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Objectives This investigation was conducted to determine whether contesting orientations add predictive utility for prosocial behavior, both in and out of sports, beyond other variables related to the component processes of moral action. Design Cross-sectional. Methods Intercollegiate US athletes (n = 2380; 56.4% male), from both individual and team sports, completed measures of contesting orientation, three moral variables (moral attentiveness, moral identity, integrity), three sport-specific variables (athletic identity, goal orientation, and fear of failure), and three outcome variables (sportspersonship, academic honesty, and prosocial helping). Data was analyzed using both correlational and regression analyses. Results Regression analyses demonstrated that contesting orientations were the best predictors of sportspersonship, but were insignificant predictors of nonsport forms of prosocial behavior. Conclusions Consistent with contesting theory, contesting orientation are salient and potent predictors of sportspersonship, but do not predict behavior outside of contest situations. [ABSTRACT FROM AUTHOR]

Objectives To examine the factorial validity of the Contesting Orientations Scale (COS) in a large sample of intercollegiate student-athletes, as well as to extend evidence of the COS’ concurrent validity by examining its relationship to autonomous and controlled motivations in sport. The ability of contesting orientations to predict sportspersonship over and above autonomous and controlled motivations was also examined. Design Cross-sectional and correlational. Methods Five hundred and forty-four intercollegiate US athletes (57.2% male) from individual and team sports completed measures of contesting orientations, autonomous and controlled motivations, and sportspersonship. Results Confirmatory factor analysis (CFA) supported the factorial validity of the COS, while correlational results supported its concurrent construct validity, with autonomous motivation associated with higher levels of partnership orientation and controlled motivation associated with higher levels of war orientation. In addition, sequential regression analyses supported the predictive utility of contesting orientations, with partnership orientation emerging as a significant positive predictor of four – and war orientation a negative predictor of three – dimensions of sportspersonship. Mediation analyses suggested that contesting orientations may partially mediate the relationship between autonomous and controlled motivations for some dimensions of sportspersonship. Conclusions The COS is a valid and reliable measure of contesting orientations. Partnership and war contesting orientations, moreover, add significantly to the prediction of sportspersonship over and above autonomous and controlled motivations. In practice, if the goal is to promote good sportspersonship, coaches and other adults involved in competitive sport should emphasize a partnership contesting orientation in addition to more autonomous forms of motivation. [ABSTRACT FROM AUTHOR]

Objective This three-study investigation was undertaken to develop, validate, and test the Contesting Orientations Scale (COS), a new measure designed to assess individuals' tendencies to use contest-is-partnership and contest-is-war conceptual metaphors (i.e., contesting orientations) when competing (Shields & Bredemeier, 2009, 2011a). Design The research design was correlational. Following preliminary item creation and expert review, survey based studies were conducted to develop theoretically-based, psychometrically sound scales measuring contesting orientations. Method In Study 1, an exploratory factor analysis (EFA) was performed on a preliminary 39-item COS administered to a sample of high school athletes (N = 233). Study 2 used EFA to evaluate a revised 23- item COS with a second sample of high school athletes (N = 92) resulting in a final reduction of the measure to twelve items. Confirmatory factor analysis (CFA) was then conducted on this 12-item COS, which proved an excellent fit to the data. A new sample of college athletes (N = 238) allowed Study 3 to (a) further examine the factorial validity of the COS, including gender invariance testing, (b) assess the concurrent validity of the COS via its correlations with goal orientations, empathy, moral identity, and moral disengagement; and, (c) assess the COS's incremental predictive utility for investigations of sportspersonship. Results and conclusion Results from the sequence of studies demonstrate that the 12-item, two-scale COS has good psychometric properties as assessed through EFA and CFA, good concurrent validity, and adds significantly to existing measures in the prediction of sportspersonship. [ABSTRACT FROM AUTHOR]

