Ecosystem resilience despite large-scale altered hydroclimatic conditions.

Climate change is predicted to increase both drought frequency and duration, and when coupled with substantial warming, will establish a new hydroclimatological model for many regions. Large-scale, warm droughts have recently occurred in North America, Africa, Europe, Amazonia and Australia, resulting in major effects on terrestrial ecosystems, carbon balance and food security. Here we compare the functional response of above-ground net primary production to contrasting hydroclimatic periods in the late twentieth century (1975-1998), and drier, warmer conditions in the early twenty-first century (2000-2009) in the Northern and Southern Hemispheres. We find a common ecosystem water-use efficiency (WUE(e): above-ground net primary production/evapotranspiration) across biomes ranging from grassland to forest that indicates an intrinsic system sensitivity to water availability across rainfall regimes, regardless of hydroclimatic conditions. We found higher WUE(e) in drier years that increased significantly with drought to a maximum WUE(e) across all biomes; and a minimum native state in wetter years that was common across hydroclimatic periods. This indicates biome-scale resilience to the interannual variability associated with the early twenty-first century drought--that is, the capacity to tolerate low, annual precipitation and to respond to subsequent periods of favourable water balance. These findings provide a conceptual model of ecosystem properties at the decadal scale applicable to the widespread altered hydroclimatic conditions that are predicted for later this century. Understanding the hydroclimatic threshold that will break down ecosystem resilience and alter maximum WUE(e) may allow us to predict land-surface consequences as large regions become more arid, starting with water-limited, low-productivity grasslands.

Development and Assessment of the SMAP Enhanced Passive Soil Moisture Product.

Launched in January 2015, the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) observatory was designed to provide frequent global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using a radar and a radiometer operating at L-band frequencies. Despite a hardware mishap that rendered the radar inoperable shortly after launch, the radiometer continues to operate nominally, returning more than two years of science data that have helped to improve existing hydrological applications and foster new ones. Beginning in late 2016 the SMAP project launched a suite of new data products with the objective of recovering some high-resolution observation capability loss resulting from the radar malfunction. Among these new data products are the SMAP Enhanced Passive Soil Moisture Product that was released in December 2016, followed by the SMAP/Sentinel-1 Active-Passive Soil Moisture Product in April 2017. This article covers the development and assessment of the SMAP Level 2 Enhanced Passive Soil Moisture Product (L2_SM_P_E). The product distinguishes itself from the current SMAP Level 2 Passive Soil Moisture Product (L2_SM_P) in that the soil moisture retrieval is posted on a 9 km grid instead of a 36 km grid. This is made possible by first applying the Backus-Gilbert optimal interpolation technique to the antenna temperature (TA) data in the original SMAP Level 1B Brightness Temperature Product to take advantage of the overlapped radiometer footprints on orbit. The resulting interpolated TA data then go through various correction/calibration procedures to become the SMAP Level 1C Enhanced Brightness Temperature Product (LiC_TB_E). The LiC_TB_E product, posted on a 9 km grid, is then used as the primary input to the current operational SMAP baseline soil moisture retrieval algorithm to produce L2_SM_P_E as the final output. Images of the new product reveal enhanced visual features that are not apparent in the standard product. Based on in situ data from core validation sites and sparse networks representing different seasons and biomes all over the world, comparisons between L2_SM_P_E and in situ data were performed for the duration of April 1, 2015 - October 30, 2016. It was found that the performance of the enhanced 9 km L2_SM_P_E is equivalent to that of the standard 36 km L2_SM_P, attaining a retrieval uncertainty below 0.040 m3/m3 unbiased root-mean-square error (ubRMSE) and a correlation coefficient above 0.800. This assessment also affirmed that the Single Channel Algorithm using the V-polarized TB channel (SCA-V) delivered the best retrieval performance among the various algorithms implemented for L2_SM_P_E, a result similar to a previous assessment for L2_SM_P.

Indicators of water use efficiency across diverse agroecosystems and spatiotemporal scales.

