Gale H. Dunn

Soil management alters seedling emergence and subsequent autumn growth and yield in dryland winter wheat–fallow systems in the Central Great Plains on a clay loam soil

Stand establishment and subsequent autumn development and growth are important determinants of winter wheat (Triticum aestivum L.) yield. Soil management practices change soil properties and conditions, which alter seedling emergence, crop development and growth. Pre-plant soil management practices were studied for 6 years in a wheat–fallow rotation in eastern Colorado, USA, to isolate the impacts of pre-plant tillage (PT) and residue level on winter wheat seedling emergence and autumn development and growth. A split plot design was used with PT, using a moldboard plow that incorporated surface residue, and with no-tillage (NT). The tillage systems represented the main plots and three residue levels within each tillage treatment as subplots: no residue (0R), normal residue (1R) and twice-normal residue (2R). Residue amount had little effect on emergence or autumn growth and development. PT resulted in soil water loss from the plow zone. NT plots had more favorable soil water levels in the seeding zone which resulted in faster, more uniform and greater seedling emergence in 4 out of the 6 years. This is especially critical for stand establishment in years with low rainfall after planting. Soil or air temperature did not account for differences among treatments. Earlier and greater seedling emergence in NT treatments resulted in greater autumn development and growth. Shoot biomass, tiller density and leaf numbers were greater in NT, and again residue amount had little effect. At spring green-up, NT treatments had greater soil water in the profile. Grain yield was always equal or greater in NT than in PT, and positively correlated with earlier/greater seedling emergence and autumn growth. NT will enhance soil protection and likely increase snow catch, reduce evaporation and benefit yield in semiarid eastern Colorado.

Evaluation of GPFARM for Simulation of Forage Production and Cow–Calf Weights

Abstract A modeling approach that assesses impacts of alternative management decisions prior to field implementation would reduce decision-making risk for rangeland and livestock production system managers. However, the accuracy and functionality of models should be verified before they are used as decision-making tools. The goal of this study was to evaluate the functionality of the Great Plains Framework for Agricultural Resource Management (GPFARM) model in simulating forage and cow–calf production in the central Great Plains. The forage production module was tested in shortgrass prairie using April–October monthly biomass values from 2000 through 2002 for warm-season grasses (WSG), cool-season grasses (CSG), shrubs, and forbs. The forage module displayed excellent (99% explained variance) agreement in the 2001 calibration year in tracking growth and senescence trends of WSG and CSG, which constitute the vast majority of the aboveground biomass. Less agreement (35%–39% explained variance) was observed for shrubs and forbs. The model-explained variances of biomass in 2000 and 2002 (verification years) were 80% for WSG, 67% for CSG, 78% for shrubs, and 82% for forbs. Further development is needed to improve predicted plant response to environmental stresses. The cow–calf production module was tested in northern mixed-grass prairie using June–November monthly average cow and calf weights from 1996 through 2001 for March-calving, moderately stocked Hereford pairs. Overall, GPFARM performed well and tracked cow (81% explained variance) and calf (94% explained variance) pre- and postweaning weights. The GPFARM model has functional utility for simulating forage and cow–calf production with satisfactory accuracy at semiarid-temperate sites, such as southeastern Wyoming and northeastern Colorado. Continued development will focus on improving plant response to environmental stresses and testing the models functionality as a decision support tool for strategic and tactical ranch management.

Ecological Sustainability of Rangelands

Rangelands and pastures are found in every state and cover 55% of the land surface of the United States. Taken as a whole, from Western deserts and grasslands to meadows and woodlands, rangelands comprise some 364 million ha or 80% of the land in the 17 Western states. The vast expanses and remoteness of rangelands make assessing economic and ecological sustainability a difficult task. Currently, there is no national monitoring framework in place to collect data on long-term or episodic processes and agents of change over time. There are no defined methods for summarizing the health of rangelands. Thus individual conclusions about the health or sustainability of the nations rangelands vary from person to person and organization to organization. Over one million people derive some portion of their income from farm and ranch activities on rangelands and pastures in the western United States. These individuals own and operate over 406,000 farms and ranches with revenues from selling beef cattle exceeding

Modeling With Limited Data: The Influence of Crop Rotation and Management on Weed Communities and Crop Yield Loss

13 billion in the 17 Western states. Their continued economic survival is dependent on the environmental sustainability of rangelands. Moreover, organizations and individuals charged with selection of best management systems on rangelands are under increasing pressure to consider not only livestock production issues, but also sustainability and health under multiple land use. As a result, ranchers, government agencies, and other organizations have a critical need for improved methods to balance the economic viability of ranchers, the well being of rural America, and the health and sustainability of the nations range- and grazinglands. Therefore, a coordinated national research and technology transfer effort is required to successfully develop and transfer to ranchers and rangeland managers a science-based, monitoring system to determine the effect of management practices on sustainability of rangeland ecosystems.

