Controlling annual weeds in cereals by deploying crop rotation at the landscape scale: Avena sterilis as an example

Weed control through crop rotation has mainly been studied in a nonspatial context. However, weed seeds are often spread beyond the crop field by a variety of vectors. For weed control to be successful, weed management should thus be evaluated at the landscape level. In this paper we assess how seed dispersal affects the interactions between crop rotation and landscape heterogeneity schemes with regard to weed control. A spatially explicit landscape model was developed to study both short- and long-term weed population dynamics under different management scenarios. We allowed for both two- and three-crop species rotations and three levels of between-field weed seed dispersal. All rotation scenarios and seed dispersal fractions were analyzed for both completely homogeneous landscapes and heterogeneous landscapes in which more than one crop was present. The potential of implementing new weed control methods was also analyzed. The model results suggest that, like crop rotation at the field level, crop rotation implemented at the landscape level has great potential to control weeds, whereby both the number of crop species and the cropping sequence within the crop rotation have significant effects on both the short- and long-term weed population densities. In the absence of seed dispersal, weed populations became extinct when the fraction of each crop in the landscape was randomized. In general, weed seed densities increased in landscapes with increasing similarity in crop proportions, but in these landscapes the level of seed dispersal affected which three-crop species rotation sequence was most efficient at controlling the weed densities. We show that ignoring seed dispersal between fields might lead to the selection of suboptimal tactics and that homogeneous crop field patches that follow a specific crop rotation sequence might be the most sustainable method of weed control. Effective weed control through crop rotation thus requires coordination between farmers with regard to cropping sequences, crop allocation across the landscape, and/ or the fraction of each crop across the landscape.     

Use of metal-reducing bacteria for bioremediation of soil contaminated with mixed organic and inorganic pollutants

Mixed contamination by organic and inorganic compounds in soil is a serious problem for remediation. Most laboratory studies and field-scale trials focused on individual contaminant in the past. For concurrent bioremediation by biodegradation and bioleaching processes, we tested metal-reducing microorganism, Geobacter metallireducens. In order to prove the feasibility of the coupled process, multiple-contaminated soil was prepared. Mineralogical analyses have shown the existence of labile forms of As(V) as amorphous and/or weakly sorbed phases in the secondary Fe oxides. In the biotic experiment using G. metallireducens, biodegradation of toluene and bioleaching of As by bacteria were observed simultaneously. Bacteria accelerated the degradation rate of toluene with reductive dissolution of Fe and co-dissolution of As. Although there have been many studies showing each individual process, we have shown here that the idea of concurrent microbial reaction is feasible. However, for the practical use as a remediation technology, more details and multilateral evaluations are required in future studies.     

Resolving local-scale emissions for modeling air quality near roadways

A large body of literature published in recent years suggests increased health risk due to exposure of people to air pollution in close proximity to roadways. As a result, there is a need to more accurately represent the spatial concentration gradients near roadways to develop mitigation strategies. In this paper, we present a practical, readily adaptable methodology, using a "bottom-up" approach to develop a detailed highway vehicle emission inventory that includes emissions for individual road links. This methodology also takes advantage of geographic information system (GIS) software to improve the spatial accuracy of the activity information obtained from a Travel Demand Model. In addition, we present an air quality modeling application of this methodology in New Haven, CT. This application uses a hybrid modeling approach, in which a regional grid-based model is used to characterize average local ambient concentrations, and a Gaussian dispersion model is used to provide texture within the modeling domain because of spatial gradients associated with highway vehicle emissions and other local sources. Modeling results show substantial heterogeneity of pollutant concentrations within the modeling domain and strong spatial gradients associated with roadways, particularly for pollutants dominated by direct emissions.     

The interplay between incremental,transitional, and transformational adaptation: a case study of Canadian agriculture

Regional Environmental Change - We develop and apply a synthetic framework for understanding potential adaptations to climate change in the Canadian agriculture sector through a case study of...     

Variable rainfall intensity and tillage effects on runoff, sediment, and carbon losses from a loamy sand under simulated rainfall

The low-carbon, intensively cropped Coastal Plain soils of Georgia are susceptible to runoff, soil loss, and drought. Reduced tillage systems offer the best management tool for sustained row crop production. Understanding runoff, sediment, and chemical losses from conventional and reduced tillage systems is expected to improve if the effect of a variable rainfall intensity storm was quantified. Our objective was to quantify and compare effects of a constant (Ic) intensity pattern and a more realistic, observed, variable (Iv) rainfall intensity pattern on runoff (R), sediment (E), and carbon losses (C) from a Tifton loamy sand cropped to conventional-till (CT) and strip-till (ST) cotton (Gossypium hirsutum L.). Four treatments were evaluated: CT-Ic, CT-Iv, ST-Ic, and ST-Iv, each replicated three times. Field plots (n=12), each 2 by 3 m, were established on each treatment. Each 6-m2 field plot received simulated rainfall at a constant (57 mm h(-1)) or variable rainfall intensity pattern for 70 min (12-run ave.=1402 mL; CV=3%). The Iv pattern represented the most frequent occurring intensity pattern for spring storms in the region. Compared with CT, ST decreased R by 2.5-fold, E by 3.5-fold, and C by 7-fold. Maximum runoff values for Iv events were 1.6-fold higher than those for Ic events and occurred 38 min earlier. Values for Etot and Ctot for Iv events were 19-36% and 1.5-fold higher than corresponding values for Ic events. Values for Emax and Cmax for Iv events were 3-fold and 4-fold higher than corresponding values for Ic events. Carbon enrichment ratios (CER) were or=1.0 for CT plots (except for first 20 min). Maximum CER for CT-Ic, CT-Iv, ST-Ic, and ST-Iv were 2.0, 2.2, 1.0, and 1.2, respectively. Transport of sediment, carbon, and agrichemicals would be better understood if variable rainfall intensity patterns derived from natural rainfall were used in rainfall simulations to evaluate their fate and transport from CT and ST systems.     

