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Predicting the consequences of manipulating genotype (G) and agronomic management (M) on agricultural ecosystem performances under future environmental (E) conditions remains a challenge. Crop modelling has the potential to enable society to assess the efficacy of G × M technologies to mitigate and adapt crop production systems to climate change. Despite recent achievements, dedicated research to develop and improve modelling capabilities from gene to global scales is needed to provide guidance on designing G × M adaptation strategies with full consideration of their impacts on both crop productivity and ecosystem sustainability under varying climatic conditions. Opportunities to advance the multiscale crop modelling framework include representing crop genetic traits, interfacing crop models with large-scale models, improving the representation of physiological responses to climate change and management practices, closing data gaps and harnessing multisource data to improve model predictability and enable identification of emergent relationships. A fundamental challenge in multiscale prediction is the balance between process details required to assess the intervention and predictability of the system at the scales feasible to measure the impact. An advanced multiscale crop modelling framework will enable a gene-to-farm design of resilient and sustainable crop production systems under a changing climate at regional-to-global scales.

There is a growing global consensus among food system experts that diets and how we source our foods must change. The sustainable nutrition community continues exploring the environmental impact and dietary value of foods. Packaged foods have been largely ignored within the dialogue, and if they are addressed, existing frameworks tend to label them all as "ultraprocessed" and uniformly discourage their consumption. This approach lacks the nuance needed to holistically evaluate packaged foods within recommended dietary patterns. Additionally, there is considerable diversity of opinion within the literature on these topics, especially on how best to improve nutrition security in populations most at risk of diet-related chronic disease. In support of addressing these challenges, 8 sustainability and nutrition experts were convened by Clif BarCompany for a facilitated discussion on the urgent need to drive adoption of healthy, sustainable diets; the crucial role that certain packaged foods can play in helping make such diets achievable and accessible; and the need for actionable guidance around how to recommend and choose packaged foods that consider human, societal, and planetary health. This article summarizes the meeting discussion, which informed the development of a proposed framework based on guiding principles for defining sustainable, nutritious packaged foods across key nutrition, environmental, economic, and sociocultural well-being indicators. Although additional research is needed to substantiate specific metrics in order to operationalize the framework, it is intended to be a foundation from which to build and refine as science and measurement capabilities advance, and an important step toward broader adoption of healthy, sustainable diets.

Food systems are increasingly challenged to meet growing demand for specialty crops due to the effects of climate change and increased competition for resources. Here, we apply an integrated methodology that includes climate, crop, economic and life cycle assessment models to US potato and tomato supply chains. We find that supply chains for two popular processed products in the United States, French fries and pasta sauce, will be remarkably resilient, through planting adaptation strategies that avoid higher temperatures. Land and water footprints will decline over time due to higher yields, and greenhouse gas emissions can be mitigated by waste reduction and process modification. Our integrated methodology can be applied to other crops, health-based consumer scenarios (fresh versus processed) and geographies, thereby informing decision-making throughout supply chains. Employing such methods will be essential as food systems are forced to adapt and transform to become carbon neutral due to the imperatives of climate change. An integrated methodology that includes climate, crop, economic and life cycle assessment models was developed to explore the climate adaptation and mitigation opportunities throughout the US potato and tomato supply chains. This study shows that supply chains for two popular processed products in the United States, French fries and pasta sauce, will be remarkably resilient, through planting adaptation strategies.

Food systems are increasingly challenged to meet growing demand for specialty crops due to the effects of climate change and increased competition for resources. We apply a novel integrated methodology that includes climate, crop, economic, and life cycle assessment (LCA) models to US potato and tomato supply chains. We assess the effectiveness of changing management strategies to address climate change and the opportunity to relocate away from regions with increased water scarcity. We find that supply chains for two popular processed products in the United States, French fries and pasta sauce, will be remarkably resilient, through planting adaptation strategies that avoid higher temperatures. Land and water footprints will decline over time due to higher yields, and GHG emissions can be mitigated by waste reduction and process modification. Our integrated methodology can be applied to other crops and geographies, and the results could inform decision-making at multiple steps along supply chains.

Twenty-first-century challenges for food and nutrition security include the spread of obesity worldwide and persistent undernutrition in vulnerable populations, along with continued micronutrient deficiencies. Climate change, increasing incomes and evolving diets complicate the search for sustainable solutions. Projecting to the year 2050, we explore future macronutrient and micronutrient adequacy with combined biophysical and socioeconomic scenarios that are country-specific. In all scenarios for 2050, the average benefits of widely shared economic growth, if achieved, are much greater than the modelled negative effects of climate change. Average macronutrient availability in 2050 at the country level appears adequate in all but the poorest countries. Many regions, however, will continue to have critical micronutrient inadequacies. Climate change alters micronutrient availability in some regions more than others. These findings indicate that the greatest food security challenge in 2050 will be providing nutritious diets rather than adequate calories. Research priorities and policies should emphasize nutritional quality by increasing availability and affordability of nutrient-dense foods and improving dietary diversity. Global environmental change complicates the goal of securing adequate nutrition for a growing world population. This study assesses the per capita availability of food nutrients for various scenarios to the year 2050. Results suggest that economic growth will expand food and macronutrient access more than climate change will suppress it, but that micronutrient inadequacies will plague some regions.