Understanding the relationship between water and production within and across agroecosystems is essential for addressing several agricultural challenges of the 21st century: providing food, fuel, and fiber to a growing human population, reducing the environmental impacts of agricultural production, and adapting food systems to climate change. Of all human activities, agriculture has the highest demand for water globally. Therefore, increasing water use efficiency (WUE), or producing 'more crop per drop', has been a long-term goal of agricultural management, engineering, and crop breeding. WUE is a widely used term applied across a diverse array of spatial scales, spanning from the leaf to the globe, and over temporal scales ranging from seconds to months to years. The measurement, interpretation, and complexity of WUE varies enormously across these spatial and temporal scales, challenging comparisons within and across diverse agroecosystems. The goals of this review are to evaluate common indicators of WUE in agricultural production and assess tradeoffs when applying these indicators within and across agroecosystems amidst a changing climate. We examine three questions: (1) what are the uses and limitations of common WUE indicators, (2) how can WUE indicators be applied within and across agroecosystems, and (3) how can WUE indicators help adapt agriculture to climate change? Addressing these agricultural challenges will require land managers, producers, policy makers, researchers, and consumers to evaluate costs and benefits of practices and innovations of water use in agricultural production. Clearly defining and interpreting WUE in the most scale-appropriate way is crucial for advancing agroecosystem sustainability.

Uncertainty in phosphorus fluxes and budgets across the US long-term agroecosystem research network.

Phosphorus (P) budgets can be useful tools for understanding nutrient cycling and quantifying the effectiveness of nutrient management planning and policies; however, uncertainties in agricultural nutrient budgets are not often quantitatively assessed. The objective of this study was to evaluate uncertainty in P fluxes (fertilizer/manure application, atmospheric deposition, irrigation, crop removal, surface runoff, and leachate) and the propagation of these uncertainties to annual P budgets. Data from 56 cropping systems in the P-FLUX database, which spans diverse rotations and landscapes across the United States and Canada, were evaluated. Results showed that across cropping systems, average annual P budget was 22.4 kg P ha-1 (range = -32.7 to 340.6 kg P ha-1 ), with an average uncertainty of 13.1 kg P ha-1 (range = 1.0-87.1 kg P ha-1 ). Fertilizer/manure application and crop removal were the largest P fluxes across cropping systems and, as a result, accounted for the largest fraction of uncertainty in annual budgets (61% and 37%, respectively). Remaining fluxes individually accounted for <2% of the budget uncertainty. Uncertainties were large enough that determining whether P was increasing, decreasing, or not changing was inconclusive in 39% of the budgets evaluated. Findings indicate that more careful and/or direct measurements of inputs, outputs, and stocks are needed. Recommendations for minimizing uncertainty in P budgets based on the results of the study were developed. Quantifying, communicating, and constraining uncertainty in budgets among production systems and multiple geographies is critical for engaging stakeholders, developing local and national strategies for P reduction, and informing policy.

Breast cancer, placing drug interactions in the spotlight: is polypharmacy the cause of everything?

PURPOSE: Breast cancer is the most prevalent and lethal cancer among women. Forty-one percent of cases occur in people ≥ 70 years, hindering their treatment given its comorbidities and polypharmacy (PP). Potential drug-drug interactions (PDDI) were analyzed in elderly breast cancer patients between daily and oncospecific treatments and their associations with Age, BMI, Mini Nutritional Assessment (MNA), Frailty categorization, PP, and adverse effects. PATIENTS/METHODS: A cohort of 77 patients ≥ 70 years with breast cancer who underwent a Comprehensive Geriatric Assessment (CGA) were included. Clinical characteristics were collected using medical records. PDDI between treatments were analyzed using two databases. Data were assessed using linear regression, Chi-square, Mann-Whitney U, and Kruskal-Wallis tests. Finally, a multivariate logistic regression model was built and tested to predict adverse effects. RESULTS: From 719 PDDI, 530 (74%) were moderate (r2 = 0.72) and the median number of drugs during oncospecific treatment (r2 = 0.73) was 9 (range 3-26). Overall, 59 patients (77%) had adverse effects associated with Frailty categorization and MNA (p < 0.05). The distribution of major, moderate, minor, and total PDDI was associated with PP at CGA and during oncospecific treatment (p < 0.05). Moreover, it was verified that Frailty categorization protects from adverse effects given the intervention made at CGA. CONCLUSIONS: CGA should be applied in oncologic elderly patients to assess clinical outcomes and categorize them according to their frailty but also to analyze PDDI. Furthermore, we encourage the use of the model in clinical practice for predicting the occurrence of adverse effects, improving therapeutic conciliation.

Patient Reported Outcomes in Microbial Keratitis.

