Determining the Price-Responsiveness of Demands for Irrigation Water Deliveries versus Consumptive Use

A water-crop simulation/mathematical programming model of irrigation water demand in northeastern Colorado is formulated to develop an original concept of derived demand for consumptive use of water. Conventional demand functions for water deliveries are also developed, and the effect of hypothetical price increases on both consumption and delivery are illustrated. Findings indicate that demand elasticity estimates are quite sensitive to model specification, and consumptive use demand tends to be significantly less price-responsive than delivery demand. Thus price incentives are likely to have only limited impacts on basin-wide water consumption and would not make much additional water available for emerging demands.crop simulation, irrigation, mathematical programming, water conservation, water-demand elasticities, water policy, Demand and Price Analysis, Resource /Energy Economics and Policy,

Soil Series: Elevation and Agricultural Soil Test Survey of the Godfrey Dryland Experimental Farm, Clarkston, Utah

The survey reported in this fact sheet details the areal distribution of soil type, topographical variation across the site and key agricultural soil test results to serve as baseline guidance information to potential researchers and farm managers

Protocol for a state-wide ground water quality monitoring program and establishment of a ground water quality data clearinghouse

February, 2004.Includes bibliographical references (pages 31-34).Financed in part by the U.S. Department of the Interior, Geological Survey, through the Colorado Water Resources Research Institute, grant no. 1434HQ96GR02660/04

Understanding Your Soil Test Report

Regular soil testing helps to develop and maintain more productive soils for farming, gardening, and landscaping. The purpose of this guide is to help you understand and interpret the results from a Utah State University soil test report. Additional Utah State University Extension bulletins are available, which address solutions to specific soil problems and offer guidance on fertilizer selection and use. See “Where to obtain additional information” at the end of this guide

Tillage Method and Glyphosate-Resistant Alfalfa Termination Timing Affect Soil Properties and Subsequent Corn Yield

Application of glyphosate [N-(phosphonomethyl) glycine]-containing herbicides and tillage, alone or in combination, has been the standard for removing declining alfalfa (Medicago sativa L.) stands. With glyphosate no longer an option to control glyphosate-resistant alfalfa, different termination strategies are needed. Field studies across four site-years in Utah evaluated the effect of tillage type and timing (fall conventional till, spring conventional till, fall strip-till, spring strip-till, and no-till) and herbicide timing (fall, spring, in-crop, and no herbicide) of 2,4-D (2,4- dichlorophenoxyacetic acid) and dicamba (3,6-dichloro-2-methoxybenzoic acid) on penetration resistance, alfalfa regrowth, corn (Zea mays L.) emergence rate, and silage corn yield. Across tillage treatments, fall, spring, and in-crop herbicide timings compared with no herbicide reduced alfalfa stem count and biomass by at least 74 and 92%, respectively. Emergence rate was greatest under fall and spring conventional till or spring strip-till compared with fall strip-till or no-till. Silage corn yield was greatest and similar with fall or spring herbicide applications for all tillage systems and conventional tillage with an in-crop herbicide application (19–27 Mg ha−1), followed by in-crop herbicide application for conservation tillage systems and fall and spring conventional till without herbicide application (14–20 Mg ha−1), and lastly when only conservation tillage was used to terminate alfalfa (5–15 Mg ha−1). Silage corn yield can be optimized when glyphosate-resistant alfalfa is terminated with herbicides prior to planting, regardless of tillage type or timing. Termination of glyphosate-resistant alfalfa by herbicides after corn emergence, depending on tillage, reduces silage corn yield 9–19%

Nitrogen Fertilization and Glyphosate-Resistant Alfalfa Termination Method Effects on First-Year Silage Corn

Tillage type/timing and herbicide application date may change the amount and timing of N mineralization, altering fertilizer N needs for first-year corn (Zea mays L.) following glyphosate [N-(phosphonomethyl)glycine]-resistant (GR) alfalfa (Medicago sativa L.). Studies were conducted in 2012 and 2013 in Utah. Yield, quality, and economic return of silage corn as affected by five tillage type/timings (fall conventional till, spring conventional till, fall strip-till, spring strip-till, and no-till), three herbicide application dates for alfalfa termination (fall, spring, and in-crop), and four N rates (0, 56, 112, and 224 kg ha−1) were evaluated. Silage corn yield and quality following GR alfalfa was economically optimized without N fertilization regardless of tillage type/timing and herbicide application date. Thus, N from decomposing alfalfa can provide the full N requirement of first-year silage corn following GR alfalfa. Estimated animal milk production ha−1 of silage corn was greatest and similar for all herbicide application dates with conventional tillage and spring herbicide application with strip-till and no-till (26–38 Mg milk ha−1), whereas an in-crop herbicide application with strip-till and no-till resulted in the lowest estimated milk production (21–29 Mg milk ha−1). Increased economic return for the in-crop herbicide date by including economics from harvesting the first alfalfa cutting before planting corn mostly offset the reduced economic return of the lower silage corn yield. Therefore, an application of 2,4-D (2,4-dichlorophenoxyacetic acid) and dicamba (3,6-dichloro-2-methoxybenzoic acid) in the fall, spring, or in-crop to control GR alfalfa are good economic options for conventional tillage, strip-till, and no-till systems

