George W. Mueller-Warrant

A hybrid genetic algorithm for multiobjective problems with activity analysis-based local search

The objective of this research was the development of a method that integrated an activity analysis model of profits from production with a biophysical model, and included the capacity for optimization over multiple objectives. We specified a hybrid genetic algorithm using activity analysis as a local search method, and NSGA-II for calculation of the multiple objective Pareto optimal set. We describe a parallel computing approach to computation of the genetic algorithm, and apply the algorithm to evaluation of an input tax to regulate pollution from agricultural production.

psbA Mutation (valine219 to isoleucine) in Poa annua resistant to metribuzin and diuron

The herbicide-binding region of the chloroplast psbA gene from a total of 20 biotypes of Poa annua L resistant and susceptible to metribuzin and diuron was selectively amplified using PCR. Sequence analysis of the fragment from six herbicide-resistant biotypes of P annua exhibited a substitution from valine to isoleucine at position 219 of the D1 protein encoded by the psbA gene. This is the same mutation as reported for Chlamydomonas and Synechococcus through site-directed mutagenesis and in cell cultures of Chenopodium rubrum L. To our knowledge this is the first report of a higher plant exhibiting resistance in the field to photosystem II inhibitors due to a psbA mutation other than at position 264. The existence of additional biotypes of P annua resistant to diuron or metribuzin but lacking mutation in the herbicide-binding region indicates that resistance to these herbicides can also be attained by other mechanisms. # 2000 Society of Chemical Industry

Genetic diversity of Poa annua in western Oregon grass seed crops.

Abstract The genetic diversity of Poa annua L.populations collected from western Oregon grass-seed fields was surveyed using 18 randomly amplified polymorphic DNA (RAPD) markers. Markers from 1357 individual plants from 47 populations collected at three sampling dates (fall, winter, and spring) for 16 sites were used to measure genetic diversity within and among populations. Site histories varied from low to high herbicide selection pressure, and some sites were subdivided by 3 years of differing post-harvest residue management. Gene diversity statistics, simple frequency of haplotype occurrence, and analysis of molecular variance (AMOVA) revealed the presence of significant variability in P. annua among sites, among collection dates within sites, and within collection dates. Nei gene-diversity statistics and population-differentiation parameters indicated that P. annua populations were highly diverse. Mean Nei gene diversity (h) for all 47 populations was 0.241 and total diversity (HT) was 0.245. A greater proportion of this diversity, however, was within (HS=0.209) rather than among (GST=0.146) populations. When populations were grouped by season of collection, within-group diversity was HS=0.241, while among-group diversity was GST=0.017. When populations were grouped by site, within-group diversity was HS=0.224, while among-group diversity was GST=0.087. The diversity among populations within season for fall, winter, and spring collections was GST=0.121, 0.142, and 0.133, respectively. Populations collected from fields with histories of high herbicide selection pressure showed low differentiation among collection dates, with GST as low as 0.016, whereas those collected from fields with low herbicide selection pressure showed greater differentiation among collection dates, with GST as high as 0.125. At high selection-pressure sites, populations were also lower in gene diversity (as low as h=0.155), while at low selection-pressure sites there was higher gene diversity (as high as h=0.286). The site to site variability was greater for the high selection-pressure sites (GST=0.107 or 69% of the total among-population variance), while the season of germination variability was greater at sites of low herbicide-selection pressure (GST=0.067, or 70% of the total among-population variance). High initial diversity coupled with a long-term re-supply of genotypes from the seed bank must have been factors in maintaining the genetic diversity of this weed despite the intensive use of herbicides. Knowledge of the genetic diversity of Willamette Valley P. annua should help in formulating more effective strategies for managing this weed.

