630.7 I£6b no. 752 cop. 8 NOTICE. Return or renew all Library Materials! The Minimum Fee for The person charging this material is responsible for its return to the library from which it was withdrawn on or before the Latest Date stamped below. Theft, mutilation, and underlining of book* are reasons for discipli- nary action and may result In dismissal from the University. To renew call Telephone Center, 333-8400 UNIVERSITY OF ILLINOIS LIBRARY AT URBANA-CHAMPAIGN •s foi'Ol L161— O-1096 SOIL PRODUCTIVITY INDEXES FOR ILLINOIS COUNTIES AND SOIL ASSOCIATIONS Bulletin 752 University of Illinois at Urbana-Champaign College of Agriculture Agricultural Experiment Station ABSTRACT The 2 percent sample soil data for the Illinois Conservation Needs Inventory were combined with produc- tivity indexes to obtain state, county, and subcounty soil productivity characteristics that were used to evaluate variations in rural land quality. State soil productivity distributions were developed to provide a general frame- work of soil quality. Frequency diagrams (histograms) of county soil productivity indexes were constructed. Ratios comparing soil productivity patterns for the state and each county were developed and analyzed. Pro- ductivity characteristics of soil associations were assembled for Illinois and for each county in a table that lists the percentage of each county in each soil association, the percentage of each soil association in each of seven productivity index categories used in the histogram format, and comparisons of ratios between state and county soil association productivity indexes within the seven productivity index categories. The productivity index data can be used to compare the relative quality of soil for agricultural use between counties and between soil asso- ciations within counties. These data should aid county and state officials in evaluating rural land assessments. Additional index words: Conservation Needs Inventory, soil productivity distributions. CONTENTS Development of data 2 State patterns of productivity 2 County patterns of productivity 9 State soil association patterns of productivity 37 County soil association patterns of productivity 38 Suggested rural land evaluation procedure 46 Discussion 49 Literature cited 49 TABLES FIGURES 1 County average quarter-section tracts 1 General soil map for Illinois 3 productivity indexes 1 2 Basic management PI distributions for Illinois 8 2 Soil series in Illinois grouped by association area 3 High management PI distributions for Illinois 8 on general soil map of Illinois 4-7 4 Basic management PI ratios for Illinois 8 3 Frequency distribution of basic management Pi's 5 High management PI ratios for Illinois 8 for Illinois soil association areas 10 6 Annotated diagram of frequency distribution of 4 Frequency distribution of high management Pi's high management Pi's for counties 9 for Illinois soil association areas 11 7 Frequency distribution of county high and basic 5 Percentage distribution of soils in various pro- management Pi's 12-37 ductivity index classes for soil association areas 8 Cross section of Hancock County soil association within counties 39-46 map 48 6 Field guidelines for estimating high management 9 Hypothetical example of relationship between sale PI categories for soil association areas 47 value and tract PI 48 Prepared by P. W. Mausel, Associate Professor of Geography, Indiana State University, Terre Haute; E. C. A. Runge, formerly Professor of Agronomy, University of Illinois at Urbana-Champaign, now Professor and Chairman of Agron- omy, University of Missouri-Columbia; and S. G. Carmer, Professor of Biometry, Department of Agronomy, Univer- sity of Illinois at Urbana-Champaign. The authors are indebted to Norman Cooprider, Department of Geography and Geology, Indiana State University, for his assistance in cartography and photography. Urbana, Illinois August, 1975 Publications in the bulletin series report the results of investigations made or sponsored by the Experiment Station. The Illinois Agricul- tural Experiment Station provides equal opportunities in programs and employment. 3M — 8-75 — 31333 5. EVALUATING RURAL LAND for purposes of tax assessment is often inconsistent and thus inequitable in many areas of Illinois and other states. Generally, these incon- sistencies in evaluation reflect the paucity of information that would permit governmental officials to make soil quality judgments that would be consistent with one an- other and thus be equitable over large areas. The soils information currently used by assessors to make land evaluation decisions varies in amount and quality from area to area. Modern county soil survey reports provide a wealth of detailed soils data that are coming to be widely used by assessors to judge soil qual- ity, but many areas lack data in this form. Nine Illinois counties have no published detailed soil reports. Detailed soil reports for another 57 counties were published in the period 1911-1945. Only 36 counties have modern (post- 1945) soil reports, published or being prepared for pub- lication, that can be suitably used to estimate relative soil quality and, indirectly, land value. It is difficult to evaluate soil quality consistently when counties have greatly differing forms of soil information. However, all Illinois counties do have soil association maps that indicate generalized soil distributions of two or more soil series, and they have detailed soil maps for the Conservation Needs Inventory (CNI) soil data. (5).1 Detailed soil maps were made for quarter-section tracts of land for each township (36 sq. mi. or 93 sq. km.) in the Illinois CNI study (2 percent sample). For each CNI tract a Productivity Index (PI) was developed (2) by finding the weighted average PI for the soil mapping units on the tract. The soil association in which the tract occurred was recorded in the CNI study (5). Frequency distributions of CNI quarter-section tract Pi's were pre- pared by counties, by soil associations for each county, and for Illinois. In the interim period before modern county soil sur- veys are available for all counties, the results reported in this bulletin and in less complete form in Mausel et al. (4) should help assessors and others interested in evalu- ating soil quality make more consistent decisions in coun- ties that have inadequate soil data. State officials charged 1 Italicized numerals refer to entries in Literature Cited. Table J. — County Average Quarfer-Secf/on Tracts Productivity Indexes (PI) High Basic High Basic High Basic County manage- manage- County manage- manage- County manage- manage- ment PI ment PI ment PI ment PI ment PI ment PI Adams 98 60 Hardin 73 39 Morgan 124 77 Alexander 99 59 Henderson 119 73 Moultrie 146 93 Bond 106 60 Henry 123 76 Ogle 126 78 Boone 122 77 Iroquois 125 78 Peoria 113 69 Brown 100 59 Jackson 93 50 Perry 99 51 Bureau 133 84 Jasper 104 56 Piatt 145 93 Calhoun 91 55 Jefferson 95 48 Pike 113 68 Carroll 120 74 Jersey 106 64 Pope 81 43 Cass 109 67 Jo Daviess 92 54 Pulaski 102 57 Champaign 145 93 Johnson 76 40 Putnam 123 76 Christian 133 84 Kane 132 83 Randolph 101 55 Clark 107 59 Kankakee 120 75 Richland 104 54 Clay 106 55 Kendall 133 84 Rock Island 117 72 Clinton 104 57 Knox 123 75 St. Clair 110 64 Coles 133 82 Lake 116 70 Saline 104 57 Cook 116 69 LaSalle 134 84 Sangamon 137 87 Crawford 107 59 Lawrence 108 62 Schuyler 105 63 Cumberland 113 63 Lee 131 83 Scott 114 70 DeKalb 146 93 Livingston 132 82 Shelby 120 70 DeWitt 142 90 Logan 143 91 Stark 134 82 Douglas 144 92 McDonough 138 86 Stephcnson 118 73 DuPage 122 75 McHenry 120 74 Tazewell 128 81 Edgar 140 89 McLean 143 91 Union 98 55 Edwards 100 54 Macon 146 93 Vermilion 132 82 Effingham 105 55 Macoupin 117 71 Wabash 115 68 Fayette 105 58 Madison 112 67 Warren 138 86 Ford 130 81 Marion 99 52 Washington 98 53 Franklin 98 51 Marshall 125 77 Wayne 103 54 Fulton 110 67 Mason 104 65 White 105 61 Gallatin 112 67 Massac 102 55 Whiteside 121 76 Greene 116 72 Menard 128 80 Will 117 71 Grundy 131 84 Mercer 126 77 Williamson 89 46 Hamilton 96 51 Monroe 102 59 Winnebago 120 75 Hancock. . ; 115 70 Montgomery 113 67 Woodford 131 82 with equalizing assessment between counties can com- pare average assessed value with county average Pi's (Table 1) or with the frequency distribution of CNI tract Pi's (Table 5) as part of their equalization pro- cedure. This study can also be used to help assessors, probably with the assistance of a soil scientist, gain a further understanding of soil and PI relationships, which should lead to more equitable land assessment. It is hoped that county assessors will use specific soils infor- mation for each quarter-section tract in their counties. DEVELOPMENT OF DATA Each of the more than 5,000 quarter-section samples that make up the Illinois CNI has an accurate enumera- tion by acres of all soil mapping units (soil series, sl'ope, and amount of topsoil remaining) located within the sample plot (5) . These soil mapping units were recorded on computer cards or tape by number of acres in each soil series-slope-erosion class, by sample plot location, and by soil association area. The 26 soil associations identified for Illinois are given in Figure 1 and Table 2. Computer programs were written to assemble these data in forms used to provide patterns of soil distribution in Illinois. Two sets of soil PI data at basic and high management levels (2) were combined with the computer-stored soil series distribution information. The basic and high man- agement Pi's of each soil mapping unit were calculated and recorded on cards for computer processing. Combining the detailed soil distribution data and the Pi's of the soil mapping units allowed us to generate previously unavailable data. The most significant infor- mation obtained from these procedures was as follows: 1. Basic and high management soil PI average for each sample plot. 2. Basic and high management soil PI averages for each county (average PI of all sample plots within a county) . 