Predicting the Occurrence of Downy Brome (Bromus tectorum) in Central Oregon

2012 ◽  
Vol 5 (1) ◽  
pp. 83-91 ◽  
Author(s):  
Sara C. P. Lovtang ◽  
Gregg M. Riegel
Keyword(s):  
Logistic Regression ◽  
Great Basin ◽  
Fire Regimes ◽  
National Forest ◽  
Downy Brome ◽  
Department Of Agriculture ◽  
Association Group ◽  
Average Probability ◽  
Regression Techniques ◽  
Successional Pathways

AbstractWhere the nonnative annual grass downy brome proliferates, it has changed ecosystem processes, such as nutrient, energy, and water cycles; successional pathways; and fire regimes. The objective of this study was to develop a model that predicts the presence of downy brome in Central Oregon and to test whether high presence correlates with greater cover. Understory data from the U.S. Department of Agriculture (USDA) Forest Service's Current Vegetation Survey (CVS) database for the Deschutes National Forest, the Ochoco National Forest, and the Crooked River National Grassland were compiled, and the presence of downy brome was determined for 1,092 systematically located plots. Logistic regression techniques were used to develop models for predicting downy brome populations. For the landscape including the eastside of the Cascade Mountains to the northwestern edge of the Great Basin, the following were selected as the best predictors of downy brome: low average March precipitation, warm minimum May temperature, few total trees per acre, many western junipers per acre, and a short distance to nearest road. The concordance index = 0.92. Using the equation from logistic regression, a probability for downy brome infestation was calculated for each CVS plot. The plots were assigned to a plant association group (PAG), and the average probability was calculated for the PAGs in which the CVS plots were located. This method could be duplicated in other areas where vegetation inventories take place.

scholarly journals Modeling of Combined Processing Steps for ReducingEscherichia coli O157:H7 Populations in Apple Cider

2001 ◽  
Vol 67 (1) ◽  
pp. 133-141 ◽  
Author(s):  
Heidi E. Uljas ◽  
Donald W. Schaffner ◽  
Siobain Duffy ◽  
Lihui Zhao ◽  
Steven C. Ingham
Keyword(s):  
Logistic Regression ◽  
Probabilistic Models ◽  
Storage Temperature ◽  
Potassium Sorbate ◽  
Data Set ◽  
Apple Cider ◽  
Multiple Treatment ◽  
Pathogen Control ◽  
Regression Techniques ◽  
Unit Reduction

ABSTRACT Probabilistic models were used as a systematic approach to describe the response of Escherichia coli O157:H7 populations to combinations of commonly used preservation methods in unpasteurized apple cider. Using a complete factorial experimental design, the effect of pH (3.1 to 4.3), storage temperature and time (5 to 35°C for 0 to 6 h or 12 h), preservatives (0, 0.05, or 0.1% potassium sorbate or sodium benzoate), and freeze-thaw (F-T; −20°C, 48 h and 4°C, 4 h) treatment combinations (a total of 1,600 treatments) on the probability of achieving a 5-log10-unit reduction in a three-strain E. coli O157:H7 mixture in cider was determined. Using logistic regression techniques, pH, temperature, time, and concentration were modeled in separate segments of the data set, resulting in prediction equations for: (i) no preservatives, before F-T; (ii) no preservatives, after F-T; (iii) sorbate, before F-T; (iv) sorbate, after F-T; (v) benzoate, before F-T; and (vi) benzoate, after F-T. Statistical analysis revealed a highly significant (P < 0.0001) effect of all four variables, with cider pH being the most important, followed by temperature and time, and finally by preservative concentration. All models predicted 92 to 99% of the responses correctly. To ensure safety, use of the models is most appropriate at a 0.9 probability level, where the percentage of false positives, i.e., falsely predicting a 5-log10-unit reduction, is the lowest (0 to 4.4%). The present study demonstrates the applicability of logistic regression approaches to describing the effectiveness of multiple treatment combinations in pathogen control in cider making. The resulting models can serve as valuable tools in designing safe apple cider processes.

