared how climate and water balance variables explained vegetation greenness and then used a multi-model ensemble of climate and water balance models to forecast monthly NDVI for three holdout years. Results Water balance variables explained vegetation greenness to a greater degree than climate variables for most growing season months. Seasonally important variables included measures of antecedent water input and storage in spring, switching to indicators of drought, input or use in summer, followed by antecedent moisture availability in autumn. In spite of similar climates, there was evidence the grazed grassland showed a response to drying conditions 1 mo sooner than the ungrazed grassland. Lead times were generally short early in the growing season and antecedent window durations increased from 3 mo early in the growing season to 1 yr or more as the growing season progressed. Forecast accuracy for three holdout years using a multi-model ensemble of climate and water balance variables outperformed forecasts made with a naïve NDVI climatology. Conclusions We determined the influence of climate and water balance on vegetation at a fine temporal scale, which presents an opportunity to forecast vegetation response with short lead times. This understanding was obtained through high-frequency vegetation monitoring using remote sensing, which reduces the costs and time necessary for field measurements and can lead to more rapid detection of vegetation changes that could help managers take appropriate actions.