3. Basic and high management soil PI state averages (average PI of all sample plots within the state). 4. Basic and high management soil PI averages for each state soil association (average PI of all sample plots within a state soil association) . 5. Frequency distribution, expressed by percent of sample plot soil in each of seven PI categories, of soil PI under basic and high management for individual soil sample plots by county. 6. Frequency distribution of basic and high manage- ment soil PI for soil associations by county. 7. Frequency distribution of basic and high manage- ment soil PI for soil associations by state. STATE PATTERNS OF PRODUCTIVITY County averages for basic (Fig. 2) and high (Fig. 3) management productivity indexes were plotted on a map to provide accurate, albeit general, patterns of soil pro- ductivity. The boundaries delineated on the maps were constructed from interpolation between county average PI values, which were considered to be located in the geographic center of each county. This procedure suc- cessfully indicates general productivity differences among areas of the state; however, the small scale of the map, the interpolated nature of the boundaries, and the use of county average PI data limit the usefulness of these maps. Although there is a great difference in actual produc- tivity of soils at the different levels of management, the relative productivity patterns indicated on the two maps are similar. The areas of highest soil productivity, regard- less of management level, are in the east-central and north-central counties. An example from this region is Champaign County, with basic and high management average Pi's of 93.4 and 145.3, respectively. Many north- western areas have lower county average Pi's overall than the north-central and east-central parts of the state but have higher Pi's than southern Illinois. For example, under conditions of basic and high management, respec- tively, Hancock County (northwestern Illinois) has Pi's of 70.3 and 115.0, while White County (southern Illi- nois) has Pi's of 60.7 and 105.2. Comparing basic and high management PI county averages shows that significant soil productivity changes are associated with level of management. The PI fre- quently increases by 60 percent or more when manage- ment practices improve from basic to high. Moreover, the percentage improvement in PI is generally much greater on naturally poor soils than on naturally good soils. For example, the percentage increase in PI from basic to high management in Champaign County is 55.5 percent, while in White County the change is 73.3 per- cent. The PI of Franklin County, in southern Illinois, increases 91.4 percent from basic to high management. A second set of maps (Figs. 4 and 5), developed from the same PI data, uses a ratio method to compare the county average PI to the state average PI. A county ratio of 1.00 indicates that the productivity average of the combined soils in the county is equal to the average state soil productivity. An analysis of Figures 2 through 5 reveals the general regional soil productivity differences for Illinois. Figure 1. General soil map for Illinois (source: I). DARK-COLORED SOILS DEVELOPED PRIMARILY FROM LOESS A Joy - Tama - Muicaline • Ipava • Sable 6 Sidell • Callin • Flanagan - Drummer C W«nona - Rutland - Strealor D Harmon - Hetriek - Virden E Oconee - Cowden - Piaia F Hoyleton . Oin. - Huey DEVELOPED PRIMARILY FROM GLACIAL DRIFT G Warsaw • Carmi - Rodman H Ringwood - Gritwold - Durand I La Rose - Saybrook - Lisbon J Elliott • Ashkum - Andrei K Swygert • Bryee - Clarence • Rowe LIGHT-COLORED SOILS DEVELOPED PRIMARILY FROM LOESS L Sealon - Fayerte - Slronghui M ftirkbeck - Word • Rusiell N Clary - Clinton - Keomah O S'ookey • Alford - Muren P Hoimer - Stoy - W«ir Q Ava - Bluford • Wynooie R Granlsburg - Robbi - Welliton DEVELOPED PRIMARILY FROM GLACIAL DRIFT S Fox - Homer - Caico T Me H«nry - Lop*«r • Pecotonica U Slrawn - Miami V Morl.y - Mount - Be«ch«r - Eylor DARK- AND LIGHT-COLORED SOILS DEVELOPED PRIMARILY FROM MEDIUM- AMD FINE-TEXTURED OUTWASH W Littleton - Proctor - Pfano • Camd«n • Hurst - Ginat DEVELOPED PRIMARILY FROM SANDY MATERIAL X Hagvner • Ridg«vill* • Bloomficid - Alvin DEVELOPED PRIMARILY FROM MEDIUM-TEXTURED MATERIAL ON BEDROCK Y Channahon • Dodgeville - CXibuquA - Derinda DEVELOPED PRIMARILY FROM ALLUVIUM Z lawion • B«oueoup - Darwin - Hoymond • Bclknap SCALE IH MILEt UNIVERSITY OF ILLINOIS AGRICUITURAI EXPERIMENT STATION In Cooperation Wirh U. 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A 1 1 1 i i i •j f 1 S i fine tex. mat. >4 ft. U and important uncc ns and symbols use med. = medium; i poor" may also be soils often occur in | 3 i 1 T3'3— «T) £««•§£ _«'> tj *_« n BASIC PRODUCTIVITY INDEX ( County Average ) Sto(« Av« = 70.2 HIGH PRODUCTIVITY INDEX ( County Average ) Stall Av«. = 1168 Figure 2. Basic management PI distributions for Illinois. Figure 3. High management PI distributions for Illinois. .eo -Wi.00 BASIC PRODUCTIVITY INDEX RATIOS HIGH PRODUCTIVITY ,o INDEX RATIOS ' Figure 4. Basic management PI ratios for Illinois. Figure 5. High management PI ratios for Illinois. COUNTY PATTERNS OF PRODUCTIVITY Frequency diagrams that reflect soil productivity vari- ations in seven PI categories at two different manage- ment levels (basic and high) were constructed to provide detailed PI distribution data within each county. These diagrams present visual patterns of soil productivity within PI categories. An annotated example of the fre- quency histogram format is given in Figure 6. In the example, the Hancock County high manage- ment frequency diagram shows that 17.7 percent of the soils in the county are in the PI category of less than 70. The approximate percentage distribution is represented by the height of the unshaded part of the bar graph above each PI category; the exact statistical value of the percentage distribution of county soils by PI category is printed at the top of each PI category bar. The height of the shaded portion of each bar repre- sents the state average percentage of soils within a given PI category. The approximate state average percentage of soils can be estimated from the bar graph alone, but the exact statistics are available in Tables 3 and 4. In Hancock County, the shaded portion of the bar for the high management PI category of less than 70 indicates that not quite 10 percent of the state's soils have a PI in that range. The exact state average percentage of soils with Pi's of less than 70 is 8.7 percent (Table 4). Each frequency distribution graph has a ratio scale for comparing the percentage of county soils in a par- ticular PI category with the average percentage of all Illinois soils in the same PI category. A ratio of 1.00 indi- cates that the county and state soil distributions are iden- tical within a given PI category. A county ratio of more than 1 .00 in a category means that the percentage of soil within the category is more than the state average for that PI category. Conversely, a county PI category ratio of less than 1.00 shows that the percentage of soils in the county PI category is below the state average. Basic and high management PI frequency diagrams are designed to show trends of soil productivity within Figure 6. Annotated diagram of frequency distribution of high management Pi's for counties. HANCOCK COUNTY HIGH PI County Ave. PI 115.0° County Ave. Ratio .98 -r 50% LT70 70-85 85-100 100-115 115-130 130-145 GE 145 HIGH MANAGEMENT PI CATEGORIES •' Based on high input levels thought to be near the levels required for maximum profit. For specific high management characteristics see (2, p. 9). b Productivity index average of all soils in the county divided by the productivity index average of all soils in the state. c Percentage of county soils in a PI category divided by the average percentage of state soils in the same PI category. The solid continuous line indicates the ratios of the PI categories. d The exact percentage of the county's soil in a specific PI category. 8 The top of the unshaded portion of each bar represents the percentage of the county's soil in that PI category. f The top of the shaded portion of each bar represents the average state percentage of soils in that PI category. 10 Table 3. — Frequency Distribution of Basic Management Pi's for Illinois Soil Association Areas Soil Percent of soils in each basic management PI category" association 23 45 55 65 75 85 95 PI area <40 40-50 50-60 60-70 70-80 80-90 >90 A 2. 3 1.4 4 7 2. 9 13.0 6.4 69.3 86.6 B 0. 6 0.7 2 3 1 9 3.9 5.7 85.0 91.5 C 1 . 3 0.7 2 5 4 6 3.3 20.6 67.0 88.6 D 3. 1 0.8 6 6 2. 5 14.3 11.9 60.8 84.9 E 6. 1 7.7 15 fi 19 7 38.2 6 7 6.0 66 3 F 8. 4 8.1 9 7 68 3 2.0 2.8 0.7 59.8 G 7 4 4 1 9 5 13 1 31 3 16 4 18 3 72 1 H 4. 0 7.3 19 3 9 7 7.1 18.3 34.3 74.6 I 1. ? 1 .2 3 7 8 5 4.9 8 7 71 .7 87.6 I 0 7 2 3 7 2 7 1 24 8 19 8 38 1 81 4 K 6. 2 5.3 10 6 22. 0 34.5 5.2 16.2 69.6 L 22. 5 7.3 23 8 6 6 17.6 6.5 15.6 59.4 M 11. 6 5.4 11 6 5. 0 25.8 12.1 28.5 71.4 N 27. 9 3.3 16 7 4 5 23.9 4.5 19.2 60.0 O 13. 7 5.9 35 5 11 8 24.9 6.3 1.9 58.8 P 25. 1 23.3 15 4 22 7 7.2 1.7 4.7 50.8 Q 28. 3 6.7 38 4 21 1 3.7 0.3 1.4 48.7 R 70. 1 4.7 13 4 8 6 3.1 0.0 0.0 33.5 s 10. 6 13.7 6 3 13 6 6.6 39.2 10.1 68.8 T . . . . 2. 7 22 0 6 6 22 8 20 0 5 9 19.9 67.9 u 3 4 15 2 8 q 10 0 24 4 14 7 23 4 72 0 V 8 6 21.7 15 7 16 6 11 3 13.1 13.0 63.1 w 2. 9 3.3 8 2 10 8 13.2 15.3 46.3 80.6 X 17. 4 8.0 14 5 23 1 15.8 12.5 8.7 61.3 Y 24 6 8 6 15 3 10 q 18 1 8 0 14.5 59.2 Z 2. 0 2.5 12 9 21 3 19.5 8.6 33.2 76.0 State 12. 