46,XX/46,XY chromosome complement in amniotic fluid cell culture followed by the birth of a normal female child

Experience indicates that the most likely explanation for a mixture of 46,XX/46,XY cells in an amniotic fluid sample is that of maternal cell contamination and that a normal male child is to be expected at birth. We report the birth of a normal female child following prenatal diagnosis of such a mixture. Extensive postnatal studies failed to reveal an XY cell line. The possible sources of the XY cell line are discussed, as are the various techniques that were applied in an effort to discover it's origin. Cross-contamination of samples could be ruled out and there was no evidence of an unsuspected twin pregnancy. It is clear from this case that not all 46,XX/46,XY results obtained in amniotic fluid can be assumed to represent maternal cell contamination and some effort should be made to eliminate other potential sources for such a mixture.     

SIMULATING NITROGEN LOSSES FROM AGRICULTURAL LAND: IMPLICATIONS FOR WATER QUALITY AND PROTECTION POLICY1

ABSTRACT: EPIC, a soil erosion/plant growth simulation model, is used to simulate nitrogen losses for 120 randomly selected and previously surveyed cropland sites. Simulated nitrogen losses occur through volatilization, surface water and soil runoff, subsurface lateral flow, and leaching. Physical and crop management variables explain a moderate but significant proportion of the variation in nitrogen losses. Site slope and tillage have offsetting effects on surface and ground water losses. Nitrogen applications in excess of agronomic recommendations and manure obtained off the farm and applied to the sites are significant contributors to nitrogen losses. Farm characteristics such as production of confined livestock, total manure nitrogen available, and farm income per cropland acre explain a relatively large portion of the variability in manure nitrogen applied to survey sites. The results help to identify farm characteristics that can be used to target nutrient management programs. Simulation modeling provides a useful tool for investigating variables which contribute to agricultural nitrogen losses.     

Effect of climate change on air quality

Air quality is strongly dependent on weather and is therefore sensitive to climate change. Recent studies have provided estimates of this climate effect through correlations of air quality with meteorological variables, perturbation analyses in chemical transport models (CTMs), and CTM simulations driven by general circulation model (GCM) simulations of 21st-century climate change. We review these different approaches and their results. The future climate is expected to be more stagnant, due to a weaker global circulation and a decreasing frequency of mid-latitude cyclones. The observed correlation between surface ozone and temperature in polluted regions points to a detrimental effect of warming. Coupled GCM–CTM studies find that climate change alone will increase summertime surface ozone in polluted regions by 1–10 ppb over the coming decades, with the largest effects in urban areas and during pollution episodes. This climate penalty means that stronger emission controls will be needed to meet a given air quality standard. Higher water vapor in the future climate is expected to decrease the ozone background, so that pollution and background ozone have opposite sensitivities to climate change. The effect of climate change on particulate matter (PM) is more complicated and uncertain than for ozone. Precipitation frequency and mixing depth are important driving factors but projections for these variables are often unreliable. GCM–CTM studies find that climate change will affect PM concentrations in polluted environments by ±0.1–1 μg m^?3 over the coming decades. Wildfires fueled by climate change could become an increasingly important PM source. Major issues that should be addressed in future research include the ability of GCMs to simulate regional air pollution meteorology and its sensitivity to climate change, the response of natural emissions to climate change, and the atmospheric chemistry of isoprene. Research needs to be undertaken on the effect of climate change on mercury, particularly in view of the potential for a large increase in mercury soil emissions driven by increased respiration in boreal ecosystems.     

Impact of underestimating the effects of cold temperature on motor vehicle start emissions of air toxics in the United States

Analyses of U.S. Environmental Protection Agency (EPA) certification data, California Air Resources Board surveillance testing data, and EPA research testing data indicated that EPA's MOBILE6.2 emission factor model substantially underestimates emissions of gaseous air toxics occurring during vehicle starts at cold temperatures for light-duty vehicles and trucks meeting EPA Tier 1 and later standards. An unofficial version of the MOBILE6.2 model was created to account for these underestimates. When this unofficial version of the model was used to project emissions into the future, emissions increased by almost 100% by calendar year 2030, and estimated modeled ambient air toxics concentrations increased by 6-84%, depending on the pollutant. To address these elevated emissions, EPA recently finalized standards requiring reductions of emissions when engines start at cold temperatures.