PURPOSE: The aim of this investigation was to study the patient-reported outcomes of patients with microbial keratitis (MK) using the 9-item National Eye Institute-Visual Function Questionnaire (NEI VFQ-9). METHODS: Using the Sight Outcomes Research Collaborative ophthalmology electronic health record repository, patients with MK and control patients who completed the NEI VFQ-9 within 7 days of their appointment were identified. The questionnaire is scored as a mean of the 9 items on a scale from 0 to 100, with higher scores indicating better functioning. Composite and individual item scores were compared between groups using the analysis of variance. RESULTS: In total, 916 questionnaires were completed from patients with acute MK (n = 84), nonacute MK (n = 30), MK with a corneal transplant (n = 21), from controls seen in a satellite comprehensive ophthalmology clinic (n = 528), and controls seen at a subspecialty ophthalmology clinic (n = 253). The mean NEI VFQ-9 composite scores per group were 66.6 (SD = 26.8), 78.1 (SD = 17.1), 58.6 (SD =21.6), 88.0 (SD = 10.2), and 83.5 (SD = 13.0), respectively (P < 0.0001). Both patients with acute MK and patients with MK requiring transplant reported significantly worse function than nonacute MK, comprehensive, and specialty patients. Patients with nonacute MK reported significantly worse function than comprehensive control patients (all Tukey-adjusted P < 0.05). DISCUSSION: Patients who had or eventually require corneal transplant for management of their MK report worse visual function than patients with nonacute MK. This may be important in helping physicians counsel their patients.

Responses to environmental variability by herbivorous insects and their natural enemies within a bioenergy crop, Miscanthus x giganteus.

Precision agriculture (PA) is the application of management decisions based on identifying, quantifying, and responding to space-time variability. However, knowledge of crop pest responses to within-field environmental variability, and the spatial distribution of their natural enemies, is limited. Quantitative methods providing insights on how pest-predator relationships vary within fields are potentially important tools. In this study, phloem feeders and their natural enemies, were observed over two years across 81 locations within a field of the perennial feedstock grass in Georgia, USA. Geographically weighted regression (GWR) was used to spatially correlate their abundance with environmental factors. Variables included distance to forest edge, Normalized Difference of Vegetation Index (NDVI), slope, aspect, elevation, soil particle size distribution, and weather values. GWR methods were compared with generalized linear regression methods that do not account for spatial information. Non-spatial models indicated positive relationships between phloem-feeder abundance and wind speed, but negative relationships between elevation, proportions of silt and sand, and NDVI. With data partitioned into three seasonal groups, terrain and soil variables remained significant, and natural enemies and spiders became relevant. Results from GWR indicated that magnitudes and directions of responses varied within the field, and that relationships differed among seasons. Strong negative relationships between response and explanatory factors occurred: with NDVI during mid-season; with percent silt, during mid-, and late seasons; and with spider abundance during early and late seasons. In GWR models, slope, elevation, and aspect were mostly positive indicating further that associations with elevation depended on whether models incorporated spatial information or not. By using spatially explicit models, the analysis provided a complex, nuanced understanding of within-field relationships between phloem feeders and environmental covariates. This approach provides an opportunity to learn about the variability within agricultural fields and, with further analysis, has potential to inform and improve PA and habitat management decisions.

The contrast diversity effect: Increasing the diversity of contrast examples increases generalization from a single item.

In five experiments, we established and explored the contrast diversity effect-the effect of diversity of negative evidence on inductive inferences drawn from a single observation of a target exemplar. In Experiments 1 through 3, we show that increasing the diversity of negative evidence in a contrasting category led people to infer that a target exemplar corresponded to a higher level category and led to greater generalization of a novel property associated with the target. Further, we demonstrated two boundary conditions in which the effect only occurred when the negative evidence was consistent with a higher level category that both united the contrast exemplars and distinguished them from the target (Experiment 4) and when the negative evidence and the target shared an obvious parent category (Experiment 5). Taken together, these findings demonstrate that increasing the diversity of negative evidence alone increases generalization from a target so long as the negative evidence is drawn from a single contrast category that excludes, but shares a common parent with, the target. Implications for general theories of induction are discussed. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Riparian land cover and hydrology influence stream dissolved organic matter composition in an agricultural watershed.

