Climate variability in the Pacific Northwest and its effect on stripe rust disease of winter wheat

Wheat stripe rust (Puccinia striiformis West.) epidemics are confined predominantly to the Pacific Northwest in the U. S. A. because of climate. This disease was frequently reported until the late 1930's and then virtually absent until the late 1950's. Since the severe epidemic in 1961, stripe rust has been frequently severe on winter wheat and has caused losses in susceptible cultivars in many years. Because of the unusual history of stripe rust in this region, the possibility that climate variability affected the pattern of rust occurrence was investigated. Meteorological data for seven locations in Oregon, Washington, and Idaho were analyzed. In 1961–1974 for the Columbia Basin locations, January and February temperatures averaged 1.20° C higher than during the period 1935–1960; however, April temperatures averaged 1.28° C lower in 1961–1974 than during the earlier period. Monthly precipitation averages have not varied more than 12.7 mm in any month. Between 1961–1974, December snowfall almost doubled over that in 1935–1960; snowfall in February decreased over 50% from the earlier period. Data was computed on a seasonal basis since 1901 and considered in respect to stripe rust epidemics. Since 1961, above-normal winter and below-normal spring temperatures have increased the frequency and severity of stripe rust epidemics in the Pacific Northwest. The direction of temperature and precipitation trends varied with the time period considered. How the climate variability which has occurred may have affected winter wheat growth and yields is postulated. Studies such as this should be useful to researchers modelling crop-yields, agronomists evaluating results from field experiments and to researchers studying fluctuations in pest populations.This research was supported by a National Science Foundation Grant (ATM 76-21725); Climate Dynamics Program, Division of Atmospheric Sciences.     

Spatial statistics for predicting fluid flow through a single rock fracture

Steady-state laminar flow through single rock fractures is predicted in terms of spatial statistics computed from the arrangement of voids and contact areas within the fracture. Within the voids, aperture is assumed to be constant. One statistic measures how often pixels alternate from void to contact area in the rows parallel to the flow direction. Two others measure the dispersion of voids in the rows and columns of the pattern. Fractures with complexity typical of observed data are simulated. Flow through patterns with 80% voids is predicted in terms of a linear combination of the three statistics. Using an extended model involving one of the three statistics, flow through patterns with other void fractions is predicted.The author did this work at the Earth Sciences Division at Lawrence Berkeley Laboratory, Berkeley, California. It is part of a Ph.D. thesis which was submitted at Stanford University.     

Quantifying how climatic factors affect variation in plant disease severity: A general method using a new way to analyze meteorological data

A general method is presented for analyzing how climatic conditions affect plant disease severity. An example of its application is given for the analysis of stripe rust (caused by Puccinia striiformis) data on winter wheat cultivar Gaines and climatic data collected at Pullman, WA. for 1968–1986. A computer program WINDOW was written to identify the climatic factors most highly correlated with disease. This program is designed to utilize meteorological data for an entire growing season of a crop as well as to include climatic conditions preceding planting. This program uses an iterative process to examine variable-length segments of meteorological data in a more exhaustive analysis than previously possible. Climatic factors considered include: mean maximum, minimum, and average temperature; total and frequency of precipitation; consecutive days with and without precipitation; accumulation of negative and positive degree days; and number of days with extreme temperature events. Variables that were highly correlated with disease were the basis for regression models that were developed to predict disease severity index for each of the three cultivars. Two- and three-variable models explained, respectively, 75 and 76% of the variation in disease from year to year. Predictions (which could be made early enough in the growing season to allow application of chemical control) were evaluated on the basis of whether years with severe disease were accurately predicted. Models were validated using Allen's PRESS statistic and by application to new data. The method is potentially applicable to studies of how climatic conditions affect the populations or productivity of other types of organisms.This research was supported by a National Science Foundation Grant (ATM 85-03115), Climate Dynamics Program, Division of Atmospheric Sciences.     

Surface temperatures in canterbury coastal waters (note)

Between September 1966 and August 1968 Canterbury coastal waters showed an annual range in surface temperature of 7–9°c. Temperatures were highest from January to March and lowest in July and August.     

Physical Properties and their Relationship to Texture and Consolidation Effects in Pliocene-Quaternary Sediments from Madeira Abyssal Plain

Multi-sensor core logger data and index properties were measured onboard the JOIDES resolution during ODP Leg 157 and compared with grain size distribution and carbonate contents measured in the on-shore laboratory. Cored sediments are similar in grain size, but very variable in carbonate content. Magnetic susceptibility clearly defines the volcanic turbidite layers, whereas GRAPE density and acoustic velocity help to define the coarser (silty) bases of some organic or calcareous turbidite layers. Index properties are mostly controlled by consolidation effects.     

Physical Properties and their Relationship to Texture and Consolidation Effects in Pliocene-Quaternary Sediments from Madeira Abyssal Plain

Multi-sensor core logger data and index properties were measured onboard the JOIDES resolution during ODP Leg 157 and compared with grain size distribution and carbonate contents measured in the on-shore laboratory. Cored sediments are similar in grain size, but very variable in carbonate content. Magnetic susceptibility clearly defines the volcanic turbidite layers, whereas GRAPE density and acoustic velocity help to define the coarser (silty) bases of some organic or calcareous turbidite layers. Index properties are mostly controlled by consolidation effects.     

Limatic variables that control development of stripe rust disease on winter wheat

The frequency and severity of the stripe rust disease (caused byPuccinia striiformis) on winter wheat in the Pacific Northwest of the U.S.A. has increased since 1958 in association with climatic variation. From 1968–1979, rust intensities on ‘Gaines’ wheat were most highly correlated with accumulated negative degree days (NDD) between 1 December and 31 January and positive degree days (PDD) between 1 April and 30 June. NDD and PDD were calculated from a 7 °C base. Linear regression equations using NDD alone accounted for 76% of the variation in stripe rust. When NDD and PDD were combined, 88% of the variation in stripe rust was explained. When a growth index (GI), and NDD plus PDD were used as independent variables in a multiple regression analysis, 91% of the variation in disease was explained. Frequency of precipitation in June was correlated with stripe rust intensity, but when it was added to the multiple regression analysis, it explained less than an additional 1% of the variation. The relationships between NDD, PDD, and disease index help to explain why stripe rust was not severe from 1941 to 1957. Methods used in this research should be applicable to similar studies of the effect of climatic variation on other pests. This research was supported by a National Science Foundation Grant (ATM 76-21725), Climate Dynamics Program, Division of Atmospheric Sciences.