4 5.8 13 7 14 6 13.8 7.4 32.3 70.2 a The PI categories are designated by range (lower line) and average value (upper line). and among counties, as related to state PI distribution data. The county frequency distribution diagrams of Champaign, Hancock, and White Counties illustrate the patterns of soil productivity most typical of east-central, northwestern, and southern Illinois, respectively (see Fig. 7) . Although no single county can be used to characterize a large region, the examples selected give insight into productivity variations within and among counties, as illustrated by the frequency-diagram approach. CHAMPAIGN COUNTY AND ASSOCIATED AREAS Champaign County is one of the most productive areas in Illinois. Many counties in Illinois have the same gen- eral pattern of soil distribution as Champaign County but not all of them are as productive. The most common high management PI frequency distribution pattern for east-central Illinois (and certain northwestern areas) has two main characteristics : a high to very high percentage of soils in the two highest PI categories (>130), and a low percentage of soils in the two lowest PI categories (<85). Generally, more than half (frequently, more than 60 percent) of the soils in east-central Illinois have Pi's of >130, and less than 10 percent of the soils have Pi's of <85. Specifically, 87 percent of Champaign County soils have a PI of > 130, and only 1 percent have a PI of <85. As expected in a county with high soil productivity, the percentage of soils in each of the five lower PI categories (<130) is far below the state aver- age (the PI ratios in those categories are less than 1.00), and the percentage of soils in the two highest categories is above the state average (those PI ratios are greater than 1.00). HANCOCK COUNTY AND ASSOCIATED AREAS Most of the northwestern and far northern areas of the state have soil productivity distribution patterns char- acterized by a large or moderately large percentage of soils in the two highest PI categories and an intermediate percentage of soils in the two lowest PI categories. Coun- ties with this pattern of distribution have at least 30 per- cent of their soils with high management Pi's of >130 and more than 10 percent of their soils with high man- agement PFs of <85. These counties have areas with soil of superior quality, as in east-central Illinois; how- ever, there is also an appreciably larger percentage of poor soil. The overall county average PI is lower than 11 Table 4. Frequency Distribution of High Management Pi's for Illinois Soil Association Areas Soil Percent of soils in each high management PI category* association 40 77.5 92 5 107.5 122.5 137.5 152.5 PI area <70 70-85 85-100 100-115 115-130 130-145 >145 A 1 7 1 q 2 3 5 2 14 7 12 0 62 2 139 2 B .. . 0. 6 0 8 1 2 2.2 4 9 10 3 80 1 146 6 c 0 0 0 o 4 9 2 4 9 5 45 1 38 7 139 1 D 3 1 3 6 2 1 9 0 10 9 65 6 5 6 127 7 E 4 2 11 9 7 R 20 0 43 7 10 8 1 7 110 6 F 4 2 9 3 3 7 9 8 69 3 2 9 0 7 112 8 G 6 1 6 4 8 ? 38.7 18.7 10.7 11 .2 111 3 H 3 •S 5 R 21 7 9 5 11 5 15 8 32 6 121 3 I 0 a 1 9 3 4 4 7 10 4 34 1 45 4 138 3 I 0 3 1 0 6 4 4 9 31 3 32 8 23.3 131 .1 K 1 2 1 4 12 1 13 0 51 3 15 7 5 2 119 1 L 19 4 8 1 13 ? 17.8 21 .7 11.5 8.3 100.4 M 7 3 8 6 3 6 10 6 28 1 21 9 19 9 119 9 N 25 6 6 3 4 5 15 8 27 4 9 9 10 6 99.4 O 12 ? 3 9 17 fi 29 5 29 5 6 2 1 1 102.2 P 17 •S 7 9 27 7 18 0 23 3 2 2 3 6 95.1 O 13 7 16 0 4 4 41 3 23 0 0 6 1 1 97 0 R 36 5 33 7 14 5 4 8 10 4 0 1 0 0 72 2 s 10 0 11 1 10 9 12 3 22 2 30 7 3 4 109.9 T 2 3 22 2 7 0 34 1 11 4 8 3 14 7 109 1 U 1. 9 15 3 4 9 11 0 33.5 16.0 18.2 119.1 v 9 8 17 6 20 6 12 4 22 6 18 4 5 6 108 7 w 2. 2 1. 9 6 4 14.4 15.2 25.3 34.6 129.9 X 14 6 10 3 15 5 30 5 9 4 15 1 4.6 100.2 Y 22 3 11 8 13 .0 14.2 21.3 7.1 10.3 96.9 Z 1 5 1 9 7 8 24.5 24.4 31.6 8.2 121 .4 State 8 7 6 5 7 .8 15.9 22.8 14 8 23.5 116.8 * The PI categories are designated by range (lower line) and average value (upper line). for Champaign County. In Hancock County approxi- mately 47 percent of the soils have high management Pi's of > 130, and 20 percent of the soils have high man- agement Pi's of <85. Comparing PI categories for Hancock County and for the state as a whole (Tables 3 and 4) indicates that Han- cock County is more complex than Champaign County. For example, Hancock County soils in the > 145 PI cate- gory are present only 0.6 times as much as the state aver- age; however, soils in PI category 130 to 145 are repre- sented over three times as often as the state average. Hancock County also has far less soil in PI category 70 to 85 than average for the state (the ratio is 0.3) ; how- ever, there is twice as much Hancock County soil in the PI category of < 70 as is average for the state. Through- out this region the county to state ratios are variable; ratios of greater than 1.00 and less than 1.00 are dis- tributed throughout all PI categories. Soil distribution patterns in which any PI category may be far above or far below the state average soil dis- tribution for that PI category are common in northwest and western Illinois counties (Fig. 7) . WHITE COUNTY AND ASSOCIATED AREAS The counties of southern Illinois — the southern two- fifths of the state — have a third distinctive soil PI pat- tern. The basic pattern is characterized by a relatively low percentage of soils with Pi's of >130 (generally no more than 30 percent, but usually less than 15 percent, of the soils) , and a relatively large percentage of soil in Pi's of <85 (generally at least 10 percent, but frequently more than 20 percent, of the soils) . White County has a large variety of soils characteristic of southern Illinois. Overall, the county has above-aver- age soils for southern Illinois because of a large amount of alluvial soils; however, the pattern of soil productivity is typical of this section of Illinois. About 12 percent of the county has soils with Pi's of >130, and 17 percent has soils with Pi's of <85. White County, like most of southern Illinois, has greater than average percentages of soils in the middle and lower PI categories (Fig. 7). The three counties used as examples illustrate the most common patterns of soil productivity distribution re- vealed through frequency-diagram analysis. Variations of the three basic patterns can also be identified. 12 Figure 7. Frequency distribution of county high and basic management Pi's. ADAMS COUNTY BASIC PI County Ave. PI 59.9 County Ave. Ratio .85 ADAMS COUNTY HIGH PI County Ave. PI 98.3 County Ave. Ratio .84 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 ALEXANDER COUNTY BASIC PI County Ave. PI County Ave. Ratio ALEXANDER COUNTY HIGH PI County Ave. PI County Ave. Ratio LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 BOND COUNTY BASIC PI County Ave. PI County Ave. Ratio BOND COUNTY HIGH PI County Ave. PI 106. ( County Ave. Ratio 36.7 LT40 40-50 50-60 60-70 70-80 80-90 GE90 LT70 70-85 85-100100-115 115-130 130-145 GE 145 BOONE COUNTY BASIC PI County Ave. PI County Ave. Ratio BOONE COUNTY HIGH PI County Ave. PI 122.0 County Ave. Ratio 1.05 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 Figure 7 (continued). 13 BROWN COUNTY BASIC PI County Ave. PI 59.4 County Ave. Ratio .85 BROWN COUNTY HIGH PI County Ave. PI 100.0 County Ave. Ratio .86 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 6EI45 5.0-- 4.0 - • 3.0 -• 2.0-- I.O-- BUREAU COUNTY BASIC PI County Ave. PI 83.8 56.7 County Ave. Ratio 1.19 BUREAU COUNTY HIGH PI County Ave. PI 132.9 -oo/ County Ave. Ratio 1.14 46.7 5.2 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 CALHOUN COUNTY BASIC PI County Ave. PI County Ave. Ratio CALHOUN COUNTY HIGH PI County Ave. PI 91.4 County Ave. Ratio .78 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100100-115 115-130 130-145 GE 145 CARROLL COUNTY BASIC PI County Ave. PI 73.6 County Ave. Ratio 1.05 CARROLL COUNTY HIGH PI County Ave. PI 120.1 County Ave. Ratio 1.03 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 14 Figure 7 (continued). CASS COUNTY BASIC PI County Ave. PI 67.4 County Ave. Ratio .96 CASS COUNTY HIGH PI County Ave. PI 108.8 County Ave. Ratio .93 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GEI45 CHAMPAIGN COUNTY BASIC PI County Ave. PI 93.4 7£ CHAMPAIGN COUNTY HIGH PI County Ave. PI 145.3 County Ave. Ratio 1.33 County Ave. Ratio 1.24 --30% 3.0- - LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 CHRISTIAN COUNTY BASIC PI County Ave. PI 83.7 65.7 County Ave. Ratio 1.19 CHRISTIAN COUNTY HIGH PI County Ave. PI 133.2 5 --50% 5.0-p county Ave. Ratio -•40% 4.0-- --30% 3.0- - -•20% 2.0- - 6 -• 10% 1.0- - 3-1 - - 2'2 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT 70 70-85 85-100 IOO-II5 115-130 130-145 GE 145 CLARK COUNTY BASIC PI County Ave. PI County Ave. Ratio CLARK COUNTY HIGH PI County Ave. PI 106.7 County Ave. Ratio .91 40.9 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 I3O-I45 GE 145 Figure 7 (continued). 15 CLAY COUNTY BASIC PI County Ave. PI 55.1 County Ave. Ratio .78 CLAY COUNTY HIGH PI County Ave. PI 105.5 County Ave. Ratio .90 57^7 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GEI45 CLINTON COUNTY BASIC PI County Ave. PI 57.2 County Ave. Ratio .81 CLINTON COUNTY HIGH PI County Ave. PI 103.7 County Ave. Ratio .89 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 COLES COUNTY BASIC PI County Ave. PI County Ave. Ratio COLES COUNTY HIGH PI County Ave. PI 132.9 County Ave. Ratio 1.14 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100100-115 115-130 130-145 GE 145 COOK COUNTY BASIC PI County Ave. PI 68.7 County Ave. Ratio .98 COOK COUNTY HIGH PI County Ave. PI 115.6 County Ave. Ratio .99 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 16 Figure 7 (continued). CRAWFORD COUNTY BASIC PI County Ave. PI 59.3 County Ave. Ratio .84 CRAWFORD COUNTY HIGH PI County Ave. PI 107.2 County Ave. Ratio .92 38.0 33.3 5.0- 4.0- 3.0- 2.0- 1.0- LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 CUMBERLAND COUNTY BASIC PI County Ave. PI 63.2 County Ave. Ratio .90 29.5 LT70 70-85 85-100 100-115 115-130 130-145 6EI45 CUMBERLAND COUNTY HIGH PI County Ave. PI 113.2 County Ave. Ratip_ .97 12.8 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 DEKALB COUNTY BASIC PI County Ave. PI County Ave. Ratio DEKALB COUNTY HIGH PI LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 DEWITT COUNTY BASIC PI 5.0-r 4.0 - • 3.0 -• 2.0-- I.O-- County Ave. PI County Ave. Ratio 89.6 1.28 DEWITT COUNTY HIGH PI County Ave. PI 141.6 65.7 „<,. County Ave. Ratio 1.21 ^ LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 Figure 7 (continued). 