Dissolved organic matter (DOM) represents an essential component of the carbon cycle and controls biogeochemical and ecological processes in aquatic systems. The composition and reactivity of DOM are determined by the spatial distribution of its sources and its residence time in a watershed. While the effects of agricultural land cover on DOM quality have been reported across spatial and temporal scales, the influence of riparian land cover on stream DOM composition has received little attention. Furthermore, the combined effects of riparian land cover and streamflow rates on DOM composition require investigation. To this end, a multi-year (2016-2018) DOM characterization study was conducted using bi-weekly water samples collected from seven sub-watersheds nested within the Little River Experimental Watershed (LREW) near Tifton, Georgia, USA. DOM optical properties were determined to assess compositional variations using UV-Vis and excitation-emission matrix (EEM) fluorescence spectroscopy coupled with parallel factor (PARAFAC) analysis. PARAFAC analysis indicated that DOM in the LREW was dominated by three humic-like fluorescing components of terrestrial, microbial, and anthropogenic origin and a protein-like component. DOM composition was influenced by riparian land cover and hydrology, and shifted towards recently produced, low molecular weight DOM with low aromaticity as the percentage of agricultural land within riparian wetlands increased. During periods of high discharge and high baseflow, the DOM pool was dominated by recalcitrant and terrestrial-derived material but shifted towards protein-like and microbial-derived with increasing cropland in the riparian area. The results of this two-year study indicate that the replacement of forested riparian buffers with agricultural land can result in altered DOM composition which may affect carbon cycling and downstream water quality in agricultural watersheds.

Method to Evaluate the Age of Groundwater Inputs to Surface Waters by Determining the Chirality Change of Metolachlor Ethanesulfonic Acid (MESA) Captured on a Polar Organic Chemical Integrative Sampler (POCIS).

We previously discovered a method to estimate the groundwater mean residence time using the changes in the enantiomeric ratio of metolachlor ethanesulfonic acid (MESA), (2-[(2-ethyl-6-methylphenyl)(2-methoxy-1-methylethyl)amino]-2-oxoethanesulfonic acid), a metabolite of the herbicide metolachlor. However, many grab samples would be needed for each watershed over an extended period, and this is not practical. Thus, we examined the use of a polar organic chemical integrative sampler (POCIS) deployed for 28 days combined with a modified liquid chromatography-mass spectrometry LC-MS/MS method to provide a time-weighted average of the MESA enantiomeric ratio. POCISs equipped with hydrophilic-lipophilic-balanced (HLB) discs were deployed at five sites across the United States where metolachlor was used before and after 1999 and compared the effectiveness of the POCIS to capture MESA versus grab samples. In addition, an in situ POCIS sampling rate (Rs) for MESA was calculated (0.15 L/day), the precision of MESA extraction from stored POCIS discs was determined, and the effectiveness of HLB to extract MESA was examined. Finally, using molecular modeling, the influence of the asymmetric carbon of metolachlor degradation on the MESA enantiomeric ratio was predicted to be negligible. Results of this work will be used in projects to discern the groundwater mean residence times, to evaluate the delivery of nitrate-N from groundwater to surface waters under various soil, agronomic, and land use conditions, and to examine the effectiveness of conservation practices.

Roflumilast increases Clara cell secretory protein in cigarette smoke-exposed mice.

Decreased Clara cell secretory protein (CCSP) levels have been found in smokers and chronic obstructive pulmonary disease (COPD) patients, which may be related to the development of COPD. A phosphodiesterase-4 (PDE4) inhibitor, roflumilast, appears to have therapeutic value for COPD. However, its effect on CCSP in cigarette smoke (CS)-exposed lungs has not been investigated. AKR/J mice were treated as follows: air control, CS, roflumilast plus CS, and roflumilast. Mice underwent four weeks of air or CS exposure. Roflumilast was administrated at 5mg/kg via gavage once daily for the duration of the study. CCSP levels in bronchoalveolar lavage (BAL) fluid and ERK1/2 activation in lungs were examined. CS exposure tended to decrease CCSP levels in BAL fluid compared to air controls. Treatment with roflumilast significantly reversed CS-induced downward trend of CCSP in BAL fluid. Roflumilast significantly inhibited CS-induced upward trend of ERK1/2 activation in lungs, and the levels of activated ERK1/2 in lungs negatively correlated with CCSP levels of BAL fluid in CS, and CS plus roflumilast groups. Our results demonstrate that one of the therapeutic mechanisms of roflumilast is to reverse CS-induced downward trend in CCSP levels of BAL fluid, which may be mediated by down-regulating ERK1/2 activity.

