Ohio Economic Insects and Related Anthropods

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An evaluation of four crop : weed competition models using a common data set

To date, several crop : weed competition models have been developed. Developers of the various models were invited to compare model performance using a common data set. The data set consisted of wheat and Lolium rigidum grown in monoculture and mixtures under dryland and irrigated conditions. Results from four crop : weed competition models are presented: ALMANAC, APSIM, CROPSIM and INTERCOM. For all models, deviations between observed and predicted values for monoculture wheat were only slightly lower than for wheat grown in competition with L. rigidum, even though the workshop participants had access to monoculture data while parameterizing models. Much of the error in simulating competition outcome was associated with difficulties in accurately simulating growth of individual species. Relatively simple competition algorithms were capable of accounting for the majority of the competition response. Increasing model complexity did not appear to dramatically improve model accuracy. Comparison of specific competition processes, such as radiation interception, was very difficult since the effects of these processes within each model could not be isolated. Algorithms for competition processes need to be modularized in such a way that exchange, evaluation and comparison across models is facilitated

An evaluation of four crop : weed competition models using a common data set

To date, several crop : weed competition models have been developed. Developers of the various models were invited to compare model performance using a common data set. The data set consisted of wheat and Lolium rigidum grown in monoculture and mixtures under dryland and irrigated conditions. Results from four crop : weed competition models are presented: ALMANAC, APSIM, CROPSIM and INTERCOM. For all models, deviations between observed and predicted values for monoculture wheat were only slightly lower than for wheat grown in competition with L. rigidum, even though the workshop participants had access to monoculture data while parameterizing models. Much of the error in simulating competition outcome was associated with difficulties in accurately simulating growth of individual species. Relatively simple competition algorithms were capable of accounting for the majority of the competition response. Increasing model complexity did not appear to dramatically improve model accuracy. Comparison of specific competition processes, such as radiation interception, was very difficult since the effects of these processes within each model could not be isolated. Algorithms for competition processes need to be modularized in such a way that exchange, evaluation and comparison across models is facilitated

Stability of corn (\u3ci\u3eZea mays\u3c/i\u3e)- foxtail (\u3ci\u3eSetaria\u3c/i\u3e spp.) interference relationships

Variation in interference relationships have been shown for a number of crop-weed associations and may have an important effect on the implementation of decision support systems for weed management. Multiyear field experiments were conducted at eight locations to determine the stability of corn-foxtail interference relationships across years and locations. Two coefficients (I and A) of a rectangular hyperbola equation were estimated for each data set using nonlinear regression procedures. The I and A coefficients represent percent corn yield loss as foxtail density approaches zero and maximum percent corn yield loss, respectively. The coefficient I was stable across years at two locations and varied across years at four locations. Maximum yield loss (A) varied between years at one location. Both coefficients varied among locations. Although 3 to 4 foxtail plants m-1 row was a conservative estimate of the single-year economic threshold (Te) of foxtail density, variation in I and A resulted in a large variation in Te. Therefore, the utility of using common coefficient estimates to predict future crop yield loss from foxtail interference between years or among locations within a region is limited

Stability of corn (\u3ci\u3eZea mays\u3c/i\u3e)- foxtail (\u3ci\u3eSetaria\u3c/i\u3e spp.) interference relationships

Variation in interference relationships have been shown for a number of crop-weed associations and may have an important effect on the implementation of decision support systems for weed management. Multiyear field experiments were conducted at eight locations to determine the stability of corn-foxtail interference relationships across years and locations. Two coefficients (I and A) of a rectangular hyperbola equation were estimated for each data set using nonlinear regression procedures. The I and A coefficients represent percent corn yield loss as foxtail density approaches zero and maximum percent corn yield loss, respectively. The coefficient I was stable across years at two locations and varied across years at four locations. Maximum yield loss (A) varied between years at one location. Both coefficients varied among locations. Although 3 to 4 foxtail plants m-1 row was a conservative estimate of the single-year economic threshold (Te) of foxtail density, variation in I and A resulted in a large variation in Te. Therefore, the utility of using common coefficient estimates to predict future crop yield loss from foxtail interference between years or among locations within a region is limited