Impact of land use patterns and agricultural practices on water quality in the Calapooia River Basin of western Oregon

Agricultural practices, including tillage, fertilization, and residue management, can affect surface runoff, soil erosion, and nutrient cycling. These processes, in turn, may adversely affect (1) quality of aquatic resources as habitat for amphibians, fish, and invertebrates, (2) costs of treating surface and ground water to meet drinking water standards, and (3) large-scale biogeochemistry. This study characterized the surface water sources of nitrogen (N) (total, nitrate [NO3−], ammonium [NH4+], and dissolved organic N) and sediment active within 40 subbasins of the Calapooia River Basin in western Oregon in monthly samples over three cropping years. The subbasins included both independent and nested drainages, with wide ranges in tree cover, agricultural practices, slopes, and soils. Sediment and N form concentrations were tested against weather and agricultural practice variables. Subbasin land use ranged from 96% forest to 100% agriculture. Average slopes varied from 1.3% to 18.9%, and surface water quality ranged from 0.5 to 43 mg L−1 (ppm) total N maxima and 29 to 249 mg L−1 suspended sediment maxima. Total N during the winter was positively related to percentage landcover of seven common agricultural crops (nongrass seed summer annuals, established seed crops of perennial ryegrass [Lolium perenne L.], tall fescue [Schedonorus phoenix {Scop.} Holub], orchardgrass [Dactylis glomerata L.], clover [Trifolium spp.], and newly planted stands of perennial ryegrass and clover) and negatively related to cover by trees and one seed crop, Italian (annual) ryegrass (Lolium multiflorum). Results for NO3− and total N were highly similar. Sediment concentrations were most strongly related to rainfall totals during periods of 4 and 14 days prior to sampling, with smaller effects of soil disturbance. Fourier analysis of total N over time identified four prominent groups of subbasins: those with (1) low, (2) medium, and (3) high impacts of N (up to 2, 8, and 21 mg L−1, respectively) and a strong cyclical signal peaking in December and (4) those with very high impact of N (up to 43 mg L−1) and a weak time series signal. Preponderance of N in streams draining agriculturally dominated subbasins was in the form of the NO3− ion, implying mineralization of N that had been incorporated within plant tissue following its initial application in the spring as urea-based fertilizer. Since mineralization is driven by seasonal rainfall and temperature patterns, changes in agronomic practices designed to reduce prompt runoff of fertilizer are unlikely to achieve to more than ~24% reduction in N export to streams.

Conservation Practices in Western Oregon Perennial Grass Seed Systems

Rapid changes in practices used to produce perennial grass seed crops in the U.S. Pacific Northwest region and shortened lengths of time that perennial grass seed fields remain in production have increased the need for additional rotation crops that are adapted to the poorly drained soils found in western Oregon. This research was conducted at three sites to determine ways to manage meadowfoam (Limnanthes alba Hartw. ex Benth.) as a component in perennial grass seed rotation systems. Experiments were conducted in 1997, 1998, and 2001 to investigate combinations of spring-applied herbicide and N fertilizer and times of applications, direct-seeded and conventional tillage establishment methods, and previous crop residue management on meadowfoam seed yield, seed oil concentration, and oil yield. No spring-applied fertilizer or herbicide produced responses for all yield components as great as or greater than any other treatment combination. Direct-seeded meadowfoam yielded more oil than the conventional establishment treatment. There was no effect of residue management amounts from grass seed grown in the previous rotation sequence on meadowfoam production; however, maximal residue management, especially if used in combination with direct-seeded meadowfoam, should reduce annual soil erosion. Meadowfoam is suited to low-input production and is adapted to the use of conservation practices including direct seeding and maximal residue management in perennial grass seed systems.

GIS Analysis of Spatial Clustering and Temporal Change in Weeds of Grass Seed Crops