Recent analyses indicate that global fruit and vegetable (F&V) production will need to increase by 50%–150% by 2050 in order to achieve sustainable and healthy diets for 10 billion people. Although global production of F&V has grown by 50% during the last two decades alone, simply scaling up current systems of F&V production, supply chains, and consumption will inevitably worsen environmental and socioeconomic tradeoffs. This article examines three examples of important F&V—avocados, leafy greens, and tomatoes—to assess the global challenge of meeting dietary recommendations at affordable prices to consumers while sustaining producer livelihoods and minimizing environmental damage. These three cases highlight key characteristics of F&V systems that make the challenge of sustainable expansion especially difficult: knowledge-, input-, and labor-intensive production, high rates of food loss and waste, and low affordability to consumers relative to less nutrient-dense food groups. Our analysis shows that only by investing in innovations that increase diversity, integrate technology, and improve equity will truly sustainable expansion of F&V systems be possible.

We’re being warned of future grain failures—not by the dreams of a biblical Pharaoh, but by modern computer model predictions. Climate science forecasts rising temperatures, changing rainfall patterns, and episodes of increasingly extreme weather, which will harm crop yields at a time when the world’s growing population can ill afford declines, especially in its most productive areas, such as the US Midwest. In order to adequately prepare, we call for the establishment of a new field research network across the US Midwest to fully integrate all methods for improving cropping systems and leveraging big data (agronomic, economic, environmental, and genomic) to facilitate adaptation and mitigation. Such a network, placed in one of the most important grain-producing areas in the world, would provide the set of experimental facilities, linked to farm settings, needed to explore and test the adaptation and mitigation strategies that already are needed globally.

The objective of this project was to explore national-scale data relationships between land use, primarily variables pertaining to agricultural production, and in-stream biotic conditions in the mainland U.S. Using the Causal Analysis/Diagnosis Decision Information System (CADDIS) and data from the USGS National Water Quality Assessment Program (NAWQA), benthic macroinvertebrate observed versus predicted (O/E) index values were analyzed against a number of land use and habitat variables in 115 sites across the U.S. Constituent loads, or the mass amounts of a chemical constituent entering the waterway per year, were estimated for each site using the USGS LOADEST program and were evaluated with respect to macroinvertebrate O/E and land use values. Relationships between variables, defined causally through CADDIS, were analyzed using simple linear regression to avoid analytical bias. Regression analyses indicated that forest and urban land cover were significantly correlated to macroinvertebrate O/E values (p = 0.0012 and p

Nutrition science-based dietary advice urges changes that may have a great impact on agricultural systems. For example, the 2016 Dietary Guidelines for Americans (DGA) recommends greatly increased fruit and vegetable consumption, but the present domestic production is insufficient to accommodate large-scale adoption of these guidelines. Increasing production to the extent needed to meet the DGA will necessitate changes in an already stressed agriculture and food system and will require nutrition and agriculture professionals to come together in open and collegial discourse. All involved need to understand the stress placed on the food system by increasing populations, changing diets, and changing environments, and recognize the major diet-based public health challenges. Furthermore, there is a need to understand the intricate interplay of the myriad parts of the food system and the vast amount of work necessary to make even small changes. New systems approaches are needed, especially at the research level, where nutrition, public health, agriculture, and the food industry work together to solve interconnected problems. Future well-being depends on a sustainable food system that continues to deliver optimal health with minimal impact on the environment.

The literature on the importance of plant pathogens sometimes emphasizes their possible role in historical foodshortages and even in famines. Aside from such major crises, plant pathogens should also be seen as important reducers of crop performances, with impacts on system sustainability, from the ecological, agronomical, social, and economic standpoints – all contributing ultimately to affecting food security. These views need reconciliation in order to produce a clearer picture of the multidimensional effects of plant disease epidemics. Such a picture is needed for disease management today, but would also be useful for future policies. This article attempts to develop a framework that would enable assessment of the impacts of plant diseases, referred collectively to as crop health, on food security via its components. We have combined three different existing definitions of food security in order to develop a framework consisting of the following six components: (1) Availability. Primary production; (2) Availability. Import - Stockpiles; (3) Access. Physical and supply chain; (4) Access. Economic; (5) Stability of food availability; (6) Utility-Safety-Quality- Nutritive value. In this framework, components of food security are combined with three attributes of production situations: the nature of the considered crop (i.e. food- or non- food), the structure of farms (i.e. subsistence or commercial), and the structure of markets (i.e. weakly organized and local, to strongly organized and globalized). The resulting matrix: [Food security components] × [Attributes of production situations] provides a framework where the impacts of chronic, acute, and emerging plant disease epidemics on food security can be examined. We propose that, given the number of components and interactions at play, a systems modelling approach is required to address the functioning of food systems exposed to plant disease risks. This approach would have application in both the management of the current attrition of crop performances by plant diseases, and also of possible disease-induced shocks. Such an approach would also enable quantifying shifts in disease vulnerability of production situations, and therefore, of food systems, as a result of climate change, globalization, and evolving crop health.