17 DOUGLAS COUNTY BASIC PI County Ave. PI 92.3 6JL,_6 DOUGLAS COUNTY HIGH PI County Ave. PI 144.2 County Ave. Ratio 1.24 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 6EI45 DUPAGE COUNTY BASIC PI County Ave. PI 75.2 County Ave. Ratio 1.07 DUPAGE COUNTY HIGH PI County Ave. PI 122.4 County Ave. Ratio 1.05 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 EDGAR COUNTY BASIC PI County Ave. PI 89.1 County Ave. Ratio 1.27 EDGAR COUNTY HIGH PI County Ave. PI 140.5 County Ave. Ratio 1.20 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100100-115 115-130 130-145 GE 145 EDWARDS COUNTY BASIC PI County Ave. PI County Ave. Ratio 53.9 .77 EDWARDS COUNTY HIGH PI County Ave. PI 100.5 County Ave. Ratio .86 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 18 Figure 7 (continued). EFFINGHAM COUNTY BASIC PI County Ave. PI County Ave. Ratio 55.2 .79 EFFINGHAM COUNTY HIGH PI County Ave. PI 105.5 County Ave. Ratio_ .90 5.0 4.0 3.0 2.0 1.0 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 FAYETTE COUNTY BASIC PI County Ave. PI 57.8 County Ave. Ratio .82 LT70 70-85 85-100 100-115 115-130 130-145 GEI45 FAYETTE COUNTY HIGH PI County Ave. PI 105.4 County Ave. Ratio .90 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 5.0- 4.0- 3.0- 2.0- 1.0- FORD COUNTY BASIC PI County Ave. PI County Ave. Ratio FORD COUNTY HIGH PI County Ave. PI 130.4 County Ave. Ratio 1.12 LT 40 40-50 50-60 60-70 70-80 80-90 GE90 FRANKLIN COUNTY BASIC PI County Ave. PI 51.2 County Ave. Ratio .73 LT70 70-85 85-100100-115 115-130 130-145 GE 145 FRANKLIN COUNTY HIGH PI County Ave. PI 98.0 County Ave. Ratio .84 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 Figure 7 (continued). 19 FULTON COUNTY BASIC PI County Ave. PI 67.3 County Ave. Ratio .96 FULTON COUNTY HIGH PI County Ave. PI 109.5 County Ave. Ratio .94 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 GALLATIN COUNTY BASIC PI County Ave. PI 67.2 County Ave. Ratio .96 GALLATIN COUNTY HIGH PI County Ave. PI 111.5 County Ave. Ratio .96 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 GREENE COUNTY BASIC PI County Ave. PI County Ave. Ratio GREENE COUNTY HIGH PI County Ave. PI 116.1 County Ave. Ratio .99 LT40 40-50 50-60 60-70 70-80 80-90 GE90 LT70 70-85 85-100100-115 115-130 130-145 GE 145 5.0- 4.0- 3.0- 2.0- 1.0- GRUNDY COUNTY BASIC PI County Ave. PI 84.5 County Ave. Ratio 1.20 GRUNDY COUNTY HIGH PI County Ave. PI 131.4 County Ave. Ratio 1.13 LT 40 4O-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 20 Figure 7 (continued). HAMILTON COUNTY BASIC PI County Ave. PI 51.2 County Ave. Ratio .73 HAMILTON COUNTY HIGH PI County Ave. PI 96.3 County Ave. Ratio .82 LLJ LT 40 40-50 50-60 60-70 70-80 80-90 6E 90 LT70 70-85 85-100 100-115 115-130 130-145 GEI45 HANCOCK COUNTY BASIC PI County Ave. PI County Ave. Ratio HANCOCK COUNTY HIGH PI County Ave. PI 115.0 County Ave. Ratio .98 31.8 20.2 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 HARD IN COUNTY BASIC PI 51.7 n County Ave. PI County Ave. Ratio 39.3 .56 HARDIN COUNTY HIGH PI County Ave. PI County Ave. Ratio LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100100-115 115-130 130-145 GE 145 5.0j 4.0 -• 3.0 -• 2.0- • 1.0- • HENDERSON COUNTY BASIC PI County Ave. PI 73.3 County Ave. Ratio 1.04 43.5 T-50% 5.0-r HENDERSON COUNTY HIGH PI County Ave. PI 119.4 County Ave. Ratio 1.02 -r 50% LT 40 40-50 50-60 6O-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 Figure 7 (continued). 21 HENRY COUNTY BASIC PI County Ave. PI County Ave. Ratio 76.0 HENRY COUNTY HIGH PI County Ave. PI 123.0 County Ave. Ratio 1.05 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 6EI45 IROQUOIS COUNTY BASIC PI County Ave. PI County Ave. Ratio -- 2 IROQUOIS COUNTY HIGH PI County Ave. PI 125.4 County Ave. Ratio 1.07 33.9 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 JACKSON COUNTY BASIC PI County Ave. PI County Ave. Ratio 50.0 .71 JACKSON COUNTY HIGH PI County Ave. PI County Ave. Ratio LT40 40-50 50-60 60-70 70-80 80-90 GE90 JASPER COUNTY BASIC PI County Ave. PI County Ave. Ratio 56.5 .80 LT70 70-85 85-100100-115 115-130 130-145 GE 145 JASPER COUNTY HIGH PI County Ave. PI 104.1 County Ave. Ratio .89 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 22 Figure 7 (continued). 5.0 y 4.0 •• 3.0 2.0 1.0 JEFFERSON COUNTY BASIC PI County Ave. PI 48.3 County Ave. Ratio .69 31.3 22.8 5.6 18.8 0 y50% 5.0 y -•40% 4.0- - --30% 3.0- - ••20% 2.0- - • - 10% 1.0- - JEFFERSON COUNTY HIGH PI County Ave. PI 94.8 County Ave. Ratio .81 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GEI45 JERSEY COUNTY BASIC PI County Ave. PI 64.1 County Ave. Ratio .91 JERSEY COUNTY HIGH PI County Ave. PI 106.3 County Ave. Ratio .91 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 II5-I3O 130-145 GE 145 JO DAVIESS COUNTY BASIC PI 50 County Ave. PI 53.9 County Ave. Ratio .77 JO DAVIESS COUNTY HIGH PI County Ave. PI 92.2 County Ave. Ratio .79 6.4 - - 50% - - 40% - - 30% - - 20% -- 10% LT 40 40-50 50-60 60-70 70-80 80-90 GE90 LT70 70-85 85-100100-115 115-130 130-145 GE 145 JOHNSON COUNTY BASIC PI County Ave. PI 40.2 County Ave. Ratio .57 JOHNSON COUNTY HIGH PI County Ave. PI 76.5 County Ave. Ratio .65 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 Figure 7 (continued). 23 5.0 - - 4.0- • 3.0 -• 2.0-- 1.0- • KANE COUNTY BASIC PI County Ave. PI 82.7 51.5 % g County Ave. Ratio 1.18 KANE COUNTY HIGH PI County Ave. PI 131.8 County Ave Ratio 1.13 2.3 • •HK^^BM 7.2 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 6EI45 KANKAKEE COUNTY BASIC PI County Ave. PI 75.2 County Ave. Ratio 1.07 KANKAKEE COUNTY HIGH PI County Ave. PI 119.8 County Ave. Ratio 1.03 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 KENDALL COUNTY BASIC PI County Ave. PI County Ave. Ratio KENDALL COUNTY HIGH PI County Ave. PI 133.2 County Ave. Ratio 1.14 T-50% LT 40 40-50 50-60 60-70 70-80 80-90 GE90 LT 70 70-85 85-100 100-115 115-130 130-145 GE 145 5.0- • 4.0- • 3.0 -- 2.0- • 1.0- • KNOX COUNTY BASIC PI County Ave. PI 74.8 County Ave. Ratio 1.07 . KNOX COUNTY HIGH PI County Ave. PI 123.2 County Ave. Ratio 1.05 10.3 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 II5-I3O 130-145 GE 145 24 Figure 7 (continued). LAKE COUNTY BASIC PI County Ave. PI 70.0 County Ave. Ratio 1.00 LAKE COUNTY HIGH PI County Ave. PI 116.5 County Ave. Ratio 1.00 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 6E 145 LASALLE COUNTY BASIC PI County Ave. PI 83.6 County Ave. Ratio 1.19 LASALLE COUNTY HIGH PI County Ave. PI 134.0 County Ave. Ratio 1.15 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 LAWRENCE COUNTY BASIC PI County Ave. PI County Ave. Ratio LAWRENCE COUNTY HIGH PI County Ave. PI 107.7 County Ave. Ratio .92 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 LEE COUNTY BASIC PI County Ave. PI County Ave. Ratio LEE COUNTY HIGH PI County Ave. PI 130.6 County Ave. Ratio 1.12 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 Figure 7 (continued). 25 LIVINGSTON COUNTY BASIC PI County Ave. PI 82.3 County Ave. Ratio 1.17 LIVINGSTON COUNTY HIGH PI County Ave. PI 131.8 County Ave. Ratio 1.13 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GEI45 5.0- - 4.0 - - 3.0-- 2.0- - I.O-- .4 LOGAN COUNTY BASIC PI County Ave. PI 91.4 7*UI T50o/0 5.0-,- County Ave. Ratio 1.30 LOGAN COUNTY HIGH PI 3.2 8.4 1.2 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 County Ave. PI 142.6 64--8 County Ave. Ratio 1.22 .6 1.0 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 MCDONOUGH COUNTY BASIC PI County Ave. PI County Ave. Ratio MCDONOUGH COUNTY HIGH PI County Ave. PI 137.6 County Ave. Ratio 1.18 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 MCHENRY COUNTY BASIC PI County Ave. PI County Ave. Ratio MCHENRY COUNTY HIGH PI County Ave. PI 120.4 County Ave. Ratio 1.03 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 26 Figure 7 (continued). MCLEAN COUNTY BASIC PI County Ave. PI 91.2 County Ave. Ratio 1.30 MCLEAN COUNTY HIGH PI County Ave. PI 143.3 6 County Ave. Ratio 1.22 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GEI45 MACON COUNTY BASIC PI County Ave. PI County Ave. Ratio MACON COUNTY HIGH PI County Ave. PI 146.0 County Ave. Ratio 1.25 5.0- • 4.0 - • 3.0-- 2.0 1.0 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 MACOUPIN COUNTY BASIC PI County Ave. PI 71.0 County Ave. Ratio 1.01 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 MACOUPIN COUNTY HIGH PI County Ave. PI 116.7 County Ave. Ratio 1.00 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100100-115 115-130 130-145 GE 145 MADISON COUNTY BASIC PI County Ave. PI 67.3 County Ave. Ratio .96 MADISON COUNTY HIGH PI County Ave. PI 111.9 County Ave. Ratio .96 LT 40 40-50 50-60 60-70 70-80 80-9O GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 Figure 7 (continued). 