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The active layer is the zone above permafrost that experiences seasonal freeze and thaw. Active‐layer thickness varies annually in response to air and surface temperature, and generally decreases poleward. Substantially less is known about thaw variability across small lateral distances in response to topography, parent material, vegetation, and subsurface hydrology. A graduated steel rod was used to measure the 1998 end‐of‐season thaw depth across several transects. A balanced hierarchical sampling design was used to estimate the contribution to total variance in active‐layer depth at separating distances of 1, 3, 9, 27, and 100 meters. A second sampling scheme was used to examine variation at shorter distances of 0.3 and 0.1 meter. This seven‐stage sample design was applied to two sites in the Arctic Foothills physiographic province, and four sites on the Arctic Coastal Plain province in northern Alaska. The spatial variability for each site was determined using ANOVA and variogram methods to compare intersite and inter‐province variation. Spatial variation in thaw depth was different in the Foothills and Coastal Plain sites. A greater percentage of the total variance occurs at short lag distances (0–3 meters) at the Foothills sites, presumably reflecting the influence of frost boils and tussock vegetation on ground heat flow. In contrast, thaw variation at the Coastal Plain sites occurs at distances exceeding 10 meters, and is attributed to the influence of well‐developed networks of ice‐wedge polygons and the presence of drained thaw‐lake basins. This information was used to determine an ongoing sampling scheme for each site and to assess the suitability of each method of analysis. 相似文献
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This research examines state support for higher education by first ascertaining the amount supplied and demanded of this service. The approach assumes that supply and demand occur simultaneously, and that each is affected by higher education spending policies among the states. We argue that enrollment is the most satisfactory proxy for both supply and demand. State policy is measured as expenditure effort. We estimate three time-series equations using two-stage least squares regression with data for the years 1986–95. In the final equation, supply/demand (enrollment) emerges as the strongest predictor of state spending effort. Commitment to higher education (effort) is also especially sensitive to variations in the number of employees (per student). Employee costs clearly are a major factor in fueling increases in state higher education spending effort. State per capita income exerts a negative effect on the final dependent variable. Poor states exert greater financial effort in support of their colleges and universities than do more affluent states. 相似文献
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