Based on six years of data from a field experiment near Pullman, WA, a bioeconomic decision model was developed to annually estimate the optimal post-emergence herbicide types and rates to control multiple weed species in winter wheat under various tillage systems and crop rotations. The model name, PALWEED:WHEAT, signifies a Washington-Idaho Palouse region weed management model for winter wheat The model consists of linear preharvest weed density functions, a nonlinear yield response function, and a profit function. Preharvest weed density functions were estimated for four weed groups: summer annual grasses, winter annual grasses, summer annual broadleaves, and winter annual broadleaves. A single aggregated weed competition index was developed from the four density functions for use functions for use in the yield model. A yield model containing a logistic damage function performed better than a model containing a rectangular hyperbolic damage function. Herbicides were grouped into three categories: preplant nonselective, postemergence broadleaf, and postemergence grass. PALWEED:WHEAT was applied to average conditions of the 6-yr experiment to predict herbicide treatments that maximized profit. In comparison to average treatment rates in the 6-yr experiment, the bioeconomic decision model recommended less postemergence herbicide. The weed management recommendations of PALWEED:WHEAT behaved as expected by agronomic and economic theory in response to changes in assumed weed populations, herbicide costs, crop prices, and possible restrictions on herbicide application rates.

Increasing plant species diversity has been proposed as a means for enhancing annual pasture productivity and decreasing seasonal variability of pasture production facing more frequent drought scenarios due to climate change. Few studies have examined how botanical complexity of sown swards affects cow performance. A 2-year experiment was conducted to determine how sward botanical complexity, from a monoculture of ryegrass to multi-species swards (MSS) (grasses-legumes-forb), affect pasture chemical composition and nutritive value, pasture dry matter (DM) intake, milk production and milk solids production of grazing dairy cows. Five sward species: perennial ryegrass (L as Lolium), white clover and red clover (both referred to as T as Trifolium because they were always sown together), chicory (C as Cichorium) and tall fescue (F as Festuca) were assigned to four grazing treatments by combining one (L), three (LT), four (LTC) or five (LTCF) species. Hereafter, the LT swards are called mixed swards as a single combination of ryegrass and clovers, whereas LTC and LTCF swards are called MSS as a combination of at least four species from three botanical families. The experimental area (8.7 ha) was divided into four block replicates with a mineral nitrogen fertilisation of 75 kg N/ha per year for each treatment. In total, 13 grazing rotations were carried out by applying the same grazing calendar and the same pasture allowance of 19 kg DM/cow per day above 4 cm for all treatments. Clover represented 20% of DM for mixed and MSS swards; chicory represented 30% of DM for MSS and tall fescue represented 10% of DM for LTCF swards. Higher milk production (+1.1 kg/day) and milk solids production (+0.08 kg/day) were observed for mixed swards than for ryegrass swards. Pasture nutritive value and pasture DM intake were unaffected by the inclusion of clover. Pasture DM, organic matter and NDF concentrations were lower for MSS than for mixed swards. Higher milk production (+0.8 kg/day), milk solids production (+0.04 kg/day) and pasture DM intake (+1.5 kg DM/day) were observed for MSS than for mixed swards. These positive effects of MSS were observed for all seasons, but particularly during summer where chicory proportion was the highest. In conclusion, advantages of grazing MSS on cow performance were due to the cumulative effect of improved pasture nutritive value and increased pasture DM intake that raised milk production and milk solids production.

Classical approaches to the economics of pest management have focused almost exclusively on single-species models. This study develops and implements a methodology with which to evaluate multi-species, non-stochastic, managerial decisions subject to stochastic elements of the plant-insect system. Multi-species insect management strategies (combinations of scouting interval, threshold value, and choice of pesticide) are analyzed using a physiological mechanistic soybean plant growth model coupled to three insect population dynamics models. Preliminary results indicate that net returns are maximized and variance is reduced with lower thresholds and more frequent scouting than current recommendations.