27 MARION COUNTY BASIC PI County Ave. PI 51.7 County Ave. Ratio .74 MARION COUNTY HIGH PI County Ave. PI County Ave. Ratio 98.8 .85 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GEI45 MARSHALL COUNTY BASIC PI County Ave. PI 76.9 4fi 50% 50 County Ave. Ratio 1.10 MARSHALL COUNTY HIGH PI County Ave. PI 125.1 County Ave. Ratio 1.07 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 5.0- 4.0- 3.0- Z.O- 1.0- MASON COUNTY BASIC PI County Ave. PI 64.8 County Ave. Ratio .92 MASON COUNTY HIGH PI County Ave. PI 103.9 County Ave. Ratio .89 13.5 LT 40 40-50 50-60 60-70 70-80 80-90 GE90 LT 70 70-85 85-100 100-115 115-130 130-145 GE 145 5.0 4.0 3.0 2.0 1.0 MASSAC COUNTY BASIC PI County Ave. PI 55.2 County Ave. Ratio .79 MASSAC COUNTY HIGH PI County Ave. PI 101.6 County Ave. Ratio .87 T-50% LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 28 Figure 7 (continued). MENARD COUNTY BASIC PI County Ave. PI 80.3 54^8 MENARD COUNTY HIGH PI County Ave. PI 128.0 County Ave. Ratio 1.10 - - 50% 37 4 --40% County Ave. Ratio 1.14 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GEI45 MERCER COUNTY BASIC PI County Ave. PI 77.3 , , 8 T50% 5 0-p County Ave. Ratio 1.10 , MERCER COUNTY HIGH PI County Ave. PI 125.8 County Ave. Ratio 1.08 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 MONROE COUNTY BASIC PI County Ave. PI 58.9 County Ave. Ratio .84 MONROE COUNTY HIGH PI County Ave. PI 102.0 County Ave. Ratio .87 35.7 24.9 LT 40 40-50 50-60 60-70 70-80 80-90 GE90 LT70 70-85 85-100100-115 115-130 130-145 GE 145 MONTGOMERY COUNTY BASIC PI 50 County Ave. PI 67.4 County Ave. Ratio .96 4.0 -• 3.0- • 2.0- • 1.0- • MONTGOMERY COUNTY HIGH PI County Ave. PI 112.9 County Ave. Ratio .97 15.7 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 Figure 7 (continued). 29 MORGAN COUNTY BASIC PI County Ave. PI 76.8 50.1 50% 5Q County Ave. Ratio 1.09 MORGAN COUNTY HIGH PI County Ave. PI 123.7 -r-50% County Ave. Ratio 1.06 47 7 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GEI45 MOULTRIE COUNTY BASIC PI County Ave. PI 92.7 County Ave. Ratio 1.32 MOULT R IF. COUNTY HIGH PI County Ave. PI 146.0 75.7 County Ave. Ratio 1.25 -- 10% I.O-- .6 3.9 .4 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 5.0- • 4.0 • • 3.0-- 2.0- • 1.0- - 5.7 OGLE COUNTY BASIC PI County Ave. PI 78.2 SO.O County Ave. Ratio 1.11 440% 4.0- - -•30% 3.0- - -•20% 2.0- - 12.7 9-° 11.8 OGLE COUNTY HIGH PI County Ave. PI 125.5 County Ave. Ratio 1.08 -•10% I.O-- 5.2 4.0 ^J- LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT 70 70-85 85-100 100-115 115-130 130-145 GE 145 PF.ORIA COUNTY BASIC PI County Ave. PI 68.8 County Ave. Ratio .98 PEORIA COUNTY HIGH PI County Ave. PI 112.9 County Ave. Ratio .97 LT 40 40-50 50-60 60-70 70-80 80-9O GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 30 Figure 7 (continued). PERRY COUNTY BASIC PI County Ave. PI 50.6 County Ave. Ratio .72 PERRY COUNTY HIGH PI County Ave. PI 99.1 County Ave. Ratio .85 37.6 33.1 - - 10% i.o- - ; LT40 40-50 50-60 60-70 70-80 80-90 GE 90 ~ LT70 70-85 85-100 100-115 115-130 130-145 GEI45 5.0 •• 4.0- • 3.0 - • 2.0 -• I.O-- PI ATT COUNTY BASIC PI County Ave. PI 93.4 81«7 County Ave. Ratio 1.33 PIATT COUNTY HIGH PI County Ave. PI 145.4 75--7 County Ave. Ratio 1.24 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 PIKE COUNTY BASIC PI County Ave. PI 68.5 County Ave. Ratio .98 PIKE COUNTY HIGH PI County Ave. PI 112.8 County Ave. Ratio .97 LT 40 4O-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100100-115 115-130 130-145 GE 145 59.6 POPE COUNTY BASIC PI County Ave. PI 42.9 County Ave. Ratio .61 POPE COUNTY HIGH PI County Ave. PI 80.7 County Ave. Ratio .69 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 Figure 7 (continued). 31 PULASKI COUNTY BASIC PI County Ave. PI 56.9 County Ave. Ratio .81 PULASKI COUNTY HIGH PI County Ave. PI 102.4 County Ave. Ratio .88 LT 40 40-50 50-60 60-70 70-80 80-90 6E 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 PUTNAM COUNTY BASIC PI County Ave. PI 76.4 4,JL4 T50% S.O-p County Ave. Ratio 1.09 PUTNAM COUNTY HIGH PI County Ave. PI 122.6 County Ave. Ratio 1.05 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 RANDOLPH COUNTY BASIC PI County Ave. PI County Ave. Ratio RANDOLPH COUNTY HIGH PI County Ave. PI 101.1 County Ave. Ratio .87 LT 40 40-50 50-60 60-70 70-80 80-90 GE90 RICHLAND COUNTY BASIC PI County Ave. PI 53.9 County Ave. Ratio .77 LT70 70-85 85-100100-115 115-130 130-145 GE 145 RICHLAND COUNTY HIGH PI County Ave. PI 103.5 County Ave. Ratio .89 -r 50% LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 32 Figure 7 (continued). ROCK ISLAND COUNTY BASIC PI County Ave. PI 71.5 County Ave. Ratio 1.02 ROCK ISLAND COUNTY HIGH PI County Ave. PI 116.7 County Ave. Ratio 1.00 • - 10% 1.0- - LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 ~ LT70 70-85 85-100 100-115 115-130 I3O-I45 GEI45 ST. CLAIR COUNTY BASIC PI County Ave. PI 63.7 County Ave. Ratio .91 ST. CLAIR COUNTY HIGH PI County Ave. PI 109.7 County Ave. Ratio .94 LT 40 40-50 50-60 60-70 70-80 80-90 6E 90 LT7C 70-85 85-100 100-115 115-130 130-145 6E 145 SALINE COUNTY BASIC PI County Ave. PI County Ave. Ratio 56.8 .81 SALINE COUNTY HIGH PI County Ave. PI 103.7 County Ave. Ratio .89 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100100-115 115-130 130-145 GE 145 SANGAMON COUNTY BASIC PI County Ave. PI County Ave. Ratio 74.0 SANGAMON COUNTY HIGH PI County Ave. PI 137.2 County Ave. Ratio 1.17 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 Figure 7 (continued). 33 SCHUYLER COUNTY BASIC PI County Ave. PI 63.0 County Ave. Ratio .90 SCHUYLER COUNTY HIGH PI County Ave. PI 104.7 County Ave. Ratio .90 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 SCOTT COUNTY BASIC PI County Ave. PI 70.5 County Ave. Ratio 1.00 SCOTT COUNTY HIGH PI County Ave. PI 113.6 County Ave. Ratio .97 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 SHELBY COUNTY BASIC PI County Ave. PI 69.9 County Ave. Ratio 1.00 SHELBY COUNTY HIGH PI County Ave. PI 119.8 County Ave. Ratio 1.03 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 II5-I3O 130-145 GE 145 5.0- • 4.0 - • 3.0 -• 2.0- • 1.0- • STARK COUNTY BASIC PI County Ave. PI 82.4 S4..3 50o/o 50 County Ave. Ratio 1.17 5.5 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 STARK COUNTY HIGH PI County Ave. PI 133.5 5(!U!,-r50% County Ave. Ratio 1.14 i i - - 40% LT70 70-85 85-100 100-115 115-130 130-145 GE 145 34 Figure 7 (continued). STEPHENSON COUNTY BASIC PI County Ave. PI County Ave. Ratio STEPHENSON COUNTY HIGH PI County Ave. PI 117.5 County Ave. Ratio 1.01 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GEI45 TAZEWELL COUNTY BASIC PI County Ave. PI County Ave. Ratio 53.7 TAZEWELL COUNTY HIGH PI County Ave. PI 128.4 County Ave. Ratio 1.10 45.0 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 UNION COUNTY BASIC PI County Ave. PI 54.6 County Ave. Ratio .78 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 UNION COUNTY HIGH PI County Ave. PI 98.0 County Ave. Ratio .84 LT 40 40-50 50-60 60-70 70-80 80-90 GE90 LT70 70-85 85-100100-115 115-130 130-145 GE 145 VERMILION COUNTY BASIC PI County Ave. PI County Ave. Ratio VERMILION COUNTY HIGH PI County Ave. PI 131.1 County Ave. Ratio 1.12 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 Figure 7 (continued). 35 WABASH COUNTY BASIC PI County Ave. PI 68.0 County Ave. Ratio .97 WABASH COUNTY HIGH PI County Ave. PI 11S.1 County Ave. Ratio .99 LT 40 40-50 50-60 60-70 70-80 8O-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GEI45 WARREN COUNTY BASIC PI County Ave. PI 86.0 6 County Ave. Ratio 1.23 WARREN COUNTY HIGH PI County Ave. PI 138.1 County Ave. Ratio 1.18 LT 40 40-5O 50-6O 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 WASHINGTON COUNTY BASIC PI County Ave. PI County Ave. Ratio WASHINGTON COUNTY HIGH PI County Ave. PI County Ave. Ratio LT 40 4O-50 50-6O 60-70 70-80 80-90 GE90 WAYNE COUNTY BASIC PI County Ave. PI 54.4 County Ave. Ratio .77 LT 70 70-85 85-100 100-115 115-130 130-145 GE 145 WAYNE COUNTY HIGH PI County Ave. PI 102.6 County Ave. Ratio .88 LT 40 40-5O 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 II5-I3O 130-145 GE 145 36 Figure 7 (continued). WHITE COUNTY BASIC PI County Ave. PI 60. 7 County Ave. Ratio .86 WHITE COUNTY HIGH PI County Ave. PI 105.2 County Ave. Ratio .90 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GEI45 5.0 - - 4.0 -- 3.0-- 2.0-- I.O-- WHITESIDE COUNTY BASIC PI County Ave. PI 75.7 County Ave. Ratio 1.08 WHITESIDE COUNTY HIGH PI County Ave. PI 121.2 County Ave. Ratio 1.04 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 WILL COUNTY BASIC PI County Ave. PI 71.3 County Ave. Ratio 1.02 WILL COUNTY HIGH PI County Ave. PI 117.4 County Ave. Ratio 1.01 LT 40 40-50 50-60 60-70 70-80 80-90 GE90 LT70 70-85 85-100100-115 115-130 130-145 GE 145 WILLIAMSON COUNTY BASIC PI County Ave. PI 45.9 County Ave. Ratio .65 WILLIAMSON COUNTY HIGH PI County Ave. PI County Ave. Ratio LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 37 Figure 7 (concluded). WINNEBAGO COUNTY BASIC PI County Ave. PI 75.2 County Ave. Ratio 1.07 WINNEBAGO COUNTY HIGH PI County Ave. PI 119.8 County Ave. Ratio 1.02 LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GEI45 WOODFORD COUNTY BASIC PI County Ave. PI 81.8 County Ave. Ratio 1.17 60 ,0 WOODFORD COUNTY HIGH PI County Ave. PI 131.3 49.8 ,. , County Ave. Ratio 1.12 ' 4-40% LT 40 40-50 50-60 60-70 70-80 80-90 GE 90 LT70 70-85 85-100 100-115 115-130 130-145 GE 145 STATE SOIL ASSOCIATION PATTERNS OF PRODUCTIVITY Basic and high management soil productivity char- acteristics of the major Illinois soil associations were de- veloped (Tables 3 and 4). These data give a broad in- sight into soil productivity distribution characteristics for every soil association of the state by indicating the aver- age percentage of soils in each of seven PI categories for basic and high management. It is not our intent to dis- cuss these PI categories for each soil association area; rather, examples of prairie, forested, and alluvial soil will be examined. It may be noted, however, that soil asso- ciation B is the most productive soil association: 95.3 percent of the area designated as B has a high manage- ment PI of 115 or greater. Soil association R