Palmer Amaranth Confirmed in Western Iowa

The presence of Palmer amaranth was recently confirmed in Harrison County near the Missouri River. The infestation was in two fields that have a history of land application of sludge. Because of the magnitude of the infestation, we believe the weed has been present for at least two growing seasons. We suspect the weed probably has spread to other fields in the area, but at this time we have not verified this

Effect of row spacing and seeding rates on soybean yields and weed management programs

This research studied the influence of row spacing on the competitiveness of soybeans with weeds. Late-emerging weeds were a greater problem in 30-in. than in 10-in. rows, and narrow-row soybeans competed successfully with weeds that emerged three weeks after planting, whereas wider-row soybeans needed four weeks to become competitive. The shading provided by narrow-row soybeans was as effective as a layby cultivation in controlling late-emerging weeds. Moreoever, post-emergence herbicides controlled weeds effectively at rates lower than recommended by the manufacturer. Two one-quarter applications two weeks apart provided control equal to the full amount, with no yield losses. Narrow-row spacing offers potential for reducing herbicide costs, although success depends on appropriate selection and timely application of herbicide

Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science

It is well documented that the majority of adults, children and families in need of evidence-based behavioral health interventionsi do not receive them [1, 2] and that few robust empirically supported methods for implementing evidence-based practices (EBPs) exist. The Society for Implementation Research Collaboration (SIRC) represents a burgeoning effort to advance the innovation and rigor of implementation research and is uniquely focused on bringing together researchers and stakeholders committed to evaluating the implementation of complex evidence-based behavioral health interventions. Through its diverse activities and membership, SIRC aims to foster the promise of implementation research to better serve the behavioral health needs of the population by identifying rigorous, relevant, and efficient strategies that successfully transfer scientific evidence to clinical knowledge for use in real world settings [3]. SIRC began as a National Institute of Mental Health (NIMH)-funded conference series in 2010 (previously titled the “Seattle Implementation Research Conference”; $150,000 USD for 3 conferences in 2011, 2013, and 2015) with the recognition that there were multiple researchers and stakeholdersi working in parallel on innovative implementation science projects in behavioral health, but that formal channels for communicating and collaborating with one another were relatively unavailable. There was a significant need for a forum within which implementation researchers and stakeholders could learn from one another, refine approaches to science and practice, and develop an implementation research agenda using common measures, methods, and research principles to improve both the frequency and quality with which behavioral health treatment implementation is evaluated. SIRC’s membership growth is a testament to this identified need with more than 1000 members from 2011 to the present.ii SIRC’s primary objectives are to: (1) foster communication and collaboration across diverse groups, including implementation researchers, intermediariesi, as well as community stakeholders (SIRC uses the term “EBP champions” for these groups) – and to do so across multiple career levels (e.g., students, early career faculty, established investigators); and (2) enhance and disseminate rigorous measures and methodologies for implementing EBPs and evaluating EBP implementation efforts. These objectives are well aligned with Glasgow and colleagues’ [4] five core tenets deemed critical for advancing implementation science: collaboration, efficiency and speed, rigor and relevance, improved capacity, and cumulative knowledge. SIRC advances these objectives and tenets through in-person conferences, which bring together multidisciplinary implementation researchers and those implementing evidence-based behavioral health interventions in the community to share their work and create professional connections and collaborations

A modeling approach to quantify the effects of spatial soybean yield limiting factors

Spatial yield variability is a complex interaction of many factors, including soil properties, weather, pests, fertility, and management. Crop models are excellent tools to evaluate these complex interactions and provide insight into causes of spatial yield variability. The goal of this study was to use a soybean crop growth model to determine the contribution of three factors that cause spatial yield variability and to test several calibration and validation strategies for yield prediction. A procedure was developed to calibrate the CROPGRO–Soybean model and to compare predicted and measured soybean yields, assuming that water stress, soybean cyst nematodes (SCN), and weeds were the dominant yield–limiting factors. The procedure involved calibrating drainage properties and rooting depth over three seasons for each grid. These procedures were tested on 77 grids (0.2 ha in size) in the McGarvey field in Perry, Iowa, for 1995, 1997, and 1999. Predicted soybean yields were in good agreement (r2 = 0.80) with measured yield after calibrating three model parameters. The calibrated model was used to quantify the effects of three yield–limiting factors on soybean. The maximum soybean yield potential in 1997 was estimated by running the calibrated model with no water, SCN, or weed stress. The model was then run for 1997, turning each yield–limiting factor off to assess its relative impact on yield reduction. Average estimated yield loss due to the combined effects of water stress, SCN, and weeds in each grid was 842 kg ha–1. Soybean yields were significantly reduced by an average of 626 kg ha–1 as a result of water stress. The presence of SCN in several grids accounted for an average yield reduction of 105 kg ha–1. The effects of weeds on soybean yield were not significant.This article is published as Paz, J.O., W.D. Batchelor, G.L. Tylka, and R.G. Hartzler. 2001. A modeling approach to quantify the effects of spatial soybean yield limiting factors. Transactions of the ASAE 44:1329-1334, doi: 10.13031/2013.6423. Posted with permission.</p