Observations of radiocarbon (14C) in Earth’s atmosphere and other carbon reservoirs are important to quantify exchanges of CO2 between reservoirs. The amount of 14C is commonly reported in the so-called Delta notation, i.e., Δ14C, the decay- and fractionation-corrected departure of the ratio of 14C to total C from that ratio in an absolute international standard; this Delta notation permits direct comparison of 14C/C ratios in the several reservoirs. However, as Δ14C of atmospheric CO2, Δ14CO2 is based on the ratio of 14CO2 to total atmospheric CO2, its value can and does change not just because of change in the amount of atmospheric14CO2 but also because of change in the amount of total atmospheric CO2, complicating ascription of change in Δ14CO2 to change in one or the other quantity. Here we suggest that presentation of atmospheric 14CO2 amount as mole fraction relative to dry air (moles of 14CO2 per moles of dry air in Earth’s atmosphere), or as moles or molecules of 14CO2 in Earth’s atmosphere, all readily calculated from Δ14CO2 and the amount of atmospheric CO2 (with slight dependence on δ13CO2), complements presentation only as Δ14CO2, and can provide valuable insight into the evolving budget and distribution of atmospheric 14CO2.

Excess unabsorbed iron in the gastrointestinal tract may select for enteric pathogens and increase the incidence and severity of infectious disease. Aspergillus oryzae (Ao) is a filamentous fungus that has the ability to accumulate and store large amounts of iron, and when used as a supplement or fortificant, has similar absorption to ferrous sulphate (FeSO4) in humans. The objective of this study was to determine the effect of iron-enriched Ao (Ao iron) compared with FeSO4 on iron accumulation, growth and motility of the Gram-negative enteric pathogen, S. Typhimurium. S. Typhimurium was cultured in media containing no added iron or 1 μM elemental iron as either Ao iron or FeSO4. S. Typhimurium cultured with FeSO4 accumulated more iron than those cultured with Ao iron. Genes regulated by the iron-activated transcriptional repressor, Fur, did not differ between control and Ao iron, but decreased in S. Typhimurium cultured with FeSO4 compared with both groups. Growth of S. Typhimurium was greater when cultured with FeSO4 compared with Ao iron and control. S. Typhimurium swam faster, had greater acceleration and travelled further when cultured with FeSO4 compared with Ao iron and control; swim speed, acceleration and distance travelled did not differ between Ao iron and control. These findings provide evidence that Ao iron reduces the virulence of a common enteric pathogen in vitro. Further research is required to determine whether iron-enriched Ao is a suitable iron supplement to improve iron delivery in areas with a high infection burden.

Theories of early cooperation in human society often draw from a small sample of ethnographic studies of surviving populations of hunter–gatherers, most of which are now sedentary. Borneo hunter–gatherers (Punan, Penan) have seldom figured in comparative research because of a decades-old controversy about whether they are the descendants of farmers who adopted a hunting and gathering way of life. In 2018 we began an ethnographic study of a group of still-nomadic hunter–gatherers who call themselves Punan Batu (Cave Punan). Our genetic analysis clearly indicates that they are very unlikely to be the descendants of neighbouring agriculturalists. They also preserve a song language that is unrelated to other languages of Borneo. Dispersed travelling groups of Punan Batu with fluid membership use message sticks to stay in contact, co-operate and share resources as they journey between rock shelters and forest camps. Message sticks were once widespread among nomadic Punan in Borneo, but have largely disappeared in sedentary Punan villages. Thus the small community of Punan Batu offers a rare glimpse of a hunting and gathering way of life that was once widespread in the forests of Borneo, where prosocial behaviour extended beyond the face-to-face community, facilitating successful collective adaptation to the diverse resources of Borneo's forests.

The Virtual Personalities Model is a motive-based neural network model that provides both a psychological model and a computational implementation that explicates the dynamics and often large within-person variability in behavior that arises over time. At the same time the same model can produce—across many virtual personalities—between-subject variability in behavior that when factor analyzed yields familiar personality structure (e.g., the Big Five). First, we describe our personality model and its implementation as a neural network model. Second, we focus on detailing the neurobiological underpinnings of this model. Third, we examine the learning mechanisms, and their biological substrates, as ways that the model gets “wired up,” discussing Pavlovian and Instrumental conditioning, Pavlovian to Instrumental transfer, and habits. Finally, we describe the dynamics of how initial differences in propensities (e.g., dopamine functioning), wiring differences due to experience, and other factors could operate together to develop and change personality over time, and how this might be empirically examined. Thus, our goal is to contribute to the rising chorus of voices seeking a more precise neurobiologically based science of the complex dynamics underlying personality.