Abstract Ten years of Oregon Seed Certification Service (OSCS) preharvest field inspections converted from a nonspatial database to a geographic information system (GIS) were analyzed for patterns in spatial distribution of occurrence and severity of the 36 most common weeds of grass seed crops. This was done under the assumptions that those patterns would be primarily consequences of interactions among farming practices, soil properties, and biological traits of the weeds, and that improved understanding of the interactions would benefit the grass seed industry. Kriging, Ripleys K-function, and both Morans I spatial autocorrelation and Getis-Ord General G high/low clustering using the multiple fixed distance band option all produced roughly similar classifications of weeds possessing strongest and weakest spatial clustering patterns. When Morans I and General G analyses of maximum weed severity observed within individual fields over the life of stands were conducted using the inverse distance weighting option, however, results were highly sensitive to the presence of a small number of overlapping fields in the 10-yr record. Addition of any offset in the range from 6 to 6,437 m to measured distances between field centroids in inverse distance weighting matrices removed this sensitivity, and produced results closely matching those for the multiple fixed distance band method. Clustering was significant for maximum severity within fields over the 10-yr period for all 43 weeds and in 78% of single-year analyses. The remaining 22% of single-year cases showed random rather than dispersed distribution patterns. In decreasing order, weeds with strongest inverse-distance spatial autocorrelation were German velvetgrass, field bindweed, roughstalk bluegrass, annual bluegrass, orchardgrass, common velvetgrass, Italian ryegrass, Agrostis spp., and perennial ryegrass. Of these nine weeds, distance for peak spatial autocorrelation ranged from 2 km for Agrostis spp. to 34 km for common velvetgrass. Weeds with stronger spatial autocorrelation had greater range between distance of peak spatial autocorrelation and maximum range of significance. Z-scores for General G high/low clustering were substantially lower than corresponding values for Morans I spatial autocorrelation, although the same two weeds (German velvetgrass and field bindweed) showed strongest clustering using both measures. Simultaneous patterns in Morans I and General G implied that management practices relatively ineffective in controlling weeds usually played a greater role in causing weeds to cluster than highly effective practices, although both types of practices impacted Italian ryegrass distribution. Distance of peak high/low clustering among perennial weeds was smallest (1 to 3 km) for Canada thistle, field bindweed, Agrostis spp., and western wildcucumber, likely indicating that these weeds occurred in patchy infestations extending across neighboring fields. Although both wild carrot and field bindweed doubled in average severity over the period from 1994 to 2003, wild carrot was the only weed clearly undergoing an increase in spatial autocorrelation. Soil chemical and physical properties and dummy variables for soil type and crop explained small but significant portions of total variance in redundancy and canonical correspondence analysis of weed occurrence and severity. Fitch-Morgoliash tree diagrams and Redundancy Analysis (RDA) and Canonical Correspondence Analysis (CCA) ordinations revealed substantial differences among soil types in weed occurrence and severity. Gi* local hot-spot clustering combined with feature class to raster conversion protected grower expectations of confidentiality while describing dominant spatial features of weed distribution patterns in maps released to the public. Nomenclature: Annual bluegrass, Poa annua L. POAAN; Canada thistle, Cirsium arvense (L.) Scop. CIRAR; common velvetgrass, Holcus lanatus L. HOLLA; field bindweed, Convolvulus arvensis L. CONAR; German velvetgrass, Holcus mollis L. HOLMO; Italian ryegrass, Lolium multiflorum Lam. LOLMU; orchardgrass, Dactylis glomerata L. DACGL; perennial ryegrass, Lolium perenne L. LOLPE; roughstalk bluegrass, Poa trivialis L. POATR; western wildcucumber, Marah oreganus (T. & G.) T. J. Howell ECNOR; wild carrot, Daucus carota L. DAUCA.

Remote sensing classification of grass seed cropping practices in western Oregon

Our primary objective was extending knowledge of major crop rotations and stand establishment conditions present in 4800 grass seed fields surveyed over three years in western Oregon to the entire Willamette Valley through classification of multiband Landsat images and multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day composite Normalized Difference Vegetation Index (NDVI). Mismatch in resolution between MODIS and Landsat data was resolved by edging of training and test validation areas using 3 by 3 neighbourhood tests for class uniformity, resampling of MODIS data to 50-m resolution followed by 3 by 3 neighbourhood smoothing to artificially enhance resolution, and resampling to 30 m for stacking data in groups of up to 64, 55 and 81 bands in 2004–2005, 2005–2006 and 2006–2007. Imposing several object-based rules raised final classification accuracies to 84.7, 77.1 and 87.6% for 16 categories of cropping practices in 2005, 2006 and 2007. Total grass seed area was under-predicted by 3.9, 5.4 and 1.8% compared to yearly Cooperative Extension Service estimates, with Italian ryegrass overestimated by an average of 8.4% and perennial ryegrass, orchardgrass and tall fescue underestimated by 10.4, 3.3 and 2.1%. Knowledge of field disturbance patterns will be crucial in future landscape-level analyses of relationships among ecosystem services.