Evaluation of miscanthus productivity and water use efficiency in southeastern United States.

Second generation biofuels, such as perennial grasses, have potential to provide biofuel feedstock while growing on degraded land with minimal inputs. Perennial grasses have been reported to sequester large amounts of soil organic carbon (SOC) in the Midwestern United States (USA). However, there has been little work on biofuel and carbon sequestration potential of perennial grasses in the Southeastern US. Biofuel productivity for dryland Miscanthus × gigantus and irrigated maize in Georgia, USA were quantified using eddy covariance observations of evapotranspiration (ET) and net ecosystem exchange (NEE) of carbon. Miscanthus biomass yield was 15.54 Mg ha-1 in 2015 and 11.80 Mg ha-1 in 2016, while maize produced 30.20 Mg ha-1 of biomass in 2016. Carbon budgets indicated that both miscanthus and maize fields lost carbon over the experiment. The miscanthus field lost 5 Mg C ha-1 in both 2015 and 2016 while the maize field lost 1.37 Mg C ha-1 for the single year of study. Eddy covariance measurement indicated that for 2016 the miscanthus crop evapotranspired 598 mm and harvest water use efficiencies ranged from 6.95 to 13.84 kg C ha-1 mm-1. Maize evapotranspired 659 mm with a harvest water use efficiency of 19.12 kg C ha-1 mm-1. While biomass yields and gross primary production were relatively high, high ecosystem respiration rates resulted in a loss of ecosystem carbon. Relatively low biomass production, low water use efficiency and high respiration for Miscanthus × gigantus in this experiment suggest that this strain of miscanthus may not be well-suited for dryland production under the environmental conditions found in South Georgia USA.

Herbicide incorporation by irrigation and tillage impact on runoff loss.

Runoff from farm fields is a common source of herbicide residues in surface waters. Incorporation by irrigation has the potential to reduce herbicide runoff risks. To assess impacts, rainfall was simulated on plots located in a peanut (Arachis hypogaea L.) field in Georgia's Atlantic Coastal Plain region after pre-emergence application of metolachlor (2-chloro-N-(2-ethyl-6-methylphenyl)-N-[(1S)-2-methoxy-1-methylethyl]-acetamide) and pendimethalin (N-(1-ethylpropyl)-3,4-dimethyl-2,6-dinitro-benzenamine). Runoff, sediment, and herbicide loss as function of strip tillage (ST) versus conventional tillage (CT) were compared with and without irrigation (12.5 mm) after application of an herbicide tank mixture. For the CT system, metolachlor runoff was reduced 2x and pendimethalin 1.2x when compared with the non-irrigated treatment. The difference in irrigated and non-irrigated metolachlor means was significant (P = 0.05). Irrigation reduced metolachlor runoff by 1.3x in the ST system, but there was a 1.4x increase for pendimethalin. Overall results indicated that irrigation incorporation reduces herbicide runoff with the greatest impact when CT is practiced and products like metolachlor, which have relatively low K(oc) and high water solubility, are used. The lower ST system response was likely due to a combination of spray interception and retention by the ST system cover crop mulch and higher ST soil organic carbon content and less total runoff. During the study, the measured K(oc) of both herbicides on runoff sediment was found to vary with tillage and irrigation after herbicide application. Generally, K(oc) was higher for ST sediment and when irrigation incorporation was used with the CT system. These results have significant implications for simulation model parametization.

Summer cover crops reduce atrazine leaching to shallow groundwater in southern Florida.