Sustainability considerations should be an integral component of food security assessments. Nourishing the expected global population of nine billion in the face of fast diminishing land and water resources and looming climate change has tremendous economic, environmental, and social implications. Furthermore, whereas much past work on food security had focused on feeding the world through more staple crop calories, the current emphasis is on nourishing the global population through the provision of a more nutrient-rich diet. Hence the focus on micronutrient deficiencies (so-called ‘hidden hunger’), dietary diversity, and the nutrient density of the food supply—all critical components of overall nutritional status. To aid future assessments of ‘sustainable nutrition security’, we need a new methodology and some novel assessment metrics and tools. Seven metrics are proposed, each based on a combination of multiple indicators, for use in characterizing sustainable nutrition outcomes of food systems: (1) nutrient adequacy of foods and diets; (2) ecosystem stability; (3) food affordability and availability; (4) sociocultural wellbeing; (5) food safety; (6) resilience; and (7) waste and loss reduction. Each of the metrics comprises multiple indicators that are combined to derive an overall score (0–100). The metrics can be combined with simulation models and then deployed by decision-makers and investors to set meaningful goals, track progress, and evaluate the potential impact of targeted food system interventions. The goal is to improve food system sustainability and resilience and to improve human nutrition and health outcomes.

Climate change represents an unavoidable and growing challenge to food security, imposing new adaptation imperatives on all farmers. Maize is arguably the world's most productive grain crop, as measured by grain yield. However, maize yields vary dramatically due to many factors, including soils, climate, pests, disease, agronomic practices, and seed quality. The difference between observed yields and those achievable by optimized crop production methods is called the yield gap. In this work we quantified the current yield gap for 44 countries through the use of a large private-sector data set recently made available to the crop modelling community. The yield gap was quantified for three groups of countries, categorized by level of intensification. Observed yield gaps for high, medium, and low levels of intensification are 23%, 46%, and 68%, respectively. If all maize production countries were able to shrink their yield gap to 16.5% (as in the USA) an additional 335 million metric tons (MMT) of maize grain...

A session was convened at the ASN Nutrition 2018 annual meeting to discuss the scientific evidence on what makes individual foods and dietary patterns both sustainable and nutritious, and the role of various stakeholders in the actions needed to implement food systems that deliver “sustainable nutrition.” This commentary is a structured synthesis of the primary themes of the session, and concludes with a set of implications and research recommendations. Consumers are becoming increasingly aware of the environmental implications of what they eat, and there is growing momentum toward changes in the food system. However, ecological challenges persist, and although the literature is evolving, methodologic improvements are needed in the scientific approaches to address dietary patterns that meet nutrition needs in more holistically sustainable ways. The session concluded with encouraging evidence that consumers, businesses, scientists, and policy-makers are collectively “rising to the occasion,” with cross-sectoral partnerships to address these issues.

Sustainability considerations have been absent from most food security assessments conducted to date, despite the tremendous economic, environmental, and social implications of meeting accelerating food demand in the face of water shortages and climate change. In addition, previous food security work has generally focused only on achieving adequate calories, rather than addressing dietary diversity and micronutrient adequacy, both of which are critical to maintaining a healthy overall nutritional status. In response to the limitations of previous assessments, a new methodology is proposed here based on the concept of “sustainable nutrition security” (SNS). This novel assessment methodology is intended to remedy both kinds of deficiencies in the previous work by defining seven metrics, each based on a combination of multiple indicators, for use in characterizing sustainable nutrition outcomes of food systems: (1) food nutrient adequacy; (2) ecosystem stability; (3) food affordability and availability; (4) sociocultural wellbeing; (5) food safety; (6) resilience; and (7) waste and loss reduction. Each of the metrics comprises multiple indicators that are combined to derive an overall score (0–100). A novel SNS assessment methodology based on these metrics can be deployed by decision-makers and investors to set meaningful goals, track progress, and evaluate the potential impact of food system interventions intended to improve sustainability and human nutrition outcomes.

Convincing data now show that temperatures are increasing, and that changing precipitation patterns are already affecting agriculture. Predicted future impacts vary by region, but all are projected to suffer productivity declines by the late twenty-first century unless successful mitigation measures are implemented soon. Exacerbating the climate change challenge, doubling of overall crop productivity will be required by mid-century. Clearly, crop protection will become increasingly difficult as higher-yielding varieties present a larger and more tempting target to all pests, and the pests themselves extend their ranges poleward and into other new geographies owing to reduced winter kill and longer growing seasons. Fortunately, good progress on enhancing crop protection technology to meet these challenges is already being made, but the scope of this climatic provocation is such that complacency is not an option. Increased investment into new technologies and adoption of new agricultural practices with improved adaptive and mitigation potential are both essential. Copyright © 2011 Society of Chemical Industry