is the least productive: 84.7 percent of the area designated as R has a high management PI of 100 or less. PRAIRIE SOIL ASSOCIATIONS Soil association area A (Fig. 1) has soils that devel- oped under prairie vegetation on thick to moderately thick (1.5 meters or more) Wisconsin-age loess that over- lies gently rolling topography. The dark colored, mod- erately permeable soils are fertile and suffer from few problems. The most productive areas are in northwestern Illinois on flat interstream divides. Very high soil Pi's are characteristic of this soil association. The combined PI average of all soils this soil association comprises fre- quently can be used to approximate the soil productivity of almost all land in association A. Variation in Pi's be- tween the nearly level major soil series within soil asso- ciation A is only about 10 units. (Average high and basic management Pi's for these individual soil series vary from 150 to 160 and from 95 to 100, respectively; the overall average high and basic management Pi's for the association are 139 and 87, respectively.) Larger PI vari- ations occur for less commonly distributed soil series and for more sloping phases within a given soil series. It is possible, therefore, to estimate Pi's for different areas within a soil association even though PI variations exist within an individual soil series or among the various soil series that are a part of the association. Soil association B is similar to soil association A in many respects. Soil association B contains soils that de- veloped under prairie vegetation on thin to moderately thick (0.5 to 1.5 meters) loess over calcareous loam till. 38 The general properties and productivity of soil series in soil association B are similar to those of soil association A. Major soil series that make up association B have high and basic management Pi's between 145 and 160 and between 90 and 100, respectively. Soil series that have minor geographical distribution or occur on sloping land have Pi's that are not typical of the major soils in asso- ciation B. The overall high and basic management PI averages for soil association B are 147 and 91, respec- tively (Tables 3 and 4) ; hence, soil association B is somewhat better than association A. The pattern of PI distribution within soil associations A and B is similar: a large majority of the soils of both are in high management PI categories of >130 (74 per- cent of association A and 90 percent of association B), while few of the soils have Pi's of <85 (4 percent of association A and 1 percent of association B). The inter- mediate PI categories (85 to 130) occur at low fre- quencies because of the dominance of the two highest PI categories; approximately 22 percent of association A soils and 8 percent of association B soils are in the inter- mediate productivity categories. Both associations are characterized by a large concentration of productive soils. Other prairie associations are relatively uniform (compared to forested and alluvial soil associations) but have more variation in Pi's between fields than do asso- ciations A and B. FOREST SOIL ASSOCIATIONS Soil association area L comprises soil series that de- veloped under broadleaf deciduous forest on thick (1.5 meters or more) Wisconsin-age loess. Soil series within this association have greater variation in PI than soil series of prairie associations because large variations in slope and loess thickness are common. Average high and basic management Pi's of major soils in this association range from 70 to .140 and from 40 to 90, respectively. The overall high and basic management PI averages for association L are 100 and 59, respectively; thus, the aver- age quality of a soil in association L is low compared to soils in associations A and B. The distribution pattern of Pi's within this association is rather uniform. For example, 28 percent of the soil association area has a high management PI average of <85, 20 percent has a high management PI average of >130, and more than half has soils in the intermediate PI categories (85 to 130). It is evident from this fre- quency distribution pattern that soils of any productivity level could dominate a given local area within soil asso- ciation L. Large variations in Pi's make it necessary to use procedures that allow differentiation between better and poorer soils in specific soil association areas. Other forested associations have similar wide variations in PI. ALLUVIAL SOIL ASSOCIATION Soils in soil association Z are related to the nature of the alluvial parent material on which they formed. The association is made up of bottomland and terrace de- posits along streams and rivers. The variable nature of the alluvial deposit results in large variations in PI be- tween soil series. High and basic management Pi's for the major soil series range from 100 to 145 and from 60 to 95, respec- tively. Most of these soil series have Pi's in the higher categories, with the result that the overall high and basic management average Pi's are 121 and 76, respectively. The soil productivity for the total association is above the state average; however, the combination of highly productive soil series with some soil series of lower pro- ductivity results in a productivity average less than those of soils in most prairie associations. The distribution of high management Pi's is as fol- lows (Table 4) : 3 percent of the soils in association Z have low Pi's (<85), 57 percent have intermediate Pi's (85 to 130), and 40 percent have high Pi's (>130). Variations in Pi's that are associated primarily with the texture of alluvial deposits make it difficult to generalize Pi's over wide areas. COUNTY SOIL ASSOCIATION PATTERNS OF PRODUCTIVITY The state average areal distribution of soils within each of the seven PI categories in individual soil associations is given in Tables 3 and 4. These data can be used to help estimate soil PI in an association area. However, possible soil Pi's of a given association in a particular county may be atypical and not closely related to the state average. Patterns of high management PI of soil associations for individual counties (Table 5) were developed in order to estimate more accurately the approximate soil productivity of a soil area within a specific county. Inter- county comparisons of soil association PI patterns are indicated by means of ratios that compare individual county soil association PI distribution characteristics with comparable state soil association data. Hancock County soil PI category >145 in soil asso- ciation L has a county/state ratio of 0.83. This ratio means the county percentage of soils in PI category > 145 is 83 percent as much as the state average for that category and association. Thus, whereas 8.3 percent of the state's soils in association L have a PI of >145, only 6.9 (0.83x8.3) percent of Hancock County soils in association L are rated that productive. This kind of information should be useful for evaluating soils within 39 Table 5. — Percenfage Distribution of Soils in Various Productivity Index Classes (or Soil Association Areas Within Counties (Ratios of County to State Percentage Distribution Are in Parentheses) Soil Percent Association of County Area County Productivity index classes - high levels of management < 70 70-85 85-100 100-115 115-130 130-145 > 145 ADAMS 1 ] 1 1 ALEXANDER ( \ : BOND BOONE BROWN BUREAU : i CALHOUN ] CARROLL i 1 1 CASS : : CHAMPAIGN 1 : i i CHRISTIAN i 1 1 CLARK 1 ( 1 1 CLAY CLINTON I 15.2 > 9.3 L 15.0 1 54.2 ! 6.3 > 24.9 1 20.2 ! 54.9 28.5 36.3 20.6 14.7 27.3 49.4 23.3 8.2 3.6 22.6 57.5 8.2 48.0 1.1 8.6 17.7 21.2 C 2.9 ! .4 L 81.7 '. 18.3 \. 47.3 L 37.6 i 2.7 1.9 8.3 2.3 25.4 15.7 11.0 14.2 C 23.2 ! 10.6 ) 55.8 r 8.6 C 4.9 1 7.0 J 23.7 I 31.6 > 48.4 I 3.7 1 16.3 1 7.3 r 16.6 } 2.4 J 12.9 P 23.3 I 30.3 » 2.3 I 4.8 r 63.7 Q 33.8 Z 2.5 D 5.0 E 15.8 F 26.4 P 23.5 Q 22.3 11.8(6.94) 10.4(3.35) 18. 1( .93) 47.6(1.86) 10.4(5.47) 2.2( .61) .6( .07) 2.8( .44) .9( .47) 1.4( .36) 1.2( .63) 5.3(2.79) 6.2( .52) 12.4(1.33) .5( .06) 7.7( .48) 23.1(1.04) .3( .16) •4( .21) 2.2( .27) 1.8( .29) 17.3(9.11) •7( .37) 3.3(1.43) 2.5( .48) .2( .02) 14. 9( .84) 14. 0( .89) 17. 5( .71) 27. 4( .93) 60.8(4.22) 32.0(1.31) 45.2(2.26) 10.4(1.06) 25.1(1.39) 14. 4( .35) .4( .09) 47.5(1.39) 37.3(2.59) 15.1(2.90) 12.5(1.39) 23.4(1.31) 19.1(1.21) 11. 4( .47) 4.4( .85) 2.6( .55) 10. 7( .60) 7.2( .50) 12. 2( .40) 16.5(1 2.5( 33.1(1 22. 4( 3.9( 17. 7( 9.K 34.1(1 29. 9( 51. 4( 29.3(1 23.8(1 13.8(1 3.6( 8.5( 14. 4( 14.5(1 38.2(1 28.3(1 14. 2( 15.2(1 15.5(3 12.4(1 38.9(1 5.2( 21.8(2 2.2( 6.3( 5.4( 23.0(1 22.7(1 9.4( 44.4(2 40.0(1 15.4(1 29.1(1 37.7(1 10. 7( 3.2( 10.0( 6.2(1 11. 2( 38. 4( 28.2(1 5.6( 5.2( 10. 0( 53.6(1 27. 1( 82.0(1 75.1(1 62.7(3 31.0(1 39.2(1 21. 6( 35.3(2 8.7( 74.0(1 26.0(1 70.5(2 51.3(1 53. 2( 43.4(1 16. 4( 11 .Sf .12) •23) .53) .82) .16) .60) .60) .40) .68) .74) .26) .03) • 33) .32) .56) .98) .33) .76) .03) .58) .03) .16) .19) .79) .34) .32) .09) .29) .22) .56) .05) .62) .08) .64) .05) .34) .38) .70) .34) •41) .27) .36) .75) .00) .37) .35) .92) .23) .99) .88) .08) .35) .05) .68) .94) .32) .36) .07) .13) .89) .17) .77) .86) .71) .i7^ 36.0(3.00) 84.6(1.29) 24.1(2.10) 6.2( .63) 60.8(1.92) 1.5( .24) 10. 8( .34) 6.5( .60) 2.0( .69) 1.0( .45) 4.9(8.17) 58.4(1.71) 4.7( .57) 20. 2( .80) 48.9(4.08) 56. 5( .86) 1.5( .13) 5.9( .60) 47.3(1.50) 13.4(1.12) 14.7(1.43) 36.3(1.06) 11.8(1.03) 35.7(1.41) 51.0(3.38) 84.4(2.67) 6.5( .57) 57.6(1.82) 19.9(1.66) 6.1( .53) 10. 7( .42) 6.6( .93) 39.2(1.24) 18.2(1.52) 5.9( .51) .4( .04) 9.6( .38) 4.9( .32) 7.6( .24) 10.7(1.04) 33.3(1.02) 22.7(1.45) 34.0(1.55) 11. 0( .43) 26.8(2.23) 77.7(1.18) 6.2( .57) 26.8(2.71) 7.5( .69) 6.7(2.31) 9.5(1.53) 5.7(2.59) 1.0(1.67) 28.8(1.14) 22. 8( .72) 1.2( .41) .6(1.00) 29. 5( .93) 42. 3( .64) 3.1( .29) 5.3(1.83) 4.6(2.09) 5.6(9.33) 31. 