At Florida's southeastern tip, sweet corn (Zea Mays) is grown commercially during winter months. Most fields are treated with atrazine (6-chloro-N-ethyl-N'-[1-methylethyl]-1,3,5-triazine-2,4-diamine). Hydrogeologic conditions indicate a potential for shallow groundwater contamination. This was investigated by measuring the parent compound and three degradates--DEA (6-chloro-N-[1-methylethyl]-1,3,5-triazine-2,4-diamine), DIA (6-chloro-N-ethyl)-1,3,5-triazine-2,4-diamine, and HA (6-hydroxy-N-[1-methylethyl]-1,3,5-triazine-2,4-diamine)--in water samples collected beneath sweet corn plots treated annually with the herbicide. During the study, a potential mitigation measure (i.e., the use of a cover crop, Sunn Hemp [Crotalaria juncea L.], during summer fallow periods followed by chopping and turning the crop into soil before planting the next crop) was evaluated. Over 3.5 yr and production of four corn crops, groundwater monitoring indicated leaching of atrazine, DIA, and DEA, with DEA accounting for more than half of all residues in most samples. Predominance of DEA, which increased after the second atrazine application, was interpreted as an indication of rapid and extensive atrazine degradation in soil and indicated that an adapted community of atrazine degrading organisms had developed. A companion laboratory study found a sixfold increase in atrazine degradation rate in soil after three applications. Groundwater data also revealed that atrazine and degradates concentrations were significantly lower in samples collected beneath cover crop plots when compared with concentrations below fallow plots. Together, these findings demonstrated a relatively small although potentially significant risk for leaching of atrazine and its dealkylated degradates to groundwater and that the use of a cover crop like Sunn Hemp during summer months may be an effective mitigation measure.

Do Americans Have a Preference for Rule-Based Classification?

Six experiments investigated variables predicted to influence subjects' tendency to classify items by a single property (rule-based responding) instead of overall similarity, following the paradigm of Norenzayan et al. (, Cognitive Science), who found that European Americans tended to give more "logical" rule-based responses. However, in five experiments with Mechanical Turk subjects and undergraduates at an American university, we found a consistent preference for similarity-based responding. A sixth experiment with Korean undergraduates revealed an effect of instructions, also reported by Norenzayan et al., in which classification instructions led to majority rule-based responding but similarity instructions led to overall similarity grouping. Our American subjects showed no such difference and used similarity more overall. We conclude that Americans do not have a preference for rule responding in classification and discuss the differences between tasks that reliably show strong rule or unidimensional preferences (category construction and category learning) in contrast to this classification paradigm.

Data Assimilation to extract Soil Moisture Information from SMAP Observations.

This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP) observations. Neural Network (NN) and physically-based SMAP soil moisture retrievals were assimilated into the NASA Catchment model over the contiguous United States for April 2015 to March 2017. By construction, the NN retrievals are consistent with the global climatology of the Catchment model soil moisture. Assimilating the NN retrievals without further bias correction improved the surface and root zone correlations against in situ measurements from 14 SMAP core validation sites (CVS) by 0.12 and 0.16, respectively, over the model-only skill and reduced the surface and root zone ubRMSE by 0.005 m3 m-3 and 0.001 m3 m-3, respectively. The assimilation reduced the average absolute surface bias against the CVS measurements by 0.009 m3 m-3, but increased the root zone bias by 0.014 m3 m-3. Assimilating the NN retrievals after a localized bias correction yielded slightly lower surface correlation and ubRMSE improvements, but generally the skill differences were small. The assimilation of the physically-based SMAP Level-2 passive soil moisture retrievals using a global bias correction yielded similar skill improvements, as did the direct assimilation of locally bias-corrected SMAP brightness temperatures within the SMAP Level-4 soil moisture algorithm. The results show that global bias correction methods may be able to extract more independent information from SMAP observations compared to local bias correction methods, but without accurate quality control and observation error characterization they are also more vulnerable to adverse effects from retrieval errors related to uncertainties in the retrieval inputs and algorithm. Furthermore, the results show that using global bias correction approaches without a simultaneous re-calibration of the land model processes can lead to a skill degradation in other land surface variables.

Combined effects of constant versus variable intensity simulated rainfall and reduced tillage management on cotton preemergence herbicide runoff.

Pesticide runoff research relies heavily on rainfall simulation experiments. Most are conducted at a constant intensity, i.e., at a fixed rainfall rate; however, large differences in natural rainfall intensity is common. To assess implications we quantified runoff of two herbicides, fluometuron and pendimethalin, and applied preemergence after planting cotton on Tifton loamy sand. Rainfall at constant and variable intensity patterns representative of late spring thunderstorms in the Atlantic Coastal Plain region of Georgia (USA) were simulated on 6-m2 plots under strip- (ST) and conventional-tillage (CT) management. The variable pattern produced significantly higher runoff rates of both compounds from CT but not ST plots. However, on an event-basis, runoff totals (% applied) were not significantly different, with one exception: fluometuron runoff from CT plots. There was about 25% more fluometuron runoff with the variable versus the constant intensity pattern (P = 0.10). Study results suggest that conduct of simulations using variable intensity storm patterns may provide more representative rainfall simulation-based estimates of pesticide runoff and that the greatest impacts will be observed with CT. The study also found significantly more fluometuron in runoff from ST than CT plots. Further work is needed to determine whether this behavior may be generalized to other active ingredients with similar properties [low K(oc) (organic carbon partition coefficient) approximately 100 mL g(-1); high water solubility approximately 100 mg L(-1)]. If so, it should be considered when making tillage-specific herbicide recommendations to reduce runoff potential.