For highly polyphagous cotton, Gossypium hirsutum L., pests such as Helicoverpa zea (Boddie), a substantial portion of the larval population develops on noncotton alternative hosts. These noncotton hosts potentially provide a natural refuge for H. zea, thereby slowing the evolution of resistance to the Bacillus thuringiensis Berliner (Bt)-derived Cry1Ac protein present in Bollgard cotton. Here, we demonstrate how the measured contribution of such alternative hosts can be included in estimating the "effective refuge" present for H. zea and in modeling resistance evolution in this species. A single-gene, two-compartment model was used in which one compartment represented corn, Zea mays L., and cotton that express the Cry1Ac protein or similar proteins, and the other compartment was the effective refuge, made up of a weighted average of non-Bt cotton and noncotton hosts. The effective refuge was estimated for each of six generations of H. zea based upon available data on larval population densities on different hosts and cropping patterns. Model runs were performed for regions centered on three states: Georgia, Mississippi, and North Carolina. Three sets of fitness cost assumptions for the putative resistance gene were used: none, low, and moderate, with either recessive or additive inheritance for resistance and fitness costs. For Georgia and North Carolina, resistance was predicted to take >30 yr to evolve except in the absence of fitness costs. For Mississippi, results were sensitive to fitness costs: >30 yr with moderate costs, 7-14 yr with low costs, and 6-10 yr without such costs.

The extent of pollen-mediated gene flow (PMGF) in wheat (Triticum spp. L.) as a function of distance from a pollinator source has been measured in recent field studies. Wheat is primarily self-pollinated; however, some cross-pollination can occur depending on biological, agronomic, and environmental factors. The complexity of these interactions restricts attempts to develop a workable mechanistic model; therefore, we pursued an entirely empirical modeling approach. We fit a simple empirical regression model to all available observed data and then used it to make general predictions about the effects of field size, blending at harvest, and isolation distances on PMGF in wheat. The empirical model was derived by fitting a least squares regression line to the gene flow data when plotted as the logarithm of PMGF versus the square root distance from the edge of the source field. Linear behavior was observed when either the maximum or mean PMGF was plotted in this manner. A "General Wheat Model" (GWM) of this same mathematical form is given which provides a conservative ("high-end") prediction of PMGF in the general case: PMGF (%) = 10(-(0.2radicalx)), where PMGF is the percent gene flow at a particular point in the field (without blending), and x is the distance (m) from the edge of the source field. The GWM was used to show that the effect of source field size is minimal for sources of 10 ha or larger, where asymptotic levels of PMGF are obtained. The model was also applied to show that harvest-blending produces PMGF at the field level 10 to 50 times lower than the highest level observed at the edge of the receptor field. Significantly, isolation buffers of 0 to 10 m were predicted by the GWM to have only a minimal impact on harvest-blended PMGF, when the receptor field had an overall width of 100 m or greater. Without any isolation buffers, the harvest-blended PMGF between neighboring commercial-sized (>10 ha) fields was less than 0.1% (well below commercial thresholds for foreign material in wheat seed and grain). This is also well below any existing standards for labeling the presence of approved biotech traits in food or seed distributed or sold as conventional.

The Acetochlor Registration Partnership conducted a prospective ground water (PGW) monitoring program to investigate acetochlor [2-chloro-N-(ethoxymethyl)-N-(2-ethyl-6-methylphenyl)-acetamide] transport to ground water at eight sites. The distribution of soil textures among these sites was weighted toward coarser soil types, while also including finer-textured soils that dominate most corn (Zea mays L.)-growing areas of the United States. Each site consisted of a 1.2-ha test plot adjacent to a 0.2-ha control plot. Suction lysimeters and monitoring wells were installed at multiple depths within each test and control plot to sample soil-pore water and near-surface ground water. Irrigation was applied to each site during the growing season to ensure water input of 110 to 200% of average historical rainfall. Acetochlor dissipated rapidly from surface soils at all sites with a DT(50) (time for 50% of the initial residues to dissipate) of only 3 to 9 d, but leaching was not an important loss mechanism, with only 0.25% of the 15,312 soil-pore water and ground water samples analyzed containing parent acetochlor at or above 0.05 microg L(-1). However, quantifiable residues of a soil degradation product, acetochlor ethanesulfonic acid, were more common, with approximately 16% of water samples containing concentrations at or above 1.0 microg L(-1). A second soil degradation product, acetochlor oxanilic acid, was present at concentrations at or above 1.0 microg L(-1) in only 0.15% of water samples analyzed. The acetochlor PGW program demonstrated that acetochlor lacks the potential to leach to ground water at detectable concentrations, and when applied in accordance with label restrictions, is unlikely to move to ground water at concentrations hazardous to human health.

A surface drinking water monitoring program for four corn (Zea mays L.) herbicides was conducted during 1995-2001. Stratified random sampling was used to select 175 community water systems (CWSs) within a 12-state area, with an emphasis on the most vulnerable sites, based on corn intensity and watershed size. Finished drinking water was monitored at all sites, and raw water was monitored at many sites using activated carbon, which was shown capable of removing herbicides and their degradates from drinking water. Samples were collected biweekly from mid-March through the end of August, and twice during the off-season. The analytical method had a detection limit of 0.05 microg L(-1) for alachlor [2-chloro-N-(2,6-diethylphenyl)-N-(methoxymethyl)-acetamide] and 0.03 microg L(-1) for acetochlor [2-chloro-N-(ethoxymethyl)-N-(2-ethyl-6-methylphenyl)-acetamide], atrazine [6-chloro-N-ethyl-N'-(1-methylethyl)-1,3,5-triazine-2,4-diamine], and metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)-acetamide]. Of the 16528 drinking water samples analyzed, acetochlor, alachlor, atrazine, and metolachlor were detected in 19, 7, 87, and 53% of the samples, respectively. During 1999-2001, samples were also analyzed for the presence of six major degradates of the chloroacetanilide herbicides, which were detected more frequently than their parent compounds, despite having higher detection limits of 0.1 to 0.2 microg L(-1). Overall detection frequencies were correlated with product use and environmental fate characteristics. Reservoirs were particularly vulnerable to atrazine, which exceeded its 3 microg L(-1) maximum contaminant level at 25 such sites during 1995-1999. Acetochlor annualized mean concentrations (AMCs) did not exceed its mitigation trigger (2 microg L(-1)) at any site, and comparisons of observed levels with standard measures of human and ecological hazards indicate that it poses no significant risk to human health or the environment.