Abstract Despite advances in drought early warning systems, forecast information is rarely used for triggering and financing early actions, such as cash transfer. Scaling up cash transfer pay-outs, and overcoming the barriers to actions based on forecasts, requires an understanding of costs resulting from False Alarms, and the potential benefits associated with appropriate early interventions. On this study, we evaluate the potential cost-effectiveness of cash transfer responses, comparing the relative costs of ex-ante cash transfers during the maize growing season to ex-post cash transfers after harvesting in Kenya. For that, we developed a forecast model using Fast-and Frugal Trees that unravels early warning relationships between climate variability, vegetation coverage, and maize yields at multiple lead times. Results indicate that our models correctly forecast low maize yield events 85% of the time across the districts studied, some already six months before harvesting. The models' performance improves towards the end of the growing season driven by a decrease of 29% in the probability of False Alarms. Overall, we show that timely cash transfers ex-ante to a disaster can often be more cost-effective than investing in ex-post expenditures. Our findings suggest that early response can yield significant cost savings, and can potentially increase the effectiveness of existing cash transfer systems. Graphical abstract Unlabelled Image Highlights • Drought early warning systems are rarely used for triggering early actions, such as cash transfer. • We evaluate the cost-effectiveness of cash transfers ex-ante (forecast-based) and ex-post. • We developed a forecast model using Machine Learning named Fast-and-Frugal Trees. • We show that our models predict the majority of the low maize yield events in all districts studied. • Our results indicate that cash transfers ex-ante can often be more cost-effective than ex-post. [ABSTRACT FROM AUTHOR]

Atmospheric methane has been increasing since the beginning of the industrial era due to anthropogenic emissions. Methane has many sources, both natural and anthropogenic, and there continues to be considerable uncertainty regarding the contribution of each source to the total methane budget. Thus, remote sensing techniques for monitoring and measuring methane emissions are of increasing interest. Recently, the Airborne Visible-Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG) has proven to be a valuable instrument for quantitative mapping of methane plumes. Despite this success, uncertainties remain regarding the sensitivity of the retrieval algorithms, including the influence of albedo and the impact of surfaces that may cause spurious signals. To explore these sensitivities, we applied the Iterative Maximum a Posterior Differential Optical Absorption Spectroscopy (IMAP-DOAS) methane retrieval algorithm to synthetic reflected radiances with variable methane concentrations, albedo, surface cover, and aerosols. This allowed for characterizing retrieval performance, including potential sensitivity to variable surfaces, low albedo surfaces, and surfaces known to cause spurious signals. We found that dark surfaces (below 0.10 μWcm −2 nm −1 sr −1 at 2139 nm), such as water and green vegetation, and materials with absorption features in the 2200–2400 nm range caused higher errors in retrieval results. We also found that aerosols have little influence on retrievals in the SWIR. Results from the synthetic scene are consistent with those observed in IMAP-DOAS retrievals for real AVIRIS-NG scenes containing methane plumes from a waste dairy lagoon and coal mine ventilation shafts. Understanding the effect of surface properties on methane retrievals is important given the increased use of AVIRIS-NG to map gas plumes from a diversity of sources over variable landscapes. [ABSTRACT FROM AUTHOR]

Rapidly expanding global trade in the past three decades has lifted millions out of people out of poverty. Trade has also reduced manufacturing wages in high income countries and made entire industries uncompetitive in some communities, giving rise to nationalist politics that seek to stop or reverse further trade expansion in the United States and Europe. Given complex and uncertain political support for trade, how might changes in trade policy affect the global food system’s ability to adapt to climate change? Here we argue that we can best understand food security in a changing climate as a double exposure: the exposure of people and processes to both economic and climate-related shocks and stressors. Trade can help us adapt to climate change, or not. If trade restrictions proliferate, double exposure to both a rapidly changing climate and volatile markets will likely jeopardize the food security of millions. A changing climate will present both opportunities and challenges for the global food system, and adapting to its many impacts will affect food availability, food access, food utilization and food security stability for the poorest people across the world. Global trade can continue to play a central role in assuring that global food system adapts to a changing climate. This potential will only be realized, however, if trade is managed in ways that maximize the benefits of broadened access to new markets while minimizing the risks of increased exposure to international competition and market volatility. For regions like Africa, for example, enhanced transportation networks combined with greater national reserves of cash and enhanced social safety nets could reduce the impact of ‘double exposure’ on food security. [ABSTRACT FROM AUTHOR]