Rethinking interhemispheric imbalance as a target for stroke neurorehabilitation

© 2019 American Neurological Association Objective: Patients with chronic stroke have been shown to have failure to release interhemispheric inhibition (IHI) from the intact to the damaged hemisphere before movement execution (premovement IHI). This inhibitory imbalance was found to correlate with poor motor performance in the chronic stage after stroke and has since become a target for therapeutic interventions. The logic of this approach, however, implies that abnormal premovement IHI is causal to poor behavioral outcome and should therefore be present early after stroke when motor impairment is at its worst. To test this idea, in a longitudinal study, we investigated interhemispheric interactions by tracking patients’ premovement IHI for one year following stroke. Methods: We assessed premovement IHI and motor behavior five times over a 1-year period after ischemic stroke in 22 patients and 11 healthy participants. Results: We found that premovement IHI was normal during the acute/subacute period and only became abnormal at the chronic stage; specifically, release of IHI in movement preparation worsened as motor behavior improved. In addition, premovement IHI did not correlate with behavioral measures cross-sectionally, whereas the longitudinal emergence of abnormal premovement IHI from the acute to the chronic stage was inversely correlated with recovery of finger individuation. Interpretation: These results suggest that interhemispheric imbalance is not a cause of poor motor recovery, but instead might be the consequence of underlying recovery processes. These findings call into question the rehabilitation strategy of attempting to rebalance interhemispheric interactions in order to improve motor recovery after stroke. Ann Neurol 2019;85:502–513

Corn Yield Potential and Optimal Soil Productivity in Irrigated Corn/Soybean Systems

In 1999, an interdisciplinary research team at the University of Nebraska established a field experiment to (1) quantify and understand the yield potential of corn and soybean under irrigated conditions, (2) identify efficient crop management practices to achieve yields that approach potential levels, and (3) determine the energy use efficiency, global warming and soil C-sequestration potential of intensively managed corn systems. The experiment compares systems that represent different levels of management intensity expressed as combinations of crop rotation (continuous corn, corn-soybean), plant density (low, medium, high) and nutrient management (recommended best management vs. intensive management). Detailed measurements include soil nutrient dynamics and C balance, crop growth and development, nutrient uptake and components of yield of corn and soybean, radiation use efficiency, soil surface fluxes of greenhouse gases, root biomass, C inputs through crop residues, translocation of non-structural carbohydrates, and amount, composition and activity of the microbial biomass. Selected results for corn are presented

Corn Yield Potential and Optimal Soil Productivity in Irrigated Corn/Soybean Systems

In 1999, an interdisciplinary research team at the University of Nebraska established a field experiment to (1) quantify and understand the yield potential of corn and soybean under irrigated conditions, (2) identify efficient crop management practices to achieve yields that approach potential levels, and (3) determine the energy use efficiency, global warming and soil C-sequestration potential of intensively managed corn systems. The experiment compares systems that represent different levels of management intensity expressed as combinations of crop rotation (continuous corn, corn-soybean), plant density (low, medium, high) and nutrient management (recommended best management vs. intensive management). Detailed measurements include soil nutrient dynamics and C balance, crop growth and development, nutrient uptake and components of yield of corn and soybean, radiation use efficiency, soil surface fluxes of greenhouse gases, root biomass, C inputs through crop residues, translocation of non-structural carbohydrates, and amount, composition and activity of the microbial biomass. Selected results for corn are presented

Climate Change, Drought, and Policymaking in the U.S. Southern Region

This report was prepared by the ORIGINAL: Institute for Science, Technology and Public Policy in The Bush School of Government and Public Service at Texas A&M University under award NA05OAR4311121 from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce. The statements, findings, conclusions, and recommendations are those of the authors and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration or the Department of Commerce.surveyNational Oceanic and Atmospheric Administration, U.S. Department of Commerce (NA05OAR4311121