The Acetochlor Registration Partnership (ARP) conducted a 7-yr ground water monitoring program at a total of 175 sites in seven states: Illinois, Indiana, Iowa, Kansas, Minnesota, Nebraska, and Wisconsin. While acetochlor [2-chloro-N-(ethoxymethyl)-N-(2-ethyl-6-methylphenyl)-acetamide] was the primary focus, the analytical methods also quantified alachlor [2-chloro-N-(2,6-diethylphenyl)-N-(methoxymethyl)-acetamide], atrazine [6-chloro-N-ethyl-N'-(1-methylethyl)-1,3,5-triazine-2,4-diamine], metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)-acetamide], and two classes of soil degradates for acetochlor, alachlor, and metolachlor. Ground water samples were collected monthly for five years and quarterly for two additional years. All samples were analyzed for the presence of parent herbicides, and degradates were monitored during the last three years. Parent acetochlor was detected above 0.1 microg L(-1) in three or more samples at just seven sites. Alachlor and metolachlor were also rarely detected, but atrazine was detected in 36% of all samples analyzed. Even more widespread were the tertiary amide sulfonic acid (ethanesulfonic acid, ESA) degradates of acetochlor, alachlor, and metolachlor, which were detected at 81, 76, and 106 sites, respectively. The other class of monitored soil degradates (oxanilic acid, OXA) was detected less frequently, at 26, 16, and 63 sites for acetochlor OXA, alachlor OXA, and metolachlor OXA, respectively. The geographic distribution of detections did not follow the pattern originally expected when the study began. Rather than being a function primarily of soil texture, the detection of these herbicides in shallow ground water was related to site-specific factors associated with local topography, the occurrence of surface water drainage features, irrigation practices, and the vertical positioning of the well screen.

A new regulatory approach is needed to characterize peak pesticide concentrations in surface waters over a range of watershed scales. Methods now in common use rely upon idealized edge-of-field scenarios that ignore scaling effects. Although some watershed-scale regulatory models are available, their complexity generally prevents them from being used duringthe pesticide registration decision process, even though nearly all exposure to both humans and aquatic organisms can occur only at this scale. The theory of fractal geometry offers a simpler method for addressing this regulatory need. Mandelbrot described rivers as "space-filling curves" (Mandelbrot, B. B. The Fractal Geometry of Nature; Freeman: New York, 1983), a class of fractal objects implying two useful properties we exploit in this work. The first is a simple power-law relationship in which log-log plots of maximum daily concentrations as a function of watershed area tend to be linear with a negative slope. We demonstrate that the extrapolation of such plots down to smaller watersheds agrees with edge-of-field concentrations predicted using the Pesticide Root Zone Model, but only when the modeling results are properly adjusted for use intensity within the watershed. We also define a second useful property, "scale-invariant dispersion", in which concentrations are well described by a single analytical solution to the convective--dispersion equation, regardless of scale. Both of these findings make it possible to incorporate the effect of watershed scale directly into regulatory assessments.

A recent (1995–2001) 175-site surface drinking water monitoring programme in the United States showed that one community water system (Nashville, Illinois) was particularly successful at removing chloroacetanilide herbicides and their degradation products from source water. Nashville adds powdered activated carbon (PAC) just prior to a clarifier in which settled solids are recirculated, increasing the PAC residence time. We conducted bench-scale studies to quantify the effects of PAC dose and contact time on removal efficiency. Results indicate that 90% of the parent herbicides and 40–45% of the acetanilide degradation products are removed for a contact time of 60 min and a PAC dose of 20 mg/l, from Nashville, IL, source water. Removal of these compounds by the same PAC dose and contact time was even higher in three other US water sources (Idaho, Kansas, Missouri) and a European (Dutch) water source, generally 60–80% for the degradation products and over 95% for the parent compounds. Removal percentages substantially increased with higher PAC dose and contact time, fell slightly with decreasing pH or higher NOM, but remained constant when the inlet concentration was raised from 2 to 10 µg/l.