Post-magmatic alteration of certain magmatic Ni sulfide ores in Western Australia, the Miitel deposit and the Sarah's Find prospect, produced Ni–As–PGE haloes around massive sulfides. A study of the composition of arsenide grains from these hydrothermal haloes, along with arsenides from various magmatic and hydrothermal mineralized environments in other localities, was conducted in order to compare their composition, and assess their potential use as indicator minerals for exploration vectoring, as well as to gain knowledge on their crystallization history. Concentrations in trace elements such as platinum-group elements (PGEs), Au and other metals was obtained by laser ablation inductively coupled plasma mass spectroscopy analyses. Results show that variations in PGEs and Au compositions can be related to the magmatic vs. hydrothermal origin of the grains; and to their provenance from deposits enriched in either Ni, Au or both. Magmatic NiCoFe sulfarsenides have strongly correlated, high IPGE (Os, Ir, Ru, Rh) contents up to 100 ppm Ir, compared with maximum values in hydrothermal sulfarsenides of ~1 ppm. Gold in hydrothermal sulfarsenides from Au-mineralized ultramafic rocks extends up to 500 ppm, with typical values of 3–30 ppm; similar values are also found in nickeline (also called niccolite). These results suggest that nickel arsenides could potentially be used as indicator minerals for nickel and gold exploration. Trace-element contents of arsenide grains in shear zones could be used to deduce the presence of Ni or Au mineralization upstream in the fluid pathway.

Crop yield loss–weed density relationships critically influence calculation of economic thresholds and the resulting management recommendations made by a bioeconomic model. To examine site-to-site and year-to-year variation in winter Triticum aestivum L. (winter wheat)–Aegilops cylindrica Host. (jointed goatgrass) interference relationships, the rectangular hyperbolic yield loss function was fit to data sets from multiyear field experiments conducted at Colorado, Idaho, Kansas, Montana, Nebraska, Utah, Washington, and Wyoming. The model was fit to three measures of A. cylindrica density: fall seedling, spring seedling, and reproductive tiller densities. Two parameters: i, the slope of the yield loss curve as A. cylindrica density approaches zero, and a, the maximum percentage yield loss as A. cylindrica density becomes very large, were estimated for each data set using nonlinear regression. Fit of the model to the data was better using spring seedling densities than fall seedling densities, but it was similar for spring seedling and reproductive tiller densities based on the residual mean square (RMS) values. Yield loss functions were less variable among years within a site than among sites for all measures of weed density. For the one site where year-to-year variation was observed (Archer, WY), parameter a varied significantly among years, but parameter i did not. Yield loss functions differed significantly among sites for 7 of 10 comparisons. Site-to-site statistical differences were generally due to variation in estimates of parameter i. Site-to-site and year-to-year variation in winter T. aestivum–A. cylindrica yield loss parameter estimates indicated that management recommendations made by a bioeconomic model cannot be based on a single yield loss function with the same parameter values for the winter T. aestivum-producing region. The predictive ability of a bioeconomic model is likely to be improved when yield loss functions incorporating time of emergence and crop density are built into the model's structure.

Field studies were conducted in Colorado, Kansas, and Wyoming to compare the use of quinclorac plus 2,4-D with picloram plus 2,4-D, dicamba plus 2,4-D, a glyphosate plus 2,4-D premix, and 2,4-D alone for control of field bindweed (Convolvulus arvensis) in a winter wheat (Triticum aestivum)-fallow rotation. Treatments were applied in late summer or fall each year for two, three, or four consecutive years at the beginning and end of each fallow period. Evaluations were taken 10 to 12 mo after treatment each year. Quinclorac plus 2,4-D and picloram plus 2,4-D consistently performed as well as or better than 2,4-D, dicamba plus 2,4-D, and glyphosate plus 2,4-D. Wheat yields increased when field bindweed was controlled during the fallow period. Strong correlations (r > −0.85) were obtained among visual field bindweed evaluation, biomass, and stand count data.

Crop rotation has long been considered one of the simplest and most effective tools for managing weeds. In this paper, we demonstrate how crop rotations can be strategically arranged to harness a novel mechanism of weed suppression: weed-weed competition. Specifically, we consider how crop stacking, or increasing the number of consecutive plantings of a single crop within a rotation, can decrease the size of the weed seed bank, by forcing weeds to compete with each other in similar environments for longer periods of time, while still reaping the traditional benefits of crop rotation. Using an annual plant model, we investigate the theoretical effects of stacked crop rotations on weeds that have different life-history strategies and phenology. Our results show that when weeds compete within a season, stacking can reduce the weed seed bank compared to rotations without stacked crops. Although more research is needed to fully understand the effects of crop stacking on other aspects of the system, such as insect pests and diseases, our research suggests that crop stacking has the potential to improve weed suppression without additional inputs, and their associated costs and externalities. More generally, improving management by changing the temporal arrangement of disturbances is a novel, process-based approach that could likely be applied to other weed management practices, such as mowing and herbicide application, and which could involve mechanisms other than weed-weed competition. Leveraging this new application of existing ecological theory to improve weed management strategies holds great promise.

