On passion and moral behavior in achievement settings: The mediating role of pride

The Dualistic Model of Passion (Vallerand et al., 2003) distinguishes two types of passion: harmonious passion (HP) and obsessive passion (OP) that predict adaptive and less adaptive outcomes, respectively. In the present research, we were interested in understanding the role of passion in the adoption of moral behavior in achievement settings. It was predicted that the two facets of pride (authentic and hubristic; Tracy & Robins, 2007) would mediate the passion-moral behavior relationship. Specifically, because people who are passionate about a given activity are highly involved in it, it was postulated that they should typically do well and thus experience high levels of pride when engaged in the activity. However, it was also hypothesized that while both types of passion should be conducive to authentic pride, only OP should lead to hubristic pride. Finally, in line with past research on pride (Carver, Sinclair, & Johnson, 2010; Tracy et al., 2009), only hubristic pride was expected to negatively predict moral behavior, while authentic pride was expected to positively predict moral behavior. Results of two studies conducted with paintball players (N=163, Study 1) and athletes (N=296, Study 2) supported the proposed model. Future research directions are discussed in light of the Dualistic Model of Passion

Climatic controls on C4 grassland distributions during the Neogene: A model-data comparison

Grasslands dominated by taxa using the C4photosynthetic pathway first developed on several continents during the Neogene and Quaternary, long after C4photosynthesis first evolved among grasses. The histories of these ecosystems are relatively well-documented in the geological record from stable carbon isotope measurements (of fossil vertebrate herbivores and paleosols) and the plant microfossil record (pollen and/or phytolith assemblages). The distinct biogeography and ecophysiology of modern C3and C4grasses have led to hypotheses explaining the origins of C4grasslands in terms of long-term changes in the Earth system, such as increased aridity and decreasing atmospheric pCO2. However, quantitative proxies for key abiotic drivers of these hypotheses (e.g., temperature, precipitation, pCO2) are still in development, not yet widely applied at the continental or global scale or throughout the late Cenozoic, and/or remain contentious. Testing these hypotheses globally therefore remains difficult. To understand better the potential links between changes in the Earth system and the origin of C4grasslands, we undertook a global-scale comparison between observational records of C4plant abundances in Miocene and Pliocene localities compiled from the literature and three increasingly complex models of C4physiology, dominance, and abundance. The literature compilation comprises > 2,600 δ13C-values each of fossil terrestrial vertebrates and of paleosol carbonates, which we interpret as primarily proxies for the abundance of C4grasses, based on the modern contribution of C4grasses to terrestrial net primary productivity. We forced the vegetation models with simulated monthly climates from the HadCM3 family of coupled ocean-atmosphere general circulation models (OAGCMs) over a range of pCO2-values for each epoch to model C4dominance or abundance in grid cells as: (1) months per year exceeding the temperature at which net carbon assimilation is greater for C4than C3photosynthesis (crossover temperature model); (2) the number of months per year exceeding the crossover temperature and having sufficient precipitation for growth (≥25 mm/month; Collatz model); and (3) the Sheffield Dynamic Global Vegetation Model (SDGVM), which models multiple plant functional types (PFTs) (C3and C4grasses, evergreen, and deciduous trees). Model-data agreement is generally weak, although statistically significant for many comparisons, suggesting that regional to local ecological interactions, continent-specific plant evolutionary histories, and/or regional to local climatic conditions not represented in global scale OAGCMs may have been equally strong or stronger in driving the evolution of C4grasslands as global changes in the Earth system such as decreases in atmospheric pCO2and late Cenozoic global cooling and/or aridification

Loneliness and social media: A qualitative investigation of young people's motivations for use and perceptions of social networking sites

The democratisation of Internet access has incrementally changed every domain of activity and has created new business and economic models. From answering work emails to learning a new language, shopping, booking medical appointments or managing one’s finances, almost everything is attainable at the click of a button. The added implications of the rapid rise of social networking websites (SNSs), such as Facebook, Twitter, Instagram or Snapchat, have further contributed to changing the way we communicate and build new friendships. Indeed most of our social relationships are now being ‘increasingly developed and maintained online’ (Nowland, Necka & Cacioppo, 2017: 1). Ostensibly, despite improved Internet access and enhanced social connectedness, modern societies are struggling to combat loneliness. It is reported to affect people of all ages, especially young adults (16-24 and 25-34 years old) who are avid Internet and social media users (see Office for National Statistics, 2018)

The birds of the Sage West China Expedition. American Museum novitates ; no. 966

17 p. ; 24 cm.Includes bibliographical references

Retrieval of Vertical LAI Profiles Over Tropical Rain Forests using Waveform Lidar at La Selva, Costa Rica

This study explores the potential of waveform lidar in mapping the vertical and spatial distributions of leaf area index (LAI) over the tropical rain forest of La Selva Biological Station in Costa Rica. Vertical profiles of LAI were derived at 0.3 m height intervals from the Laser Vegetation Imaging Sensor (LVIS) data using the Geometric Optical and Radiative Transfer (GORT) model. Cumulative LAI profiles obtained from LVIS were validated with data from 55 ground to canopy vertical transects using a modular field tower to destructively sample all vegetation. Our results showed moderate agreement between lidar and field derived LAI (r2=0.42, RMSE=1.91, bias=0.32), which further improved when differences between lidar and tower footprint scales (r2=0.50, RMSE=1.79, bias=0.27) and distance of field tower from lidar footprint center (r2=0.63, RMSE=1.36, bias=0.0) were accounted for. Next, we mapped the spatial distribution of total LAI across the landscape and analyzed LAI variations over different land cover types. Mean values of total LAI were 1.74, 5.20, 5.41 and 5.62 over open pasture, secondary forests, regeneration forests after selective-logging and old-growth forests respectively. Lastly, we evaluated the sensitivities of our LAI retrieval model to variations in canopy/ground reflectance ratio and to waveform noise such as induced by topographic slopes. We found for both, that the effects were not significant for moderate LAI values (about 4). However model derivations of LAI might be inaccurate in areas of high-slope and high LAI (about 8) if ground return energies are low. This research suggests that large footprint waveform lidar can provide accurate vertical LAI profile estimates that do not saturate even at the high LAI levels in tropical rain forests and may be a useful tool for understanding the light transmittance within these canopies

A 50-m forest cover map in Southeast Asia from ALOS/PALSAR and its application on forest fragmentation assessment.

Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×10(6) km(2) (GlobCover) to 2.69×10(6) km(2) (MCD12Q1) in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%). The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+) implementation, and biodiversity