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<br />.. 582 - <br /> <br />\- <br /> <br />1.0 <br /> <br />E <br /> <br />\~"nO~ 0 <br />~ <br />SUR F ACE T RAN S P 0 R TP <br />~ARSE----SPARSE---DE~-DENSE--- <br />. 0 <br />E c Q~k~ y <br />- STOCKRAISlNG CROPSa STOCK/ :ROPS-;STocK:-aMANuFACTURING-- <br />DEN SIT Y 0 F R U R A L <br />_ _ _ __2:....Q2:.~--'=_e~J_I_O_~ _~~R__k_~ _ __ __ <br />2 TO 6 6 JO 18 18 TO 45 18 TO 45 <br />(18 TO 45 IN IRRIGATED....AREAS) <br />0' <br />___ _~_ ___S_O_'_~S____ __ _____ <br />~T a BROWN PRAIRIE a CHERNOZEM GREY-BROWN PODlOLIC - <br /> <br />__ LAND USES <br />SUBHUMID GRAziNG-'RRIGATED CROPS-;-PASTURE CROPS-CROPS -PASTUREWOODLAND <br />AND PASTURE I I <br /> <br />N A T U R A L V E GET A T ION <br />0.2 GRAMAGRASS SAND SAGE -SAND GRASSNEEDLEGRASS - -OAK=H,CKORY-BLUESTEM <br />BUFFALO GRASS COTTONWOOD-WILLOW WEATGRASS <br /> <br />08 <br /> <br />z <br />o <br />I- 0.6 <br /><l <br />I- <br /> <br />a.. <br />u <br />w <br />a:: <br />a.. 0.4 <br />...J <br /><l <br />::> <br />z <br />z <br /><l <br /> <br />P H Y S lOG RAP H Y <br />- -SANO-- - -- LOE SS-- -- --MORAINE---TILLPRATRi'E-- <br /> <br />LINCOLN <br />COUNTY <br />(3) <br /> <br />~ <br />DODGE OMAHA <br />COUNTY <br />(4) <br /> <br />DENVER MORGAN <br />COUNTY <br />(2) <br /> <br />t r-t <br />MAHASKA MCDONOUGH PEORIA <br />COUNTY COUNTY <br />(5) (6) <br /> <br />Fig. 7 - Environmental elements arrayed along the 100 C isotherm crossing a precipitation <br />gradient <br /> <br />Using numerical data from an agricultural census of six counties that lay close to the 100 C <br />isotherm, an exploration was made of the utility of certain classification techniques in <br />showing the role of precipitation. Locations of five of the counties are shown in Fig. 7. <br />The sixth is Churchill County, Nevada, just east of Reno. Norgan County, Colorado, and <br />Lincoln County, Nebraska, straddle the South Platte River and contain both irrigated bottom <br />lands and dry-farmed and sandhill plains. The three eastern counties are physiographically <br />more homogeneous. <br /> <br />The first classifications sought to describe how the counties differed one from another in <br />terms of the agricultural descriptors. Principal-component analysis (Fig. 8) arrays the <br />counties in two distinct clusters. Component I has a correlation coefficient with precipi- <br />tation of 0.87, while Component II seems related to an irrigation/fallow complex and may be <br />related nonlinearly to preCipitation. There is a suggestion that the irrigation/fallow com- <br />plex may be strongest where precipitation is about 0.35 m. Much less rain, and dry-land <br />farming is impossible; much more rain, and fallowing is unnecessary. Discriminant analysis <br />revealed that a single variable, value of farm equipment, was sufficient to discriminate <br />between the clusters. The next best discriminants were fallow cropland, idle cropland, and <br />land in cover crops. The latter may reflect political aspects of the soil bank program. <br /> <br />A second set of classifications sought to describe how the'agricultural descriptors dif- <br />fered one from another in terms of the county-exemplars. Mapping of the first two com- <br />ponents and cluster analysis revealed three groupings of descriptors, as follows: <br />