We examine the Holocene loess record in the Heye Catchment on the margins of the Tibetan Plateau (TP) and China Loess Plateau (CLP) to determine: the region to which the Heye Catchment climate is more similar; temporal change in wind strength; and modification of the loess record by mass wasting and human activity. Luminescence and radiocarbon dating demonstrate loess deposited in two periods: >11–8.6 ka and <5.1 ka. The 8.6–5.1 ka depositional hiatus, which coincides with the Mid-Holocene Climatic Optimum, is more similar to the loess deposition cessation in the TP than to the loess deposition deceleration in the CLP. Grain-size analysis suggests the Heye loess is a mixture of at least three different grain-size distributions and that it may derive from multiple sources. A greater proportion of coarse sediments in the older loess may indicate stronger winds compared with the more recent depositional period. Gravel incorporated into younger loess most likely comes from bedrock exposed in slump scarps. Human occupation of the catchment, for which the earliest evidence is 3.4 ka, postdates the onset of slumping; thus the slumps may have created a livable environment for humans.

Seed production from weeds that are missed by herbicide application can affect future weed populations and management decisions. It may be possible to expand the utility of computerized weed management decision aids to include an estimate of weed seed production resulting from selected treatments based on crop yield potential. Field studies were conducted in soybean near Columbia, MO, to determine whether weed control recommendations based on crop yield potential from a computerized weed management decision aid influence weed seed production in two soybean row spacings. At approximately 28 d after planting, weed densities and heights were entered into WeedSOFT® to generate a list of treatments ranked by predicted crop yields. Treatments included: (1) highest predicted crop yield in a glyphosate-resistant system, (2) highest predicted crop yield in a nonglyphosate-resistant system, (3) a 10% yield reduction, (4) a 20% yield reduction, and (5) an untreated control. These treatments were applied to soybean grown in 38- and 76-cm rows. Treatments that provided 90% or higher control of an individual species at 22 d after treatment usually produced less seed than untreated checks. Weed seed production based on early-season herbicide efficacy showed a linear relationship and was relatively predictable (r2 ≥ 0.52) for the predominant weed species. For less dominant weed species, weed seed production was not strongly correlated (r2 ≤ 0.27) to early-season herbicide efficacy but apparently influenced by control of other weed species. Narrow row spacing reduced giant foxtail biomass both years but did not reduce common ragweed and ivyleaf morningglory biomass. Narrow rows did not decrease giant foxtail, common ragweed, and ivyleaf morningglory seed production.

Field studies were conducted in 2000 and 2001 to evaluate corn yield-loss predictions generated by WeedSOFT, a computerized weed management decision aid. Conventional tillage practices were used to produce corn in 76-cm rows in Illinois, Indiana, Kansas, Michigan, Missouri, Nebraska, and Wisconsin. A total of 21 site-years from these seven states were evaluated in this study. At 4 wk after planting, weed densities and size, crop-growth stage, estimated weed-free yield, and environmental conditions at the time of application were entered into WeedSOFT to generate POST treatments ranked by percent maximum yield (PMY). POST treatments were chosen with yield losses ranging from 0 to 20%. Data were subjected to linear regression analysis by state and pooled over all states to determine the relationship between actual and predicted yield loss. A slope value equal to one implies perfect agreement between actual and predicted yield loss. Slope value estimates for Illinois and Missouri were equal to one. Actual yield losses were higher than the software predicted in Kansas and lower than predicted in Michigan, Nebraska, and Wisconsin. Slope value estimate from a data set containing all site years was equal to one. This research demonstrated that variability in yield-loss predictions occurred at sites that contained a high density of a single weed specie (>100/m2) regardless of its competitive index (CI); at sites with a predominant broadleaf weed with a CI greater than five, such as Palmer amaranth, giant ragweed, common sunflower, and common cocklebur; and at sites that experience moderate to severe drought stress.

Approximately half of the variation in wellbeing measures overlaps with variation in personality traits. Studies of non-human primate pedigrees and human twins suggest that this is due to common genetic influences. We tested whether personality polygenic scores for the NEO Five-Factor Inventory (NEO-FFI) domains and for item response theory (IRT) derived extraversion and neuroticism scores predict variance in wellbeing measures. Polygenic scores were based on published genome-wide association (GWA) results in over 17,000 individuals for the NEO-FFI and in over 63,000 for the IRT extraversion and neuroticism traits. The NEO-FFI polygenic scores were used to predict life satisfaction in 7 cohorts, positive affect in 12 cohorts, and general wellbeing in 1 cohort (maximal N = 46,508). Meta-analysis of these results showed no significant association between NEO-FFI personality polygenic scores and the wellbeing measures. IRT extraversion and neuroticism polygenic scores were used to predict life satisfaction and positive affect in almost 37,000 individuals from UK Biobank. Significant positive associations (effect sizes <0.05%) were observed between the extraversion polygenic score and wellbeing measures, and a negative association was observed between the polygenic neuroticism score and life satisfaction. Furthermore, using GWA data, genetic correlations of -0.49 and -0.55 were estimated between neuroticism with life satisfaction and positive affect, respectively. The moderate genetic correlation between neuroticism and wellbeing is in line with twin research showing that genetic influences on wellbeing are also shared with other independent personality domains.