Spatial Targeting of Agri-Environmental Policy Using Bilevel Evolutionary Optimization

In this study we describe the optimal designation of agri-environmental policy as a bilevel optimization problem and propose an integrated solution method using a hybrid genetic algorithm. The problem is characterized by a single leader, the agency, that establishes a policy with the goal of optimizing its own objectives, and multiple followers, the producers, who respond by complying with the policy in a way that maximizes their own objectives. We assume that the leader has perfect knowledge of policy outcomes for all parameterizations of agri-environmental policy. We use a hybrid genetic algorithm to simulate perfect knowledge of all policy outcomes in a bilevel optimization. Our hybrid genetic algorithm integrates a biophysical model (Soil and Water Assessment Tool; SWAT) with an economic model (profit maximization; DEA). The Soil and Water Assessment Tool (SWAT) is included to specify agency environmental objectives, and Data Envelopment Analysis (DEA) is used to model producer behavior in response to agri-environmental policy. We applied the resulting integrated modeling system to the analysis of an input tax on fertilizer in the Calapooia watershed in Oregon, USA. Application of the incentive policy at different geographical resolutions showed that bilevel optimization is effective for calculating optimal spatial targeting of agri-environmental policy. Surprisingly, the presented algorithm found multiple different policy configurations that achieved nearly identical results for the upper level (agency) objectives. This observation raises the possibility that additional objectives could incorporate equity, equality of outcome, and policy initiatives such as support for small farms at no additional cost.

Differential sensitivity of Italian ryegrass (Lolium multiflorum) cultivars to fenoxaprop

Abstract Several seed production fields of the Italian ryegrass cultivar ‘Tetrone’ were destroyed in 1988 by 280 to 350 g ai ha−1 racemic fenoxaprop applied for wild oat control. Because similar rates of fenoxaprop had possessed adequate safety when applied to ‘Oregon common’ Italian ryegrass, suspicion arose that the cultivars differed in tolerance. Seedlings of 21 commonly grown cultivars were screened in the greenhouse at the three-leaf growth stage to determine their fresh weight GR50 for fenoxaprop. The GR50 values for the two most tolerant cultivars, ‘Marshall’ and ‘Torero’, were more than threefold greater than the two most sensitive cultivars, ‘Futaharu’ and ‘Ace’. Cultivars could be separated into sensitive, intermediate, and tolerant groups, but the distribution of the GR50 values appeared to be continuous rather than discrete. Tolerance increased with growth stage, and the average GR50 for tillered plants was 80% higher than that for the two-leaf stage and 41% higher than that for the four-leaf stage seedlings. Cultivars differed slightly in the specific activity of acetyl–coenzyme A carboxylase (ACCase) (EC 6.4.1.2) and in the I50 values for the inhibition by fenoxaprop, but the only clear relationship between these biochemical factors and whole-plant tolerance was a threefold increase in ACCase activity at the tillered stage over that present in the younger seedlings. Nomenclature: Fenoxaprop; wild oat, Avena fatua L. AVEFA; Italian ryegrass, Lolium multiflorum Lam. LOLMU.

High resolution modeling of agricultural nitrogen to identify private wells susceptible to nitrate contamination

Given the lack of data on private wells, public health and water quality specialists must explore alternative datasets for understanding associated exposures and health risks. Characterizing agricultural nitrogen inputs would be valuable for identifying areas where well water safety may be compromised. This study incorporated existing methods for estimating nutrient loading at the county level with datasets derived from a state permitting program for confined animal feeding operations and agricultural enterprise budget worksheets to produce a high resolution agricultural nitrogen raster map. This map was combined with data on soil leachability and new well locations. An algorithm was developed to calculate nitrogen loading and leachability within 1,000 meters of each well. Wells with a nonzero nitrogen total linked to soils with high leachability were categorized and displayed on maps communicating well susceptibility across the state of Oregon. Results suggest that 4% of recently drilled wells may be susceptible to nitrate contamination, while areas identified for mitigation are too restrictive to include all susceptible wells. Predicted increases in population density and the steady addition of approximately 3,800 new wells annually may lead to a large number of residents, especially those in rural areas, experiencing long-term exposures to nitrate in drinking water.