Abstract: Carbon dioxide is emitted from the combustion of fossil fuels and is an important contributor to anthropogenic climate change. Multiple current and planned satellite missions are designed to quantify atmospheric carbon dioxide concentrations on a global scale, but most of these sensors do not have the spatial resolution necessary to resolve point sources such as fossil fuel power plants. Airborne imaging spectrometer data, such as those from the Airborne Visible InfraRed Imaging Spectrometer (AVIRIS), can have multiple, contiguous bands covering shortwave infrared (SWIR) absorption features produced by carbon dioxide. Therefore, high spatial resolution data from AVIRIS-like sensors may offer a means for detecting plumes and retrieving carbon dioxide concentrations for point source emissions. The objectives of this study include modeling minimum carbon dioxide anomalies detectable in AVIRIS data under different conditions and applying a Cluster-Tuned Matched Filter for detection of carbon dioxide plumes in simulated data and in AVIRIS images acquired over power plants. Radiative transfer simulations were used to model the residual radiance produced by increased absorption by carbon dioxide as concentration was elevated above background levels within a 0–500m layer. Carbon dioxide anomalies, surface reflectance, water vapor concentration, solar zenith angle, sensor height, and aerosol scattering were varied in simulation sets and the resulting residual radiance spectra were compared against noise equivalent delta radiance (NEdL) for the “classic” and “next generation” AVIRIS instruments. Sensitivity to carbon dioxide anomalies improved with increased surface reflectance and declined with increased water vapor concentration, solar zenith angle, sensor height, and aerosol scattering. Zero to 500m concentration anomalies as low as 100 parts per milion by volume (ppm) for AVIRIS C and 25ppm for AVIRIS NG produced residual radiance values that exceeded SWIR NEdL. Carbon dioxide concentrations modeled for a generic power plant emissions scenario using a plume dispersion model were combined with randomly-generated reflectance spectra to create simulated images with varying surface reflectance and NEdL. For these simulated images, true positive and false positive detection rates improved as background reflectance increased and as NEdL decreased. Apparent plumes were detected in all four AVIRIS C images acquired over power plants, although the characteristics of the plumes varied according to solar-plume-sensor geometry. Improvements in modeling may allow retrieval of plume concentration, providing a valuable means for quantifying point source emissions and a basis for comparison with column concentrations retrieved from in situ measurements and coarse resolution satellite data. [Copyright &y& Elsevier]

Abstract: In this study, a Cluster-Tuned Matched Filter (CTMF) technique was applied to data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over marine and terrestrial locations known to emit methane (CH4). At the Coal Oil Point marine seep field, prominent CH4 anomalies were consistent with advection from known areas of active seepage. For a region with natural CH4 and oil seepage located west of downtown Los Angeles, significant CH4 anomalies were identified for known sources at the La Brea Tar Pits and in close proximity to probable sources, including an office complex documented as venting CH4 continuously and hydrocarbon storage tanks on the Inglewood Oil Field. However, interpretation of anomalies was complicated by noise and false positives for surfaces with strong absorptions at the same wavelengths as CH4 absorption features. Segmentation of results identified 16 distinct locations of contiguous pixels with high CTMF scores and segments were classified into probable CH4 anomalies and confusers based on the spectral properties of the underlying surface over the full spectral range measured by AVIRIS. This technique is particularly well suited for application over large areas to detect CH4 emissions from concentrated point sources and should permit detection of additional trace gasses with distinct absorption features, including carbon dioxide (CO2) and nitrous oxide (N2O). Thus, imaging spectrometry by an AVIRIS-like sensor has the potential to improve high resolution greenhouse gas mapping, better constraining local sources. [Copyright &y& Elsevier]