The Drought Calculator: Decision Support Tool for Predicting Forage Growth During Drought

Abstract Theory and models of crop yield loss from weed competition have led to decision models to help growers choose cost-effective weed management. These models are available for multiple-species weed communities in a single season of several crops. Growers also rely on crop rotation for weed control, yet theory and models of weed population dynamics have not led to similar tools for planning of crop rotations for cost-effective weed management. Obstacles have been the complexity of modeling the dynamics of multiple populations of weed species compared to a single species and lack of data. We developed a method to use limited, readily observed data to simulate population dynamics and crop yield loss of multiple-species weed communities in response to crop rotation, tillage system, and specific weed management tactics. Our method is based on the general theory of density dependence of plant productivity and extensive use of rectangular hyperbolic equations for describing crop yield loss as a function of weed density. Only two density-independent parameters are required for each species to represent differences in seed bank mortality, emergence, and maximum seed production. One equation is used to model crop yield loss and density-dependent weed seed production as a function of crop and weed density, relative time of weed and crop emergence, and differences among species in competitive ability. The model has been parameterized for six crops and 15 weeds, and limited evaluation indicates predictions are accurate enough to highlight potential weed problems and solutions when comparing alternative crop rotations for a field. The model has been incorporated into a decision support tool for whole-farm management so growers in the Central Great Plains of the United States can compare alternative crop rotations and how their choice influences farm income, herbicide use, and control of weeds in their fields.

Spatial analysis of various soil properties in a semiarid rangeland

Abstract The Drought Calculator (DC), a spreadsheet-based decision support tool, was developed to help ranchers and range managers predict reductions in forage production due to drought. Forage growth potential (FGP), the fraction of historical average production, is predicted as a weighted average of monthly precipitation from January through June. We calibrated and evaluated the DC tool in the Great Plains of the United States, using FGP and precipitation data from Colorado (CO), North Dakota (ND), and Wyoming (WY). In CO, FGP was most sensitive to precipitation in April and May, in ND to precipitation in April and June, and in WY to precipitation in April, May, and June. Weights in these months ranged from 0.16 to 0.52. Prediction was better for CO and WY than for ND. When January–June precipitation was used, the tool correctly predicted 83% of the years with FGP reduced by drought for CO, 82% for WY, and only 67% for ND. Positive values of the True Skill Statistic (0.53 for CO, 0.42 for WY, and 0.17 for ND) indicate that FGP was classified as above or below average better than random selection. Predicting FGP earlier than April in CO and WY will require accurate forecasts of April–June precipitation. Use of the DC is most limited by insufficient forage data to determine the site-specific relationships between FGP and monthly precipitation. Even so, the decision tool is useful for discriminating drought effects on FGP classification being above or below the long-term average, and it provides a quantitative prediction to producers for their destocking decisions in drought years.

Fractal analyses of steady infiltration and terrain on an undulating agricultural field.

Abstract Researchers and managers of semiarid rangelands rely on accurately determining soil properties for such tasks as establishing experimental plots, randomizing experiments, and developing mangement plans. Spatial variability of many soil characteristics is generally very high often resulting in erroneous assumptions concerning baseline soil properties. A field study was initiated to quantify the degree of spatial variability on a rangeland site in northeastern Colorado. The research site consisted of north‐ and south‐facing slopes. Soil cores were collected at two depths from a 100‐point grid laid out on each slope. Soil was analyzed for bulk density, particle size, calcium carbonate, and organic matter. Conventional and geostatistical analyses were conducted to compare variables within and between the two slopes. Spatial correlations were detected for percentage sand, clay, and calcium carbonate on the south‐facing slope. Soil bulk density and percentage calcium carbonate in the soil were the most...