A spatial modeling approach for predicting forage production and utilization on a semidesert grassland (original) (raw)
1993
Abstract
Geographic analysis procedures and multiple linear regression techniques are applied to the problem of generalizing forage production and utilization information from sample point data. The study involves the application of these procedures to predict the spatial variability of mean production and utilization of Diaitaria californina on the Santa Rita Experimental Range near Tucson, Arizona. Analysis of ten-year means from data collected between 1957 and 1966 indicate that variability in production is a function of mean summer precipitation and elevation. Variability in utilization is found to be a function of land slope and distance from livestock water. Geostatistical procedures are used to estimate mean summer precipitation. A geographic information system (GIS) is used to automate multiple linear regression functions for points in a raster data structure. The geographic analysis procedures are used to describe the spatial variability of the data in a mapped form. Management appl...
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