Field and Laboratory Dissipation of the Herbicide Fomesafen in the Southern Atlantic Coastal Plain (USA).

To control weeds with evolved resistance to glyphosate, Southeastern (USA) cotton farmers have increased fomesafen (5-(2-chloro-α,α,α-trifluoro-p-tolyloxy)-N-mesyl-2-nitrobenzamide) use. To refine fomesafen risk assessments, data are needed that describe its dissipation following application to farm fields. In our study, relatively low runoff rates and transport by lateral subsurface flow, <1.0 and 0.15% of applied respectively, were observed. The low runoff rate was linked to postapplication irrigation incorporation and implementation of a common conservation tillage practice. Moderate soil persistence (t1/2 = 100 days) was indicated in laboratory incubations with surface soil, however, analysis of soil cores from treated plots showed that ≈3% of fomesafen applied persisted in subsoil >3 years after application. Findings suggest low potential for fomesafen movement from treated fields, however, the fate of fomesafen that accumulated in subsoil and the identity of degradates are uncertain. Soil and water samples were screened for degradates, but, none were detected.

Tillage impact on herbicide loss by surface runoff and lateral subsurface flow.

There is worldwide interest in conservation tillage practices because they can reduce surface runoff, and agrichemical and sediment losses from farm fields. Since these practices typically increase infiltration, their use may increase subsurface transport of water-soluble contaminants. Thus, to assess long-term environmental benefits of conservation tillage data may be needed that quantify both surface and subsurface contaminant fluxes. This study focused on the herbicide fluometuron (N,N-dimethyl-N'-[3-(trifluoromethyl)phenyl]-urea) and its soil degradate DMF (N-methyl-N'-[3-(trifluoromethyl) phenyl]-urea). Both compounds are classed as "leachable". They were measured for 10 years in surface runoff and lateral subsurface flow from paired fields located on a hill slope in the Atlantic Coastal Plain region of the southeastern USA. One group of fields was conventionally tilled incorporating all crop residues into soil prior to planting. The second was strip tilled, a common conservation tillage practice. Seven fluometuron applications were made to cotton (Gossypium hirsutum) produced in rotation with peanut (Arachis hypogea). Combined fluometuron and DMF surface and subsurface losses from the conventionally tilled fields were equivalent to 1.2% and 0.13% of fluometuron applied and 0.31% and 0.32% from the strip tilled fields. Annual surface runoff losses were significantly greater from the conventionally tilled fields while the strip tilled fields had significantly greater annual subsurface losses. Results demonstrated that shifting from conventional to conservation tillage management of farm fields in this landscape will reduce surface runoff losses of herbicides like fluometuron but subsurface losses will likely increase. The same trends can be expected in landscapes with similar soil and hydrologic properties. This should be considered when planning implementation of programs that promote conservation tillage use.

Dissipation of the defoliant tribufos in cotton-producing soils.

Soil dissipation of the cotton defoliant tribufos was measured in laboratory incubations and on 0.2-ha research plots. Computed 50% dissipation time (DT(50)) using nonlinear and linear kinetic models ranged from 1 to 19 days. Data indicated that exchangeable soil aluminum inhibited tribufos-degrading soil organisms. Nevertheless, measured DT(50) values were 40 to 700 times less than the aerobic soil half-life (t(1/2)) values used in recent tribufos risk assessments. DT(50) values suggest that risk estimates were overstated. However, edge-of-field runoff concentrations measured on research plots exceeded invertebrate LOECs, thus some aquatic risk is indicated. Field data also suggested that volatilization may be a significant soil dissipation pathway. From this result, we conclude that volatilization should be included in simulation models used for pesticide registration. This will likely improve the accuracy of model outputs for products such as tribufos. Potential volatilization losses indicate a need to evaluate the atmospheric behavior of tribufos.