1( .73} 19 4 5 13 ,6( .32) •9( .59) .8( .55) .6(1.66) 4.2( .32) 1.3( .29) 3.3( .42) 8.8( .50) 28.4(4.44) 14.8(1.90) 7.8(1.00) 16.4(4.43) 10. 7( .39) 5.3(1.20) 1.8( .53) .3( .04) 1.2( .19) 27.2(2.06) 8.8(1.96) 1.2( .52) 43.1(3.53) •5( .23) 2.9(1.93) 3.8( .90) 4.3(1.02) 22.8(1.30) 17.1(1.25) .4( .17) .7( .32) 5.7(3.35) 16.5(5.32) 7.1( .37) 33.5(1.31) 3.3(2.20) 1.2( .71) - 3 10 26 25 20 31 15 2 6 63 69 36 13 44 5 .6( .35) .1(4.43) .6(2. 941 .8(24.36) .5( .60) .4(1.39) .8( .92) •5( .25) .2( .02) •7( .25) .6( .80) .9(1.03) .8( .87) .5( .80) .8(1.66) .7(1.29) .4(1.17) 2.8(3.50) 19. 2( .99) 3.3(1.50) .!( .08) 4.6( .57) .8( .42) 5.1( .50) 6.8( .84) 4.3(2.26) .8( .42) 22.8(2.81) 24.2(12.74) 15.1(1.47) 12.0(1.02) 7.9(4.16) 16.8(2.07) 5.7( .90) •9( .47) 7.1( .69) .!( .13) 5.4( .63) .5( .14) 1.8( .15) 4.4( .70) 3.6( .39) 1.9( .30) 4.4(1.13) 2.1( .27) 6.1( .38) .3( .16) 6.1( .66) 8.3( .52) 54.5(15.14) 19.4(1.63) 33.4(3.59) 4.9( .62) 17.2(1.08) 9.2(2.71) ,9( .07) 3.1( .48) 4.5C .29) 32.6(2.47) 10.3(1.32) 2.1( .91) 16.8(1.27) 30.9(4.83) 42.5(2.74) 10. 5( .81) .8( .10) 1.6( .70) 6.1( .46) 9.0(2.00) 3.5( .55) 7.8( .50) .4( .05) .7( .58) .3( .05) 12.3(1.02) 1.4( .39) 1.2< .52) 1.6( .76) 20.1(2.58) 2.0( .44) 3.0( .81) 7.5( .43) 3.3( .12) 5.9(1.34) •7( .11) .3( .04) 2.4( .65) 9.8(2.23) 13.3(8.87) 24.4(1.26) 4.0(2.67) .9( .53) 3.5( .18) 22.4(1.26) 13. 1( .53) 5.0( .96) 18.0(1.01) 24.8(1.72) 1.9( .06) 8.1( .57) 4.8( .20) 2.6( .50) 5.2( .29) 6.8( .43) 9.8( .68) 27. 7( .91) 72.0(2.94) 1.1( .50) 2.1( .43) 1.1( .08) 7.3( .69) 3.7( .71) 2.7( .30) 18. 3( .92) 18.7(1.18) 5.9( .30) 11.4(1.16) 35. 4( .91) 32.5(1.10) 33.0(1.83) 46.4(1.12) 5.2( .36) 34.3(1.40) 13.8(1.41) 36. 8( .89) 1.0( .11) 3.2( .16) 2.8( .29) 21.0(1.17) 54.7(1.32) A< Lit kT\ 1 5 48 10 30 1 15 51 4 3 51 4 10 80 52 25 19 83 63 4 10 2 .!( .13) .3( .65) .4( .78) .2(1.23) .2(6.57) .8( .17) .2(1.85) .6( .83) .9( .59) •3( .31) .3(1.48) .0( .87) .1(1.23) .9(1.01) .1(2.24) .5(4.90) .2( .96) .4(2.41) .0(1.01) .5( .80) .8(1.02) .7(1.59) 10. 4( .71) 16. 6( .74) 2.6(1.53) 32.0(1.65) 37.0(1.45) 14.2(6.45) 45.1(3.09) .3( .50) 1.0(3.33) 4.5( .62) .!( .06) 3.0( .97) 10. 2 ( .40) 1.9( .45) .2( .05) 15.1(1.24) 16. 5( .94) 16.7(1.22) .3( .20) 2.3( .55) 18.2(1.33) 2.2( .71) 7.1(1.69) 4.4(1.05) 4.4( .25) 4.7( .34) - 2 30 33 .!( .03) .4(2.18) .!( .87) .3(4.06) .2( .29) .4( .36) .2( .12) 15.6(2.00) 1.0( .27) 16. 8( .61) 1.4( .32) 5.0(1.39) 40 Table 5. — Continued County Soil Percent Association of Area County Productivity index classes - high levels of management > 70 70-85 85-100 100-115 115-130 130-145 < 145 COLES B 49.9 47 Ort 1 /9 C "1\ •4( .33) 1.8( .82) W7 / 7A\ 1.0( .20) TO A / Qf\\ 8.8( .85) 88.0(1.10) H * / 40.8 12.3(1.68) JV*1\2 « Jj) 7.6( .88) 4.9(1.36) • ' \ • '**) 10. 2( .96) JV.'H ,y\J) 33.3(1.19) 13. 1(1 . 21) 11. 7( .53) 2.6(1 .53) 19.9(1.00) W 2.3 .7( .32) -.- ... 7.9(1.23) 3.3( .23) 28.5(1.88) 21. 9( .87) 37.7(1.09) Z 2.3 5Q 19.1(12.73) 7.6(4.00) 61 f f. 1 n\ c^ 0/7 Q7^ 2.5( .10) 27 / ->; ,8( .06) it *i\ *OI ) 56.6(1.10) ,o( **•!) 7.3( .46) .!( .18) .5( .10) V 28.5 r\n e 1.2( .43) 18.2(1.03) 49 ft 91 ^ 29.8(1.45) 4n f di\ 11. 0( .89) 4c / -51 \ 21. 0( .93) IE n/ QON 17. 5( .95) e/ 9/*) 1A\ 1.2( .21) IB f\t ^9^ u X 22*3 14.2 *2\Z«ZAJ tU( .oJj 4.1( .26) .3( .31) 5.2( .17) ID.LH ryj) 5.0( .53) 34*2(2 .14} 82.3(5.45) lo.U(. »92J 3.3( .72) CRAWFORD F 24.2 27 .6( .14) 2.1( .23) 2.1( .57) n*) Qfi ^7^ G 0 • / 19.3 3.3( .27) 6.8(1.74) t £\L , 5 1 ) 5.0( .28) J J * 7 ^ 1 • *W ) 27. 3( .93) 42.4(1.44) J (. * 7 \J ,U/ ) 15.2(2.45) ... p 13.1 7.5( .43) 10.2(1.29) 23. 9( .86) 24.1(1.34) 30.5(1.31) 3.8(1.73) — — Q 30.7 13.9(1.01) 7.1( .44) 4.9(1.11) 55.2(1.34) 18. 4( .80) .5( .83) — Z 10.0 •5( .33) .9( .47) 7.0( .90) 29.5(1.20) 21. 8( .89) 40.3(1.28) CUMBERLAND E 27.8 .9( .21) 2.2( .18) .6( .08) 4.0( .20) 68.5(1.57) 21.8(2.02) 2.0(1.18) F 25.3 5.3(1.25) 4.7( .51) .8( .22) 8.5( .87) 75.7(1.09) 4.4(1.52) •4( .57) G 1.7 25.8(4.23) 5.8( .91) .6( .07) 21. 3( .55) 6.5( .35) 3.9( .36) 36.1(3.22) M 6.9 4.1( .56) — - 10.3(2.86) 1.3( .12) 63.2(2.25) 16. 2( .74) 4.9( .25) P 1.7 25.2(1.44) ... ... — . ... 26.5(1.47) 33.5(1.44) 1.9( .86) 12.9(3.58) Q 24.6 26.1(1.91) 7.5( .47) .4( .09) 35. 8( .87) 29.7(1.29) — .6( .55) w 1.7 — - ... ... ... ... — . 42.5(1.68) 57.5(1.66) z 10.3 •4( .27) •7( .37) 9.4(1.21) .!( .00) 16. 3( .67) 23. 6( .75) 49.5(6.04) DE KALB B 26.5 •1( .17) •5( .42) .3( .14) 6.2(1.27) 12.4(1.20) 80.4(1.00) I 34.6 .4( .50) — 1.6( .47) 2.5( .53) 11.9(1.14) 31. 8( .93) 51.8(1.14) U 2.0 7H O .6( .14) •5 / ni\ 145 GALUTIN GREENE GRUNDY HAMILTON HANCOCK HARDIN HENDERSON HENRY IROQUOIS JACKSON JASPER JEFFERSON JERSEY JO DAVIESS JOHNSON 0 P Q W X z A D L N W Z G J K W X Y Q R W A D L N 0 P R A L W X z A L W X Z I J K W X 0 P Q W z F Q X z F Q R A D L N Z A B L X Y P R 10.2 10.6 3.8 54.7 7.8 12.9 17.2 2.2 27.3 39.6 2.2 11.6 5.1 41.0 9.1 23.1 11.1 10.5 63.7 19.3 17.0 15.0 36.5 30.6 18.0 16.3 42.0 41.7 33.0 40.0 3.0 18.2 5.8 44.7 11.8 31.5 9.1 2.8 9.2 17.5 25.7 26.5 21.2 12.5 43.2 5.1 28.8 10.5 52.6 38.3 2.3 6.7 22.2 75.5 2.3 5.6 6.6 43.1 39.4 5.3 4.6 4.2 39.5 4.1 47.7 53.8 39.1 7 1 15.0(1.23) 35.7(2.04) 12. 8( .93) 1.6( .73) .!( .03) 6.8( .86) 8.7( .54) .7( .37) 6.3( .61) 10. 7 ( .61) 19. 5( .70) 3.0( .68) 18.5(2.89) 21.6(1.39) .2( .09) 8.9( .67) 3.8( .84) 31.9(1.08) 10.4( .58) 43.0(1.04) 14.6(1.01) 31.8(1.04) 23.0( .94) 1.5( .29) 17. 2( .97) 13. 4( .85) 27.1(1.88) 33.8(1.38) 17 .0( .44) 4.7( .96) .2( .02) .5( .03) 56.6(1.86) 9.4( .66) 51.1(1.24) 10.6(2.21) 61.9(4.30) 7.6(1.46) .8( .09) 17. 3( .97) 2.7( .17) 26. 6( .90) 3.5( .19) 4.7( .98) 6.3(1.21) 15. 8( .89) 20.7(1.44) 14. 6( .48) 16.2(3.12) 18.2(1.02) 6.4( .44) 19. 1( .63) 37.2(1.26) 23.6(1.01) 32.6(1.42) 42.4(2.79) 19.7(2.10) 1.3( .05) 1.1( .07) 33.3(3.06) 20. 5 ( .94) 30.0(1.09) 11. 6( .76) 21. 3( .87) 50.5(2.70) 9.7( .31) 55.4(1.08) 13. 4( .88) 15.1(1.61) 7.7( .36) 26.5(1.15) 10.5(1.01) 19.3(1.27) 20.1(1.37) 14.9(1.37) 22.6(1.04) 26. 8( .98) 13. 6( .46) 11. 1( .48) 7.4( .71) 13. 8( .94) 13.4( .62) 9.0( .59) 6.3( .67) 8.5( .35) 16.1(1.10) 16. 0( .74) 18.3(1.20) 15.3(1.63) 6.1( .25) 6.4( .62) 27. 6( .88) 50. 7( .99) 11. 3( .74) 11.4(1.21) 7.6( .26) 11. 9( .51) .7( .03) 11. 4( .75) 19. 5( .80) 72.0(1.04) 24.2(1.05) 15.9(1.69) 46.6(1.91) 61. 4( .89) 17. 7( .77) 5.5( .53) 11. 0( .75) 15.3(1.40) 20. 0( .92) 31.6(1.15) 32.5(1.33) 2.9( .20) 18.2(3.71) 23.3(1.07) 5.2( .84) 4.0(1.82) 22. 3( .88) 20.6(1.36) 75.7(2.40) 11. 6( .97) 51. 6( .79) 12.6(1.10) 12.7(1.28) 14. 8( .58) 40.5(1.28) 2.2( .21) 37.6(1.15) 44.4(2.83) 28.7(1.13) 21.4(1.42) 29.2(4.11) 20.9(1.74) 57. 9( .88) 19.3(1.68) 9.5( .96) 6.5(1.05) 1.4( .64) .1(1.00) 7.8( .65) 14.5(1.26) 2.1( .08) 13. 3( .88) 80.7(2.55) 11. 9( .99) 13.8(1.20) 22. 3( .88) 23.3(1.54) 27. 2( .86) 18. 2( .53) 44.5(1.36) 18.9(1.20) 50.2(1.98) 29.9(1.98) 3.3( .53) •2( .12) 13.1(4.23) 28.0(1.44) 24. 3( .95) 2.0( .56) .9( .11) 1.6( .25) 85.5(1.37) 11.9(1.43) 14.1(1.33) 46.5(1.34) 3.3( .40) 9.4( .84) 41.5(1.78) 57.0(1.65) 1.3( .28) 31.0(3.01) 1.1( .14) 3.2( .39) 3.1( .48) .3( .05) 5.6( .36) 1.9( .15) 3.1( .70) 18.4(1.27) 18.7(2.92) .6( .26) 7.5(3.57) 9.4( .71) .!( .33) 17.7(2.77) 3.2(3.20) •2( .11) 5.6( .25) 12. 0( .88) 40.3(1.10) 15.3(1.30) 7.3( .46) 20. 3( .60) 2.7(1.42) 5.2(1.44) .3( .04) .6( .10) 3.4( .87) 6.0( .76) 24. 6( .73) .5( .26) .7( .09) 34.7(3.37) 3.7(1.95) 7.7( .95) 3.0(1.58) 15.1(1.47) 1.4( .82) 9.5(3.06) 24.3(1.25) 36.5(1.43) 25.4(2.08) 39.5(2.26) 42.2(1.16) 5.7(3.35) 24.0(1.24) 46. 7( .75) 4.2( .75) 6.9( .83) 23.9(2.25) 24.5(1.39) 38.5(1.39) 20.9(1.44) 2.8(1.22) 7.7( .58) 63.1(1.01) 23.9(2.88) 68.3(1.97) 7.2(1.57) 10.8(1.32) 45. 6( .73) 26.2(3.16) 32. 8( .95) 14.7(1.01) 9.3( .60) 2.4(1.04) 13.5(1.02) 5.9( .92) 18.9(1.22) 5.4( .69) 5.0(1.47) .8( .13) 11. 1( .92) 2.5( .39) 15.5(1.00) 29.3(1.66) 36.4(1.31) 18.7(4.25) 40.1(6.27) 28.6(3.67) 1.2( .32) 1.3( .30) 36.4(2.35) •7( .09) 9.7(2.62) 7.3(1.66) 4.1(2.41) 4.6( .24) 11.3(5.14) 8.2( .56) .3( .38) .!( .33) .3( .25) .7( .32) 8.3( .57) 14.6(1.20) 19.6(1.12) 7.2( .53) 15.2(6.91) 6.2(4.13) 5.6(1.33) 25.6(1.86) 10. 6( .73) 1.4( .93) 1.4( .33) 12. 1( .88) 44.8(1.23) 61.2(7.46) 59.8(1.32) 23.8(1.02) 4.0( .77) 29. 6( .86) 5.5(1.20) .4( .36) .6( .86) .2( .18) 1.2(1.00) .!( .10) .9( .64) 1.7( .89) 4.5( .44) 9.0(1.91) 3.0( .61) 14.0(1.08) 4.1( .28) 25. 0( .82) 44.8(1.52) 18.5(1.03) 58.4(1.41) 27.1(1.88) 30.5(1.24) 2.6( .27) 37.4( .91) 30.5(1.00) 3.4( .14) 15.7(1.60) 36. 6( .89) .6( .13) 9.7( .87) 6.6( .73) 24.3(1.37) 21.2(1.34) 17. 7( .72) 33.9(6.52) 28.7(13.05) 22.5(1.26) 14. 5( .48) 10. 2( .72) 14. 4( .80) 5.4(1.13) 70.2C2.87'> 13.6(1.72) 15.i( .94) 6.2(3.26) 1.1( .58) 7.9( .85) 7.6( .48) 6.6( .64) .2( .11) 11.8(1.27) 26.3(1.64) 49.1(1.46) 1.3( .36) .!( .01) 2.6(1.37) 2.2(2.75) 6.3( .78) 23.5(2.28) 21.0(1.78) 12.5(1.58) 26. 5( .79) 14. 1( .45) 10.2(3.52) 3.6(6.00) 47.7(1.51) 2.0( .17) 72.8(1.11) 8.1( .70) 17.4(1.76) 41.0(1.30) 9.2( .77) 17.8(1.73) 7.8( .68) 77.2(1.24) 4.1(1.32) 36.5(1.88) 18. 9( .74) 1.0( .67) 15.6(26.00) 17. 0( .88) 11. 6( .79) 33.5(1.50) 31.0(1.77) 48.8(1.37) 10. 0( .76) .3( .07) 30.2(13.13) 17.5(14.58) 19.9(1.51) .6( .04) 18.4(1.42) 33.1(1.19) 9.3( .64) 11.0C1.671 1.1( .13) 10. 5( .99) 7.9( .96) 21. 3( .34) 3.2( .39) 49.8(10.83) 4.4( .43) 9.0( .42) 9.0( .39) 10. 1( .97) 16. 8C .691 3.4( .48) _•• •-• 42 Table 5. — Continued County Soil Association Area Percent of County < 70 Productivity index classes - high levels of management 70-85 85-100 100-115 115-130 130-145 > 145 KANE KANKAKEE KENDALL KNOX LAKE LA SALLE B G I J T D V U I J K w X Y B I J K 0 w A D LAWRENCE LEE LIVINGSTON LOGAN MfcCON MACOUPIN W Y F G 0 P Q W X Z A B I M W X A B C I J K W A B L M N W A B M U A D M P 2.7 1.5 26.8 2.8 2.3 14.3 2.7 46.8 7.4 5.6 15.0 31.6 16.1 5.7 35.7 7.7 21.3 1.9 27.7 52.6 1.8 1.5 44.1 9.4 38.8 7.6 4.2 36.3 3.7 24.9 2.7(3.38) 11.2(4.87) .4( .21) .3( .14) 15.0(1.03) 4.3( .19) 1.3( .68) 5.8(2.64) 3.2(1.88) 28.4(1.46) 18. 