Floristics and Fire Regimes of a Vegetation Sequence From Sedgeland-Heath to Rainforest at Bathurst Harbour, Tasmania

1982 ◽  
Vol 30 (6) ◽  
pp. 659 ◽  
Author(s):  
MJ Brown ◽  
FD Podger
Keyword(s):  
Gradient Analysis ◽  
Fire Regime ◽  
Fire Regimes ◽  
Major Axis ◽  
Fire Frequency ◽  
Edaphic Factors ◽  
Direct Gradient Analysis ◽  
Principal Coordinates ◽  
Successional Pathways ◽  
Descriptive Models

The floristic differences found in vegetation ranging from sedgeland-heath to rainforest were sampled by the placement of 80 quadrats in an area 2 km2 near Bathurst Harbour, Tasmania. A direct gradient analysis using the time since last fire as the major axis of variation suggests that the changing species composition of sites is both gradational and fire-related. This interpretation is supported by a point- centred quarter analysis of the forested communities and by Principal Coordinates and Detrended Correspondence Analyses of the entire vegetation sequence. Previous descriptive models based on correlations between he frequency and structural formations are confirmed by this study. A broad correlation between fire frequency and floristic associations within non-forested vegetation is also demonstrated. However, explanation of detailed patterns requires consideration of the total fire regime (including duration and intensity of fire) and its interaction with edaphic factors. For example, fires which burn in peat lead to hysteresis in the successional pathways.

scholarly journals Where there's smoke, there's fuel: predicting Great Basin rangeland wildfire

2021 ◽  
Author(s):  
Joseph T Smith ◽  
Brady W Allred ◽  
Chad S Boyd ◽  
Kirk W Davies ◽  
Matthew O. Jones ◽  
...  
Keyword(s):  
Great Basin ◽  
Spatial Data ◽  
Ground Cover ◽  
Fire Regimes ◽  
Machine Learning Algorithms ◽  
Fire Season ◽  
Drought Indices ◽  
Area Burned ◽  
Fire Activity ◽  
Fine Fuels

Wildfires are a growing management concern in western US rangelands, where invasive annual grasses have altered fire regimes and contributed to an increased incidence of catastrophic large wildfires. Fire activity in arid, non-forested regions is thought to be largely controlled by interannual variation in fuel amount, which in turn is controlled by antecedent weather. Thus, long-range forecasting of fire activity in rangelands should be feasible given annual estimates of fuel quantity. Using a 32 yr time series of spatial data, we employ machine learning algorithms to predict the relative probability of large (>400 ha) wildfire in the Great Basin based on fine-scale annual and 16-day estimates of cover and production of vegetation functional groups, weather, and multitemporal scale drought indices. We evaluate the predictive utility of these models with a leave-one-year-out cross-validation, building spatial forecasts of fire probability for each year that we compare against actual maps of large wildfires. Herbaceous vegetation aboveground biomass production, bare ground cover, and long-term drought indices were the most important predictors of fire probability. Across 32 fire seasons, >80% of the area burned in large wildfires coincided with predicted fire probabilities ≥0.5. At the scale of the Great Basin, several metrics of fire season severity were moderately to strongly correlated with average fire probability, including total area burned in large wildfires, number of large wildfires, and average and maximum fire size. Our findings show that recent years of exceptional fire activity in the Great Basin were predictable based on antecedent weather and biomass of fine fuels, and reveal a significant increasing trend in fire probability over the last three decades driven by widespread changes in fine fuel characteristics.

scholarly journals Faktor-faktor yang Memengaruhi Preferensi Nasabah terhadap Produk Rahn: Studi Kasus PT. BPRS Amanah Ummah

