Huntington North Dam Outlet Works Modification and Carriage of Non-Project Water through Emery County Project Facilities Final Environmental Assessment and Finding of No Significant Impact

This document is an Environmental Assessment (EA) for the conveyance of 14,074 acre-feet per year of non-project water through Huntington North Reservoir and the related outlet works modification and spillway construction. Huntington Cleveland Irrigation Company (HCIC) has requested Bureau of Reclamation (Reclamation) authorization for HCIC to convey non-project water through Emery County Project facilities

Impact of shortened crop rotation of oilseed rape on soil and rhizosphere microbial diversity in relation to yield decline

Oilseed rape (OSR) grown in monoculture shows a decline in yield relative to virgin OSR of up to 25%, but the mechanisms responsible are unknown. A long term field experiment of OSR grown in a range of rotations with wheat was used to determine whether shifts in fungal and bacterial populations of the rhizosphere and bulk soil were associated with the development of OSR yield decline. The communities of fungi and bacteria in the rhizosphere and bulk soil from the field experiment were profiled using terminal restriction fragment length polymorphism (TRFLP) and sequencing of cloned internal transcribed spacer regions and 16S rRNA genes, respectively. OSR cropping frequency had no effect on rhizosphere bacterial communities. However, the rhizosphere fungal communities from continuously grown OSR were significantly different to those from other rotations. This was due primarily to an increase in abundance of two fungi which showed 100% and 95% DNA identity to the plant pathogens Olpidium brassicae and Pyrenochaeta lycopersici, respectively. Real-time PCR confirmed that there was significantly more of these fungi in the continuously grown OSR than the other rotations. These two fungi were isolated from the field and used to inoculate OSR and Brassica oleracea grown under controlled conditions in a glasshouse to determine their effect on yield. At high doses, Olpidium brassicae reduced top growth and root biomass in seedlings and reduced branching and subsequent pod and seed production. Pyrenochaeta sp. formed lesions on the roots of seedlings, and at high doses delayed flowering and had a negative impact on seed quantity and quality

The impact of islet mass, number of transplants, and time between transplants on graft function in a national islet transplant program

The UK islet allotransplant program is nationally funded to deliver one or two transplants over 12 months to individuals with type 1 diabetes and recurrent severe hypoglycemia. Analyses were undertaken 10 years after program inception to evaluate associations between transplanted mass; single versus two transplants; time between two transplants and graft survival (stimulated C-peptide >50 pmol/L) and function. In total, 84 islet transplant recipients were studied. Uninterrupted graft survival over 12 months was attained in 23 (68%) single and 47 (94%) (p =.002) two transplant recipients (separated by [median (IQR)] 6 (3–8) months). 64% recipients of one or two transplants with uninterrupted function at 12 months sustained graft function at 6 years. Total transplanted mass was associated with Mixed Meal Tolerance Test stimulated C-peptide at 12 months (p <.01). Despite 1.9-fold greater transplanted mass in recipients of two versus one islet infusion (12 218 [9291–15 417] vs. 6442 [5156–7639] IEQ/kg; p <.0001), stimulated C-peptide was not significantly higher. Shorter time between transplants was associated with greater insulin dose reduction at 12 months (beta −0.35; p =.02). Graft survival over the first 12 months was greater in recipients of two versus one islet transplant in the UK program, although function at 1 and 6 years was comparable. Minimizing the interval between 2 islet infusions may maximize cumulative impact on graft function

Habitat Characteristics Associated with Ring-necked Pheasant Use of Winter Food Plots in Eastern South Dakota

A cooperative program between sportsmen\u27s groups, private landowners, and the Department of Game, Fish and Parks has resulted in placement of numerous winter food plots, primarily of corn, on private lands in eastern South Dakota with the intent to help wintering ring-necked pheasants (Phasianus colchicus) survive. The objective of this study was to evaluate levels of pheasant use of food plots in relation to characteristics of food plots and their peripheral habitats. Thirty food plots were studied during the winter of 1988-89 and 45 during the winter of 1989-90; 59 of these were unique to a year and 16 were measured during both years. Pheasant numbers in food plots were monitored throughout each winter both by counting tracks (per 50 m) following fresh snow and counting pheasants flushed within and immediately adjacent to food plots during each month. When snow was lacking, data collection was limited to flush counts only. Twelve habitat variables potentially related to pheasant use of food plots were measured from aerial photographs within a 300 and a 600 meter radius of each food plot center (28.3 ha area and 113.1 ha area, respectively). Variation in average tracks/50 m and flush counts among 75 food plots (years combined) was related to the selected habitat variables using multiple regression (MAXR) analysis. Variation in average flush counts (R2 = 0.73) was more associated with habitat variables than was variation in average track counts (R2 = 0.45). Variables measured within a 300 m radius were better predictors of pheasant use than variables measured within a 600 m radius. Percent of the peripheral area in dense wetland emergents and willow (Salix spp.) patches was the best predictor of pheasant use of food plots. Percentage cover of tall grassland (\u3e 76 cm) and distance from windward to leeward side of the food plot also were correlated with use of food plots. Shelterbelts, even with heavy understory, did not enhance use of food plots by pheasants. Extreme snowfall and drifting may alter this relationship

A carbon monitoring system for mapping regional, annual aboveground biomass across the northwestern USA

This paper presents a prototype Carbon Monitoring System (CMS) developed to produce regionally unbiased annual estimates of aboveground biomass (AGB). Our CMS employed a bottom-up, two-step modeling strategy beginning with a spatially and temporally biased sample: project datasets collected and contributed by US Forest Service (USFS) and other forestry stakeholders in 29 different project areas in the northwestern USA. Plot-level AGB estimates collected in the project areas served as the response variable for predicting AGB primarily from lidar metrics of canopy height and density (R ^2 = 0.8, RMSE = 115 Mg ha ^−1 , Bias = 2 Mg ha ^−1 ). This landscape model was used to map AGB estimates at 30 m resolution where lidar data were available. A stratified random sample of AGB pixels from these landscape-level AGB maps then served as training data for predicting AGB regionally from Landsat image time series variables processed through LandTrendr. In addition, climate metrics calculated from downscaled 30 year climate normals were considered as predictors in both models, as were topographic metrics calculated from elevation data; these environmental predictors allowed AGB estimation over the full range of observations with the regional model (R ^2 = 0.8, RMSE = 152 Mg ha ^−1 , Bias = 9 Mg ha ^−1 ), including higher AGB values (>400 Mg ha ^−1 ) where spectral predictors alone saturate. For both the landscape and regional models, the machine-learning algorithm Random Forests (RF) was consistently applied to select predictor variables and estimate AGB. We then calibrated the regional AGB maps using field plot data systematically collected without bias by the national Forest Inventory and Analysis (FIA) Program. We found both our project landscape and regional, annual AGB estimates to be unbiased with respect to FIA estimates (Biases of 1% and 0.7%, respectively) and conclude that they are well suited to inform forest management and planning decisions by our contributing stakeholders. Social media abstract Lidar-based biomass estimates can be upscaled with Landsat data to regionally unbiased annual maps