Jointed goatgrass is a problem weed in winter wheat production areas of the Great Plains. Winter wheat seeding rates are easily adjusted by the growers and influence competition by some weeds. Field experiments were initiated in Kansas, Nebraska, and Wyoming using winter wheat cultivars selected from leading adapted cultivars from each region to determine the effect of wheat plant density in the fall on jointed goatgrass competitiveness. Three winter wheat seeding rates (50, 67, and 84 kg seeds/ha) were used at Hays, KS, and Sidney, NE, and four seeding rates (33, 50, 67, and 101 kg seeds/ha) were used at Torrington and Archer, WY. An analysis of covariance model was fit with winter wheat fall plant density as the covariate. In 1996, winter wheat grain contamination (dockage) was reduced at the rate of about 6% for every 10 additional wheat plants/m2 above the threshold density of 70 plants/m2 at Archer, WY, and at the rate of about 0.5% for every 10 additional wheat plants/m2 above the threshold density of 110 plants/m2 at Hays, KS. At Hays the reduction occurred only with the semidwarf cultivar ‘Vista’. Increased wheat density reduced jointed goatgrass reproductive tillers in four out of six location–year combinations and biomass in two out of four location–year combinations. Despite the lack of a consistent reduction in jointed goatgrass competitiveness as the result of increased wheat density, increased seeding rates may be a good, low-cost, long-term investment as part of an integrated jointed goatgrass control program in winter wheat.

Cogongrass, an invasive grass native to Asia, has infested thousands of hectares in the southeastern United States. Although numerous studies have examined cogongrass control, no published studies, to our knowledge, have tested strategies for cogongrass eradication. Cogongrass has a persistent, thick rhizome mat but an ephemeral seedbank; therefore, successful eradication methods must largely focus on the rhizomes. A field study to evaluate specific herbicide treatments and application timings for cogongrass patch eradication was conducted at two locations in southwestern Alabama. Herbicide treatments included glyphosate at 4.48 kg ai ha−1, imazapyr at 0.84 kg ai ha−1, and a tank mix of glyphosate and imazapyr at the same rates. Treatments were applied in May, August, or October for 3 consecutive yr, and the May glyphosate treatment included a second annual application each October. Cogongrass visual control, shoot biomass, rhizome biomass, rhizome depth, and total nonstructural carbohydrate (TNC) content were sampled during the course of the study. Cogongrass response to treatments varied by location but by 36 mo after initial treatment (MAIT), complete elimination of cogongrass shoot and rhizome biomass and 100% visual control was achieved in several herbicide treatment–timing combinations at both locations. These included glyphosate plus imazapyr at any application timing, imazapyr in August or October, and glyphosate applied in May and October each year. TNC levels of surviving healthy rhizomes were not affected by herbicide treatments, but a seasonal pattern was observed. The maximum live-rhizome depth was not influenced by any treatment, indicating that herbicides were not preferentially leaving deeper, surviving rhizomes. These results demonstrate, for the first time, that the entire rhizome layer of cogongrass can be eliminated within 3 yr with multiple treatment options and that cogongrass patch eradication is possible for many land managers.

Secale cereale is a serious weed problem in winter Triticum aestivum–producing regions. The interference relationships and economic thresholds of S. cereale in winter T. aestivum in Colorado, Kansas, Nebraska, and Wyoming were determined over 4 yr. Winter T. aestivum density was held constant at recommended planting densities for each site. Target S. cereale densities were 0, 5, 10, 25, 50, or 100 plants m−2. Secale cereale–winter T. aestivum interference relationships across locations and years were determined using a negative hyperbolic yield loss function. Two parameters—I, which represents the percent yield loss as S. cereale density approaches zero, and A, the maximum percent yield loss as S. cereale density increases—were estimated for each data set using nonlinear regression. Parameter I was more stable among years within locations than among locations within years, whereas maximum percentage yield loss was more stable across locations and years. Environmental conditions appeared to have a role in the stability of these relationships. Parameter estimates for I and A were incorporated into a second model to determine economic thresholds. On average, threshold values were between 4 and 5 S. cereale plants m−2; however, the large variation in these threshold values signifies considerable risk in making economic weed management decisions based upon these values.