In the intensely farmed corn-growing regions of the mid-western USA, surface waters have often been contaminated by herbicides, principally as a result of rainfall runoff occurring shortly after application of these to corn and other crops. In some vulnerable watersheds, water quality criteria for chronic human exposure through drinking water are occasionally exceeded. We selected three settings representative of vulnerable corn-region watersheds, and used the PRZM-EXAMS model with the Index Reservoir scenario to predict corn herbicide concentrations in the reservoirs as a function of herbicide properties and use pattern, site characteristics and weather in the watersheds. We compared herbicide application scenarios, including broadcast surface pre-plant atrazine and alachlor applications with a glyphosate pre-plant application, scenarios in which losses of herbicides were mitigated by incorporation or banding, and scenarios in which only glyphosate or glufosinate post-emergent herbicides were used with corn genetically modified to be resistant to them. In the absence of drift, in almost all years a single runoff event dominates the input into the reservoir. As a result, annual average pesticide concentrations are highly correlated with annual maximum daily values. The modeled concentrations were generally higher than those derived from monitoring data, even for no-drift model scenarios. Because of their lower post-emergent application rates and greater soil sorptivity, glyphosate and glufosinate loads in runoff were generally one-fifth to one-tenth those of atrazine and alachlor. These model results indicate that the replacement of pre-emergent corn herbicides with the post-emergent herbicides allowed by genetic modification of crops would dramatically reduce herbicide concentrations in vulnerable watersheds. Given the significantly lower chronic mammalian toxicity of these compounds, and their vulnerability to breakdown in the drinking water treatment process, risks to human populations through drinking water would also be reduced. © 2001 Society of Chemical Industry

DiGiovanni and Kevan (2008, Environ. Biosafety Res. 7 : 105–108) commented extensively on the empirical approach that I and my co-authors took in our previous modeling of pollen-mediated gene flow in maize (Gustafson et al. (2006) Crop Sci. 46 : 2133–2140). As we detailed in that original paper, gene flow is a highly complex process that necessarily requires at least some level of empiricism in order to adequately quantify all of the biological, meteorological, and physical phenomena that are involved. DiGiovanni and Kevan favor a mechanistic modeling approach, and they proposed a number of potential advantages for such a method over our entirely empirical technique. However, the 20 m buffers we had proposed based on our empirical model continue to be supported by the rapidly growing body of experimental data on maize gene flow that has now been collected in Europe and elsewhere around the world. This does not mean there is no place for mechanistic modeling of gene flow, but it does suggest that properly implemented empirical approaches have a valid role to play. They offer a degree of simplicity and practical utility that is not available from more complicated approaches.

Agreement is developing among agricultural scientists on the emerging inability of agriculture to meet growing global food demands. The lack of additional arable land and availability of freshwater have long been constraints on agriculture. However, the increased frequency of extreme and unpredictable weather events, in a manner consistent with the changes predicted by global climate models, is expected to exacerbate the global food challenge as we move toward the middle of the 21st century. These climate- and constraint-driven crop production challenges are interconnected within a complex global economy, where diverse factors add to price volatility and food scarcity. The present report projects the impact of climate change on food security through the year 2050. The analysis presented here suggests that climate change in the first half of the 21st century does not represent a near-term threat to food security in the US due to the availability of adaptation strategies. However, as climate continues to trend away from 20th century norms current adaptation measures will not be sufficient to enable agriculture to meet growing food demand. High-end projections on carbon emissions will exacerbate the food shortfall, although uncertainty in climate model projections (particularly precipitation) is a limitation to impact studies.

Roundup Ready (glyphosate-resistant) cropping systems enable the use of glyphosate, a non-selective herbicide that offers growers several benefits, including superior weed control, flexibility in weed control timing and economic advantages. The rapid adoption of such crops in North America has resulted in greater glyphosate use and concern over the potential for weed resistance to erode the sustainability of its efficacy. Computer modeling is one method that can be used to explore the sustainability of glyphosate when used in glyphosate-resistant cropping systems. Field tests should help strengthen the assumptions on which the models are based, and have been initiated for this purpose. Empirical evaluations of published data show that glyphosate-resistant weeds have an appearance rate of 0.007, defined as the number of newly resistant species per million acres treated, which ranks low among herbicides used in North America. Modeling calculations and ongoing field tests support a practical recommendation for growers occasionally to include other herbicides in glyphosate-resistant cropping systems, to lower further the potential for new resistance to occur. The presented data suggest that the sustainability of glyphosate in North America would be enhanced by prudent use of additional herbicides in glyphosate-resistant cropping systems.

In both laboratory and field studies, the dissipation of pesticides in soil often fails to follow simple first-order reaction kinetics. This nonlinear behavior has now been described successfully through the use of a new first-order, nonlinear kinetic model. Excellent fits to both laboratory and field data are obtained for all pesticides modeled

For highly polyphagous cotton, Gossypium hirsutum L., pests such as Helicoverpa zea (Boddie), a substantial portion of the larval population develops on noncotton alternative hosts. These noncotton hosts potentially provide a natural refuge for H. zea, thereby slowing the evolution of resistance to the Bacillus thuringiensis Berliner (Bt)-derived Cry1Ac protein present in Bollgard cotton. Here, we demonstrate how the measured contribution of such alternative hosts can be included in estimating the "effective refuge" present for H. zea and in modeling resistance evolution in this species. A single-gene, two-compartment model was used in which one compartment represented corn, Zea mays L., and cotton that express the Cry1Ac protein or similar proteins, and the other compartment was the effective refuge, made up of a weighted average of non-Bt cotton and noncotton hosts. The effective refuge was estimated for each of six generations of H. zea based upon available data on larval population densities on different hosts and cropping patterns. Model runs were performed for regions centered on three states: Georgia, Mississippi, and North Carolina. Three sets of fitness cost assumptions for the putative resistance gene were used: none, low, and moderate, with either recessive or additive inheritance for resistance and fitness costs. For Georgia and North Carolina, resistance was predicted to take30 yr to evolve except in the absence of fitness costs. For Mississippi, results were sensitive to fitness costs:30 yr with moderate costs, 7-14 yr with low costs, and 6-10 yr without such costs.

