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In mammals, trait variation is often reported to be greater among males than females. However, to date, mainly only morphological traits have been studied. Energy expenditure represents the metabolic costs of multiple physical, physiological, and behavioral traits. Energy expenditure could exhibit particularly high greater male variation through a cumulative effect if those traits mostly exhibit greater male variation, or a lack of greater male variation if many of them do not. Sex differences in energy expenditure variation have been little explored. We analyzed a large database on energy expenditure in adult humans (1494 males and 3108 females) to investigate whether humans have evolved sex differences in the degree of interindividual variation in energy expenditure. We found that, even when statistically comparing males and females of the same age, height, and body composition, there is much more variation in total, activity, and basal energy expenditure among males. However, with aging, variation in total energy expenditure decreases, and because this happens more rapidly in males, the magnitude of greater male variation, though still large, is attenuated in older age groups. Considerably greater male variation in both total and activity energy expenditure could be explained by greater male variation in levels of daily activity. The considerably greater male variation in basal energy expenditure is remarkable and may be explained, at least in part, by greater male variation in the size of energy-demanding organs. If energy expenditure is a trait that is of indirect interest to females when choosing a sexual partner, this would suggest that energy expenditure is under sexual selection. However, we present a novel energetics model demonstrating that it is also possible that females have been under stabilizing selection pressure for an intermediate basal energy expenditure to maximize energy available for reproduction. [ABSTRACT FROM AUTHOR]

Abstract: Both aboveground and belowground processes play important roles in tree-grass interactions in savannas. Little consideration has been given to within-site heterogeneity in the strengths of co-occurring canopy and root effects of trees on grasses in savanna communities. Here, we attempted to correlate the spatial pattern of grass morphological traits with the strengths of canopy and root effects. The results from a spatial analysis suggested that the grass traits had lower variability within the operating domain of the root effect than within that of the canopy effect in sub-canopy areas; in contrast, the operating domain of the root effect presented higher variability of grass traits than that of the canopy effect in inter-canopy areas. Combined with root investigations on vertical distribution patterns, these results suggested that the root effect appeared to outweigh the canopy effect in the sub-canopy areas, where apparent vertical root separation between trees and grasses was shown; while the canopy effect could outweigh the root effect in the inter-canopy areas, where root separation was not observed. This study could provide correlative information on the relative importance of canopy and root effects, and has some useful implications on within-site heterogeneity in terms of aboveground and belowground components in savannas. [Copyright &y& Elsevier]

Abstract: This study used daily diary data to model trait and state Positive Affect (PA) and Negative Affect (NA) using the Positive and Negative Affect Schedule (PANAS; ). Data were collected from 364 college students over five days. Intraclass correlation coefficients suggested approximately equal amounts of variability at the trait and state levels. Multilevel factor analysis revealed that the model specifying two correlated factors (PA, NA) and correlated uniqueness terms among redundant items provided the best fit. Trait and state PA and NA were generally associated with stress, anxiety, depression, and three types of self-esteem (performance, academic, social). The coefficients describing these relationships differed somewhat, suggesting that trait and state measurement may have different predictive utility. [Copyright &y& Elsevier]