Systematic literature review of determinants of sedentary behaviour in older adults:a DEDIPAC study

BACKGROUND: Older adults are the most sedentary segment of society and high sedentary time is associated with poor health and wellbeing outcomes in this population. Identifying determinants of sedentary behaviour is a necessary step to develop interventions to reduce sedentary time. METHODS: A systematic literature review was conducted to identify factors associated with sedentary behaviour in older adults. Pubmed, Embase, CINAHL, PsycINFO and Web of Science were searched for articles published between 2000 and May 2014. The search strategy was based on four key elements: (a) sedentary behaviour and its synonyms; (b) determinants and its synonyms (e.g. correlates, factors); (c) types of sedentary behaviour (e.g. TV viewing, sitting, gaming) and (d) types of determinants (e.g. environmental, behavioural). Articles were included in the review if specific information about sedentary behaviour in older adults was reported. Studies on samples identified by disease were excluded. Study quality was rated by means of QUALSYST. The full review protocol is available from PROSPERO (PROSPERO 2014: CRD42014009823). The analysis was guided by the socio-ecological model framework. RESULTS: Twenty-two original studies were identified out of 4472 returned by the systematic search. These included 19 cross-sectional, 2 longitudinal and 1 qualitative studies, all published after 2011. Half of the studies were European. The study quality was generally high with a median of 82 % (IQR 69-96 %) using Qualsyst tool. Personal factors were the most frequently investigated with consistent positive association for age, negative for retirement, obesity and health status. Only four studies considered environmental determinants suggesting possible association with mode of transport, type of housing, cultural opportunities and neighbourhood safety and availability of places to rest. Only two studies investigated mediating factors. Very limited information was available on contexts and sub-domains of sedentary behaviours. CONCLUSION: Few studies have investigated determinants of sedentary behaviour in older adults and these have to date mostly focussed on personal factors, and qualitative studies were mostly lacking. More longitudinal studies are needed as well as inclusion of a broader range of personal and contextual potential determinants towards a systems-based approach, and future studies should be more informed by qualitative work

From Disease Association to Risk Assessment: An Optimistic View from Genome-Wide Association Studies on Type 1 Diabetes

Genome-wide association studies (GWAS) have been fruitful in identifying disease susceptibility loci for common and complex diseases. A remaining question is whether we can quantify individual disease risk based on genotype data, in order to facilitate personalized prevention and treatment for complex diseases. Previous studies have typically failed to achieve satisfactory performance, primarily due to the use of only a limited number of confirmed susceptibility loci. Here we propose that sophisticated machine-learning approaches with a large ensemble of markers may improve the performance of disease risk assessment. We applied a Support Vector Machine (SVM) algorithm on a GWAS dataset generated on the Affymetrix genotyping platform for type 1 diabetes (T1D) and optimized a risk assessment model with hundreds of markers. We subsequently tested this model on an independent Illumina-genotyped dataset with imputed genotypes (1,008 cases and 1,000 controls), as well as a separate Affymetrix-genotyped dataset (1,529 cases and 1,458 controls), resulting in area under ROC curve (AUC) of ∼0.84 in both datasets. In contrast, poor performance was achieved when limited to dozens of known susceptibility loci in the SVM model or logistic regression model. Our study suggests that improved disease risk assessment can be achieved by using algorithms that take into account interactions between a large ensemble of markers. We are optimistic that genotype-based disease risk assessment may be feasible for diseases where a notable proportion of the risk has already been captured by SNP arrays

Genetic approaches to human renal agenesis/hypoplasia and dysplasia

Congenital abnormalities of the kidney and urinary tract are frequently observed in children and represent a significant cause of morbidity and mortality. These conditions are phenotypically variable, often affecting several segments of the urinary tract simultaneously, making clinical classification and diagnosis difficult. Renal agenesis/hypoplasia and dysplasia account for a significant portion of these anomalies, and a genetic contribution to its cause is being increasingly recognized. Nevertheless, overlap between diseases and challenges in clinical diagnosis complicate studies attempting to discover new genes underlying this anomaly. Most of the insights in kidney development derive from studies in mouse models or from rare, syndromic forms of human developmental disorders of the kidney and urinary tract. The genes implicated have been shown to regulate the reciprocal induction between the ureteric bud and the metanephric mesenchyme. Strategies to find genes causing renal agenesis/hypoplasia and dysplasia vary depending on the characteristics of the study population available. The approaches range from candidate gene association or resequencing studies to traditional linkage studies, using outbred pedigrees or genetic isolates, to search for structural variation in the genome. Each of these strategies has advantages and pitfalls and some have led to significant discoveries in human disease. However, renal agenesis/hypoplasia and dysplasia still represents a challenge, both for the clinicians who attempt a precise diagnosis and for the geneticist who tries to unravel the genetic basis, and a better classification requires molecular definition to be retrospectively improved. The goal appears to be feasible with the large multicentric collaborative groups that share the same objectives and resources