The article by Swan et al. (2003) suggested that alachlor exposure was linked to reduced sperm quality in fertile men; after publication of the article, Monsanto (St. Louis, MO) began a detailed examination of the issue because the findings were entirely unexpected and inconsistent with both our information and the extensive published literature on alachlor. Most surprisingly, alachlor mercapturate (AM) was reportedly found in the urine of 92% of study participants in Columbia, Missouri. Because this metabolite arises exclusively from exposure to the parent compound, few, if any, detects would be expected based on declining alachlor use (National Agricultural Statistics Service 2005) and our detailed understanding of its biological and environmental properties (Feng et al. 1994). Also, extensive water monitoring studies submitted to the U.S. Environmental Protection Agency (EPA) have shown that parent alachlor occurs very infrequently in both potable wells (Holden et al. 1992) and drinking water from surface water sources (Hackett et al. 2005), thereby calling into question the plausibility of such widespread exposure. We met with Swan and colleagues at the University of Missouri in Columbia (UMC), and with the personnel at the Centers for Disease Control and Prevention (CDC) who conducted the analyses, to discuss our surprise at the findings. Our concern about the reported frequent detections of alachlor in urine was heightened when we learned that the liquid chromatography/mass spectrometry–mass spectrometry method employed by the CDC (Olsson et al. 2004) included no confirmatory ions, a standard technique for avoiding false positives in the analysis of urine (Department of Health and Human Services 1998). An 18-month collaboration ensued, which included numerous discussions and a round-robin study conducted between Monsanto and the CDC, with involvement by UMC researchers, to assess the performance and transferability of the methods used by each laboratory. After successful completion of the round-robin study, several frozen urine samples retained from the original study were sent to Monsanto. In results that we intend to submit for publication, we found no detectable level of AM (limit of detection < 0.10 ppb) in samples that the CDC reported to contain up to 3 ppb (Swan et al. 2003). Sample degradation does not explain this difference, because we have data demonstrating AM stability under such conditions. Our analyses followed Good Laboratory Practice standards [U.S. Environmental Protection Agency (EPA) 1989] and included confirmatory ions. We also analyzed urine samples of 52 volunteers from agricultural areas across North America, none of which actually contained detectable AM, but 11 of which showed false positives when confirmatory ions were not used. The CDC has now modified its method to include confirmatory ions for alachlor. We are confident that little or no AM would have been detected had they included confirmatory ions in the original analysis. The CDC previously declined Monsanto's request that they analyze the original samples using a modified method with confirmatory ions. However, after receiving an earlier version of this letter, the CDC quickly performed new analyses of 14 retained frozen samples and informed us that analysis with confirmatory ions validated their original findings. Unfortunately, the CDC has not provided us with sufficient data to confirm the validity of the new method and results. Monsanto continues to believe the detections are spurious. From our perspective, the only possible resolution of the matter at this time would be for the retained samples to be sent to an independent third-party laboratory for confirmatory analysis. We understand Swan et al. are now having urine samples from other similar agricultural areas analyzed using a confirmatory method, and that AM is no longer being routinely detected. This would affirm that alachlor exposure is rare and the alleged link to semen quality is implausible. It would be very informative to identify the apparent interferent using high-resolution mass spectrometry methodology, but our collaboration has clearly shown that it was not AM. The evidence presented by our analyses of the samples provided by Swan, supported by our successful performance in the round-robin analysis of fortified samples, demonstrates that the reported detections of alachlor were most likely attributable to an interferent. The data refute any link between alachlor exposure and reduced sperm quality in fertile men.

Biomonitoring was used to assess the combined dermal, oral, and inhalation exposure associated with the agricultural use of Harness Plus, an emulsifiable concentrate formulation of the herbicide acetochlor. Twenty Spanish farmers handled and applied acetochlor to maize in the spring of 2003, following the product label recommendations. Open- and closed-cabin applications were equally represented. Urine was collected during six consecutive days, starting the day prior to application. Daily composites were analyzed for 2-ethyl-6-methyl-aniline, a common chemophore representing the major urinary acetochlor metabolites. All applicators showed detectable concentrations in urine after application. Although, the open-cabin applicators treated fewer hectares, they showed significantly higher exposure compared to the closed-cabin applicators (average exposure: 0.004 and 0.002 mg/kg bw/day, respectively). Linear regression analysis suggested that untracked incidents had a significant impact on the total exposure. Other events that may have contributed to the observed exposure are repair of faulty equipment, accidental spillages, splashes, and inadequate use of protective gloves. The average margins of exposure (MOE) for farmers ranged from 23,000 (open cabin) to about 44,000 (closed cabin). For professional applicators the MOEs were 10-fold lower. These MOEs clearly indicate that no adverse health effects should be expected from agricultural acetochlor applications.