Three models that empirically predict crop yield from crop and weed density were evaluated for their fit to 30 data sets from multistate, multiyear winter wheat–jointed goatgrass interference experiments. The purpose of the evaluation was to identify which model would generally perform best for the prediction of yield (damage function) in a bioeconomic model and which model would best fulfill criteria for hypothesis testing with limited amounts of data. Seven criteria were used to assess the fit of the models to the data. Overall, Model 2 provided the best statistical description of the data. Model 2 regressions were most often statistically significant, as indicated by approximate F tests, explained the largest proportion of total variation about the mean, gave the smallest residual sum of squares, and returned residuals with random distribution more often than Models 1 and 3. Model 2 performed less well based on the remaining criteria. Model 3 outperformed Models 1 and 2 in the number of parameters estimated that were statistically significant. Model 1 outperformed Models 2 and 3 in the proportion of regressions that converged on a solution and more readily exhibited an asymptotic relationship between winter wheat yield and both winter wheat and jointed goatgrass density under the constraint of limited data. In contrast, Model 2 exhibited a relatively linear relationship between yield and crop density and little effect of increasing jointed goatgrass density on yield, thus overpredicting yield at high weed densities when data were scarce. Model 2 had statistical properties that made it superior for hypothesis testing; however, Model 1's properties were determined superior for the damage function in the winter wheat–jointed goatgrass bioeconomic model because it was less likely to cause bias in yield predictions based on data sets of minimum size.

Field experiments were conducted at five locations in Kansas, Nebraska, and Wyoming to determine the effects of imazamox rate and application timing on winter annual grass control and crop response in imidazolinone-tolerant winter wheat. Imazamox at 35, 44, or 53 g ai/ha applied early-fall postemergence (EFP), late-fall postemergence, early-spring postemergence (ESP), or late-spring postemergence (LSP) controlled jointed goatgrass at least 95% in all experiments. Feral rye control with imazamox was 95 to 99%, regardless of rate or application timing at Hays, KS, in 2001. Feral rye control at Sidney, NE, and Torrington, WY, was highest (78 to 85%) with imazamox at 44 or 53 g/ha. At Sidney and Torrington, feral rye control was greatest when imazamox was applied EFP. Imazamox stunted wheat <10% in two experiments at Torrington, but EFP or LSP herbicide treatments in the Sidney experiment and ESP or LSP treatments in two Hays experiments caused moderate (12 to 34%) wheat injury. Wheat injury increased as imazamox rate increased. Wheat receiving imazamox LSP yielded less grain than wheat treated at other application timings in each Hays experiment and at Sidney in 2001. No yield differences occurred in one Torrington experiment. However, yields generally decreased as imazamox application timing was delayed in the other Torrington experiment. Generally, imazamox applied in the fall provided the greatest weed control, caused the least wheat injury, and maximized wheat yield.

A Research Committee was established by the Weed Science Society of America to outline the direction of weed science research during the next decade. Weeds adversely affect humans in both agricultural and nonagricultural environments. It is the opinion of the research committee that weed science will be advantageously positioned for the future if research focuses on research decision processes, weed biology and ecology, weed control and management practices, herbicide resistance, issues related to transgenic plants, environmental issues, and potential benefits of weeds. These future weed science research directions endorse those of the commodity and grower input group Coalition for Research on Plant Systems (CROPS)'99, a U.S. Department of Agriculture (USDA)-supported initiative. The future of weed science is dependent on a joint effort from industry, government regulators, and the public sector consisting of grower groups, as well as USDA, Agriculture and Agri-Food Canada (AAFC), and university researchers. It is our opinion that efforts spent on these research areas will benefit not only growers, commodity groups, homeowners, and industry, but society at large, through the maintenance and improvement of the food and fiber production system, and the environment in North America.

Field experiments were conducted in 1994 and 1995 under sprinkler irrigation at the University of Wyoming Research and Extension Center at Torrington to evaluate the effects of season-long interference and the effects of duration of interference of several common sunflower and green foxtail densities, alone or in combination, on pinto bean yield. Green foxtail densities did not significantly affect pinto bean yield in 1994 and reduced yield only at the highest density in 1995. In contrast, sunflower densities reduced pinto bean yield, except at the lowest density in 1994. Pinto bean yield was reduced as the combined density of green foxtail and sunflower increased. Compared with yield losses from each weed species alone, yield reductions from mixed species were additive in 1994 and at low weed densities in 1995 and less than additive at higher weed densities in 1995. The minimum number of weeds per m of row that will economically reduce pinto bean yield was estimated to be 1.6 to 2.9 for green foxtail and 0.12 to 0.2 for sunflower. Pinto bean yield reduction increased as the duration of green foxtail and sunflower interference increased, whether grown alone or in combination. The maximum duration that green foxtail, sunflower, and green foxtail plus sunflower can interfere with pinto bean before causing economical losses was estimated to be 4.5, 3.2, and 2.5 wk, respectively.