Al-Muzara ah ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 1-16
Author(s):  
Lisda Qotrunnada Nabila Putri ◽  
Jaenal Effendi
Keyword(s):  
Logistic Regression ◽  
Public Interest ◽  
Education Level ◽  
Customer Preferences ◽  
Savings And Loan ◽  
Regression Techniques ◽  
Knowledge Promotion

Rahn is financing for the community to borrow money using personal items as collateral. Public interest in rahn is still small, even though rahn knew as savings and loan services for property that is guaranteed by customers. The savings and loan services are paid every month along with the loan installments and do not use the interest system, only determining the nominal value of the rupiah determined by the pawning party. Thus, this study aims to determine the factors that influence customer preferences in choosing rahn products. The total of 120 respondents are taken, with a proportion of 60 as respondents representing rahn product respondents and 60 other respondents. The collected data is processed using logistic regression techniques. The results of the study show the factors that influence customer preferences for rahn products are factors of knowledge, promotion, service, education level, employment, income, expenditure and the number of dependents significantly influence customer decisions in choosing rahn products.

scholarly journals Effects of Diabetes on The Output of Farmer and Its Policy Implications

2020 ◽  
Vol 15 (1) ◽  
pp. 1
Author(s):  
Syed Asif Ali Naqvi ◽  
Bilal Hussain ◽  
Syed Ale Raza Shah ◽  
Muhammad Sohail Amjad Makhdum
Keyword(s):  
Logistic Regression ◽  
Marital Status ◽  
Work Performance ◽  
Negative Influence ◽  
Policy Implications ◽  
Cross Sectional ◽  
Farming Communities ◽  
Regression Techniques ◽  
The Impact ◽  
Working Efficiency

This study investigated the impact of diabetes on work performance of different farming communities from Punjab, Pakistan. This study was based on cross-sectional data. A representative sample of 374 farmers was collected from five selected districts. Three types of respondents were analyzed in the study e.g.,laborer, small and large growers. Poisson and logistic regression techniques were used for the sake of analysis. According to the investigated results for thelabor category, respondents with more age, less qualification, low earning per month (Rupees), and having positive record of family diabetes, would havemore leave per month. In the same way, findings for small farmers revealed that education, family size, family with diabetic records, marital status and availability at farm (hour/day) were significant. In case of third category, study outcome highlighted that age, education, marital status, having positive record offamily diabetes and number of hours spent at farm would be positively correlated with the reduction in working efficiency at farm due to diabetes. It can beconcluded that diabetes have negative influence on the work performance of selected farming groups.

The History and Distribution of Downy Brome (Bromus tectorum) in North America

Weed Science ◽  
1984 ◽  
Vol 32 (S1) ◽  
pp. 2-6 ◽  
Author(s):  
Larry A. Morrow ◽  
Phillip W. Stahlman
Keyword(s):  
United States ◽  
North America ◽  
Winter Wheat ◽  
Great Basin ◽  
Bromus Tectorum ◽  
Production Systems ◽  
Western United States ◽  
Downy Brome ◽  
Tillage Practices ◽  
Agricultural Production Systems

Downy brome (Bromus tectorumL. # BROTE) has developed into a severe weed in several agricultural production systems throughout North America, particularly on rangeland and in winter wheat (Triticum aestivumL.). Several million hectares of winter wheat, pastureland, alfalfa (Medicago sativaL.), grass seed fields, and overgrazed rangeland, as well as other crops, have been invaded by this annual grass since its introduction into this hemisphere. Downy brome is most abundant in the Great Basin and Columbia Basin areas of the western United States, but is found throughout the continental United States and parts of Canada and Mexico. In some cases, the vegetation on overgrazed rangeland consists totally of downy brome, while winter wheat growers in the western United States proclaim it as their worst weed problem. Changes in tillage practices that are currently being implemented for the control of soil erosion coupled with the lack of selective herbicides for the control of downy brome have aided its increase and spread.

Sign in / Sign up

Export Citation Format

Share Document