An updated empirical approach is proposed for specifying coexistence requirements for geneti- cally modified (GM) maize ( Zea mays L.) produc- tion to ensure compliance with the 0.9% label- ing threshold for food and feed in the European Union. The model improves on a previously published (Gustafson et al., 2006) empirical model by adding recent data sources to supple- ment the original database and including the fol- lowing additional cases: (i) more than one GM maize source field adjacent to the conventional or organic field, (ii) the possibility of so-called "stacked" varieties with more than one GM trait, and (iii) lower pollen shed in the non-GM recep- tor field. These additional factors lead to the possibility for somewhat wider combinations of isolation distance and border rows than required in the original version of the empirical model. For instance, in the very conservative case of a 1-ha square non-GM maize field surrounded on all four sides by homozygous GM maize with 12 m isolation (the effective isolation distance for a single GM field), non-GM border rows of 12 m are required to be 95% confident of gene flow less than 0.9% in the non-GM field (with adventi - tious presence of 0.3%). Stacked traits of higher GM mass fraction and receptor fields of lower pollen shed would require a greater number of border rows to comply with the 0.9% threshold, and an updated extension to the model is pro- vided to quantify these effects.

Surveys of drinking water quality throughout the agricultural regions of the world have revealed the tendency of certain crop protection chemicals to enter water supplies. Fortunately, the trace concentrations that have been detected are generally well below the levels thought to have any negative impact on human health or the environment. However, the public expects drinking water to be pristine and seems willing to bear the costs involved in further regulating agricultural chemical use in such a way so as to eliminate the potential for such materials to occur at any detectable level. Of all the tools available to assess exposure to agricultural chemicals via drinking water, computer models are one of the most cost-effective. Although not sufficiently predictive to be used in the absence of any field data, such computer programs can be used with some degree of certainty to perform quantitative extrapolations and thereby quantify regional exposure from field-scale monitoring information. Specific models and modeling techniques will be discussed for performing such exposure analyses. Improvements in computer technology have recently made it practical to use Monte Carlo and other probabilistic techniques as a routine tool for estimating human exposure. Such methods make it possible, at least in principle, to prepare exposure estimates with known confidence intervals and sufficient statistical validity to be used in the regulatory management of agricultural chemicals.

Agricultural chemicals sporadically occur at detectable levels in the surface waters of intensively farmed watersheds. HSPF, a previously released model of agricultural chemicals in surface water, had been used to predict concentrations which were much higher (10 X) than those actually observed during monitoring studies. A new model, SURFACE, is described here which is much simpler than HSPF and gives better predictions of surface water concentrations. SURFACE uses PRZM, an EPA model, to calculate edge‐of‐field runoff losses and simple hydraulic routing algorithms to determine concentrations at the bottom of large river basins. In water systems sampled during 1985 and 1986, SURFACE predictions of annualized mean concentrations for alachlor, atrazine, cyanazine and metolachlor were within 0.09 ppb half of the time.

The assumption of constant dispersion coefficient is ubiquitous in the modeling of pesticide transport through the root zone. This assumption is critically examined and found to be invalid in most lab and field studies. An improved model is proposed and tested in which it is assumed that the dispersion coefficient grows linearly with time and distance traveled. Ways in which this improved representation of dispersion could be incorporated into existing models of pesticide transport are discussed.

Government agencies at both the state and federal levels now face increasing pressures to assess the likelihood of pesticide occurrence in well‒water supplies. Screening methodologies are required in order to determine which pesticides now in use should receive the greatest attention with respect to groundwater, and in order to determine whether elaborate and expensive groundwater testing should be required in order to register a new pesticide. Several screening techniques have been proposed recently, some based on threshold values for critical physical properties of the pesticide, and others based on mathematical models of the leaching process. A different approach is taken in this paper, whereby an index is derived based entirely on the physical properties of those pesticides that have been found either leachable or essentially immobile. The index is based on graphical examination of a plot formed by two widely available pesticide properties: half‒life in soil (tsoil1/2) and partition coefficient between soil organic carbon and water (Koc). Other physical properties, such as water solubility, octanol/water partition coefficient, and volatility from soil, have often been invoked as indicators of leachability, but they are found in this paper to have no useful power in discriminating between “leachers” and “nonleachers.” Scores assigned with the new screening index agree with the results of several recent well‒water monitoring programs, even though point‒source events are thought to be responsible for some of the observed contamination. A nomogram is given that reduces the task of calculating the index to simply placing a straight edge on a diagram.

Reforestation efforts throughout the world are often hindered by animal browse damage. Numerous harmful natural phenomena affect seedling growth, including nutrient deficiencies, competing vegetation, insects, disease, and drought. However, animal damage is often found to have the most severely deleterious effects on the tree. Loss of time in reestablishing trees on harvested sites can necessitate costly replanting practices. The financial incentive for protecting seedlings has led to the development of several mechanical and chemical repellent systems.