7( .73) 4.4( .44) .6( .21) 1.4( .82) 3.6(3.00) 2.5(2.50) 3.0( .14) 7.5( .49) 7.1( .40) 4.3(2.26) 6.7(4.78) •2( .11) 3.6( .35) 2.7( .23) 5.2( .14) .34) .32) 3.6(1.89) 8.2(1.01) 9.6(1.52) 4.8(4.00) 3.4(3.40) .9( .64) 3.9( .35) 21.6(1.23) 2.1 4.2 15.0 6.6 7.3( .38) 7.2(2.57) .4( .18) .3( .03) 8.9( .51) 9.4(4.95) 12.0 2.0( .33) 4.2( .66) 8.3 38.2 15.2 8.2 11.6 2.0( .11) 1.8( .13) .!( .05) .7( .05) 1.0( .67) 13.1(1.66) 25.0(1.56) 3.9(2.05) 5.9( .57) 32.8 6.6 4.1(6.83) 9.0(11.25) 3.5(4.38) 3.9(3.25) 35.1 11.6 1.4( .64) 15.2(1.04) 1.7( .89) 10.4(1.01) 9.3 .4( .67) 1.9(2.37) 29.6 19.2 63.4 1.4(1.17) 1.4( .64) .2( .12) 2.1(1.50) .5( .26) .2( .11) 2.0 2.1 5.7 25.0 2.2 72.5 10.8 4.5( .23) 3.0( .41) 15. 5( .61) .!( .05) 2.8(1.65) .!( .17) 13.3(1.82) 7.1( .88) 4.9( .57) 1.8( .29) .5( .26) 4.2(2.21) .!( .13) 25.0(2.91) 8.6 42.6 20.0 28.8 4.1(2.41) .5( .16) 33.4(1.30) 31.8(1.82) 2.3( .64) 1.0( .13) 3.9(3.25) 11.4(1.39) 5.0(1.47) 8.0(1.25) 8.2(1.17) 6.2(1.48) 7.1( .34) 1.9( .30) 8.8(1.38) 26.3(2.17) 5.3( .83) 10. 5( .68) 11.0( .85) .2( .06) 12.9(2.02) 8.6( .71) 3.2( .50) 1.5( .65) 8.2( .62) 7.3(1.62) 1.0( .29) 17.1(2.67) 25.4(2.10) 22.4(1.09) 22.6(3.53) .2( .09) 2.4(2.00) .5( .12) 16.0(2.50) 9.8( .81) 3.3( .25) 15. 0( .73) 2.6( .41) 34.0(9.19) 8.4(1.02) 9.0( .51) 17. 0( .61) 4.5(1.02) 4.5( .70) 11. 1( .72) 15.0(1.92) 2.5(1.09) 2.3(1.92) 15.6(4.59) 14.9(4.14) 1.9( .30) 7.7( .50) .6( .50) 12.4(2.95) 1.5( .44) *.!( 11. 6( .64) .96) .11) .26) 17.9(1.36) 4.2( .93) .3( .05) 1.5(1.25) 1.0( .28) .9( .39) 1.1( .52) 1.6( .36) 13. 0( .47) 30. 7( .79) 8.3(1.77) 4.3( .88) 7.5( .22) 12.4(1.13) 52.6(4.24) 2.0( .14) 1.0( .21) 3.7( .76) 4.6( .35) 7.4( .51) 43.0(1.41) 5.5( .39) .6( .27) 5.8(1.23) 6.1(1.24) 21.0(1.62) 31.4(2.85) 15.3(1.06) 6.5(1.25) .6( .07) 11. 2( .63) 12. 4( .78) 10.0(2.13) 6.4(1.31) 9.6( .74) .6( .05) 12.7(1.02) 2.6( .18) 1.5( .29) 4.1(1.86) .5( .04) 49.3(2.77) 12.6(1.19) 11. 0( .89) 15.2(1.06) 11. 5( .81) 15.7(1.60) 73.4(1.90) 13. 7( .46) 21.0(1.17) 45.8(1.11) 14.7(1.02) 43.8(1.44) 25.3(1.07) 1.6( .31) 6.8(3.09) 11.6(2.47) 24.7(2.33) 13. 3( .92) 28. 7( .94) 15.3(6.95) 3.6(1.50) 11. 2( 3.2( .33) .86) .22) 3.4( .65) 7.7( .43) 6.1( .58) 20.5(1.30) l.5( .10) 11.3(2.17) .4( .18) 8.8( .83) 10.6(2.04) 4.2( .47) 20.6(1.30) 12. 0( .67) 5.8(1.18) 22.3(2.14) 32.1(1.03) 7.5( .66) 30. 6( .91) 11. 7( .52) 18.8(1.24) 1.3( .13) 41.9(1.34) 34. 2( .67) 17.2(1.13) 5.1( .54) 41.5(1.95) 7.8(1.59) 9.6( .92) 27. 2( .87) 55.7(1.09) 20. 3( .61) 13. 0( .86) 27.6(1.88) 13. 4( 24. 4( .62) .89) 33.6(3.23) 24. 0( .77) 51.7(1.01) 19. 4( .87) 15. 9( .70) 55.5(3.65) 12. 0( .82) 16.0(3.27) 5.3( .56) 24. 6( .79) 48. 8( .95) 8.7( .40) 29.2(1.04) 23.8(1.05) 31.4(2.07) 51.6(2.42) 43. 8( .63) 5.5( .29) 59.6(2.02) 45.2(1.94) 21. 4( .93) 25.6(1.68) 13.7(1.46) 31.2(1.28) 18.1(1.23) 14.3(2.92) 7.7( .74) 17. 2( .61) 3.6( .24) 15.7(1.67) 4.2( .86) 29.7(3.06) 11.8(1.13) 29. 9( .96) 58.7(1.14) 15. 0( .99) 8.4( .57) 8.7(1.78) .6( .03) 13. 4( .48) 30.4(1.11) 11. 6( .76) 38.7(2.63) 2.5( .51) 18. 6( .66) 4.5( .30) 18.2(1.70) 26. 7( .78) 16. 0( .49) 59.0(7.11) 22.4(1.40) 19.5(1.06) 21. 2( .84) 50.0(1.47) 19. 6( .60) 12. 0( .76) 31.0(1.23) 20.9(1.38) 10.3(1.45) 15.2(1.48) 30. 5( .89) 7.0( .21) 5.1( .32) 17.0(1.06) 18. 0( .74) 5.6( .47) 12. 5( 7.9( 20. 3( 21.4( .85) .72) .74) .92) 8.2( .83) 39.1(1.15) 41.7(1.27) 12. 4( .79) 71.7(2.34) 25.1(1.36) 19. 4( .77) 11. 1( .93) 9.1( .88) 43. 0( .95) 17. 3( .53) 7.2( .46) 27.3(2.37) 31.9(1.47) 13. 4( .73) 4.5( .18) 2.6( .37) 6.6( .62) 12.1(1.95) 1.7( .77) 1.6(2.67) 51.1(2.02) 24.9(1.65) 26. 4( .84) 7.2( .60) 16.2(1.57) 32. 2( .94) 2.8( .13) 26.9(1.06) 14. 7( .97) 1.5( .13) 19.5(1.89) 17. 3( .38) 23. 8( .70) 42.9(1.31) 14. 3( .91) 15. 6( .62) 15.5(1.29) 1.3( .13) 12.8(1.11) 22.6(1.03) 7.1( .72) 28.3(1.12) 28.2(2.35) 3.7( .36) 18. 7( .85) 11.7( .46) 23.1(1.93) 84.1(1.28) 8.7( .88) 11.7(5.32) 90.3(1.13) 39.8(3.55) 31. 4( .69) 37.0(1.59) 3.7( .25) 20.5(1.13) 1.9( .34) 51.5(1.49) 47.8(1.05) 26.1(1.12) 16.2(3.12) 38.8(1.12) 1.9( .41) 24.7(2.40) 76.4( .95) 53.8(1.19) 46.8(2.01) 9.4(1.81) 24.8(1.36) 44.1(1.27) 52. 1( .84) 99.4(17.75) 30.6(3.69) 19.3(1.82) 11. 5( .25) 7.4( .32) 1.7( .30) 73.8(1.19) 68. 1( .85) 51.2(1.32) 42.2(1.81) 17.9(3.44) 4.0( .48) 25.9(1.30) 20.7(3.70) 36.5(1.05) 34.3(3.33) 69.7(1.12) 52. 9( .66) 20. 0( .44) 6.0( .30) 51.2(1.48) 7.6(1.65) 98.5(1.58) 58. 0( .72) 37. 6( .97) 62.9(1.39) 21. 5( .92) .8( .15) 63.7(1.84) 71.7(1.15) 90.0(1.12) 49.4(5.95) 50.0(2.51) 20.3(1.92) 57.9(1.67) 14. 8( .24) 91.6(1.14) 14. 6( .73) 83.8(2.42) 48. 8( .78) 15.4(1.45) 9.2(2.56) 43 Table 5. — Continued Soil Association County Area Percent of County Productivity Index classes - high levels of management < 70 70-85 85-100 100-115 115-130 130-145 > 145 MADISON MARION MARSHALL MASON MASSAC MC DONOUGH MC HENRY MC LEAN MENARD MERCER MONROE MONTGOMERY MORGAN A D E H L K 0 P Z F P Q A B C M N Z A L W X 7. M P W Z A D N B G H I J M S T n V w A B I J M N W A L N W X z A L W X z E 0 p z A D E P Q A L N W z 9.0 12.4 15.6 1.9 8.8 4.7 11.9 23.3 12.4 41.6 2.0 56.4 34.3 19.0 9.4 3.1 31.3 3.1 9.7 2.3 15.0 63.3 9.7 2.3 57.9 21.9 17.9 73.0 6.5 20.5 2.0 10.4 6.0 6.0 3.8 7.9 11.2 13.8 13.9 3.6 21.6 21.0 22.8 24.4 16.3 6.6 4.3 10.4 38.0 13.3 9.5 20.3 9.6 9.3 51.0 26.5 6.8 2.2 13.6 4.8 31.6 34.9 28.7 1.6 33.0 28.7 27.0 9.7 55.8 4.3 35.7 2.3 2.0 .8( .22) 5.3( .45) .6( .26) 3.3(1.57) 8.0(1.03) 19. 4( .92) 12. 5( .95) 10.0(2.22) 13. 0( .74) 17. 4( .63) 22.3(2.86) 1.8( .49) 4.6( .17) 3.3( .75) 2.1( .91) 13.0(10.83) 15.5(2.98) 51.6(5.74) 60.2(3.01) 11.3(1.19) 29.3(1.65) 15.8(1.00) 32.0(1.08) 16. 6( .92) 14.0( .57) 6.8( .69) 45.8(2.54) 34. 5( .84) 1.7( .33) 3.6(1.64) 6.2(2.58) 24.8(2.34) 15. 2( .96) 19.8(3.81) 34.2(1.92) 19.2(1.33) 34.1(1.12) .8( .05) 44.1(4.16) 16. 5( .92) 62.1(4.31) 42.0(1.71) 2.7( .52) .2( .02) 18.9(1.20) 16.1(7.32) 17. 9( .46) 1.9( .20) 1.7( .35) 4.8( .45) 14.8(1.20) 8.3( .24) 8.6( .78) 7.8( .63) 3.9( .27) .3( .06) .2( .09) 3.0( .64) 1.3( .26) 1.8( .17) 29.7(1.88) 3.8( .26) 3.1( .60) 6.9( .39) 4.7( .30) 9.3( .65) 22. 6( .74) 6.1( .25) 3.5( .67) 16. 4( .92) 2.7( .19) 7.7( .52) 16.8(1.54) 15. 5( .35) 11.9(1.03) 23.0(1.06) 12. 0( .44) 25. 3( .86) 23.8(1.02) 17. 0( .70) 75.5(1.09) 22. 2( .96) 28.5(1.24) 30.1(2.05) 11.5(2.35) 6.4( .67) 22. 9( .81) 29.1(1.04) 21.1(1.44) 13. 8( .64) 15.2(1.00) 3.4( .36) 62.8(2.57) 19. 6( .70) 17. 5( .75) 22.2(1.46) 18. 3( .75) 7.0( .48) 11.6(1.06) 32.7(1.20) 29.0(5.92) 26.2(1.40) 17.4(1.51) 1.3( .13) 8.4( .27) 37.0(1.32) 22.8(1.03) 27.0(2.37) 30. 6( .91) 40.3(1.78) 14. 2( .93) 12. 2( .83) 6.0(1.22) 3.6( .35) 26. 7( .85) 10. 0( .36) 28.7(1.05) 12. 8( .84) 11. 3( .77) 28.9(1.33) 37.1(1.35) 13.4( .88) 15.0(1.60) 1.3( .05) 25.8(1.76) 20. 7( .95) 22.5(1.88) 26. 8( .41) 10. 4( .96) 3.8( .24) 4.1( .36) 8.8( .89) 7.8(1.26) 6.8(3.09) 37.6(1.19) 53. 8( .86) •7( .23) .7( .17) 18. 3( .94) 36.0(1.41) 17.9(1.47) 17.6(1.01) .3( .20) 4.1( .98) 15. 0( .86) 20.3(1.48) 53.8(1.65) 11.2(1.35) 17.5(1.65) 3.9(3.54) 17.7(4.92) 6.4( .78) 1.6( .20) .2( .03) 2.4(1.26) 11.7(1.26) 12.4(1.57) 13. 3( .83) .4( .21) 4.2(5.25) 7.2( .84) 5.9( .94) 10. 2( .85) 5.8( .56) 43. 3( .96) 18. 3( .84) 10.2(1.03) 93.4(2.96) 1.9( .16) 12.5(1.09) 32.7(1.29) 5.2( .34) 35.2(1.11) .4( .02) 24. 4( .77) 7.4( .62) 4.2( .06) 6.9( .70) 23.2(2.25) 21.0(1.96) 52.3(3.31) 56.9(1.67) 23. 1( .70) 26.5(1.21) 22. 4( .73) 10.5(1-27) 12. 1( .76) 23.0(1.25) 48.1(1.90) 7.4( .62) 9.5( .92) 22. 0( .65) 20. 3( .62) 35.7(1.63) 12.8(1.29) 16. 5( .65) 11. 2( .93) 4.2( .37) 7.9( .80) 28.0(1.11) 4.7( .31) 91.6(2.90) 11. 8( .98) 19.5(1.70) 46.6(1.84) 55. 6( .89) 61. 9( .77) 44.0(1.14) 6.2( .58) 6.6( .80) 51. 3( .82) 15.7(2.15) 30.3(1.18) 11.1(3.08) 3.1( .69) 4.1(1.78) 2.0( .15) 5.1( .80) 26.4(1.70) .3( .04) 32.9(9.14) 49.1(1.77) 10.8(1.69) 14.3(1.83) .9( .39) 5.6(2.67) 1.7( .38) 10.3(8.58) 8.3(1.01) 6.6( .31) 6.2(1.82) 29.1(4.55) 12.3(1.21) 6.3( .90) 3.8( .90) 8.5( .41) 4.1( .64) 3.1(1.35) .8( .67) 7.0(2.06) 1.2( .33) 2.1( .47) .3( .05) 1.8( .78) 6.0( .45) .3( .18) 13. 8( .71) 1.4( .74) 23.7(2.93) .4( .21) 10.8(1.05) 3.5( .41) 13.0(1.65) 3.0(1.58) •9( .47) 2.1(1.11) 6.2(1.72) 19.4(24.25) 10.3(1.61) 3.0( .52) 7.4(7.40) 12.6(1.14) 33.8(1.52) 24.8(1.62) 18.0(1.02) 1.2( .63) 1.7(1.42) 8.6(1.37) 1.2( .63) 16.6(2.05) 26.7(4.24) 3.7(1.95) 36.7(3.56) 27. 5( .79) 1.2( .26) .8( .10) 18.8(1.29) 3.9( .22) 1.5( .68) •2( .13) 2.6(1.53) 77.3(1.24) 72.1(12.88) 13.7(1.29) .6( .01) 11.9(1.06) 18. 4( .56) 35. 6( .78) 30.4(1.30) 29.9(1.50) 4.1(1.21) 10. 4( .71) 16. 8( .92) 1.8( .32) 26. 7( .77) 77.0(1.24) 83.6(1.04) 62.5(1.38) 51.8(2.22) 51.2(2.57) 11.6(1.09) 66.1(1.91) 71.4(1.15) 9.1(1.10) 9.1( .86) 39.1(1.13) 1.5( .33) .6( .07) 49. 5( .80) 13.1(1.58) 2.7( .08) 29.8(3.63) M .24) 1.3(1.18) .2( .06) 1.0( .12) 57. 4( .92) 26.1(1.02) 1.3(2.17) 4.4( .72) .4( .11) 1.8( .25) 11.1(1.11) 3.7(1.61) 3.4(1.79) .7( .25) 1.8( .82) .2( .25) 6.4( .25) .5( .23) 28.3(1.46) 14. 5( .57) 4.7(2.14) 13. 5( .92) •4( .27) 1.9(1.12) 6.6( .34) 13.6(6.18) 28.8(1.97) 1.1( .73) 8.0(1.90) 2.9( .24) 19.7(1.13) •7( .47) 7.3(1.74) 33.9(1.94) 39.7(2.90) 1.7(1.00) 24.8(1.28) 21. 7( .85) 1.8( .28) 5.9( .38) 1.0( .53) 15.9(1.96) 9.7(5.10) 41.9(4.07) 1.4( .74) 21.6(1.82) 9.0(2.31) 8.6(1.09) .!( .05) 6.5(2.83) 8.0( .61) 24.8(3.88) 29.4(1.90) 5.5( .71) 22.3(2.86) 32.7(1.86) 24. 1( .87) 17.5(2.24) 23. 6( .96) 6.1( .31) 23. 8( .81) 17. 0( .94) 17. 4( .71) 1.0( .04) 40. 7( .93) 24. 9( .84) 29.5(1.27) 54.2(2.23) 37.5(1.19) .9( .08) 5.4( .87) •9( .41) 9.1( .29) 42.6(3.55) 75.5(1.15) 14.7(1.36) .6( .27) 4.0(6.67) 5.6( .47) 14.6(1.27) 5.3( .54) 60.9(2.41) 100.0(3.16) 2.2( .61) 18.2(1.53) .4( .05) 3.2( .20) 4.4(2.32) 31.5(3.89) 19.1(3.03) 1.0( .48) 4.8( .62) 10. 0( .36) 8.8(2.00) l.5( .65) 6.1( .46) 6.0(1.33) 14.3(1.59) 19. 7( .99) 10. 2( .57) 7.1( .17) 7.0(1.35) 9.6( .54) 7.5( .47) 1.8( .13) 7.0( .64) 29. 8( .68) 28.3(1.21) 26.2(1.14) 10. 0( .68) 13. 4( .62) 27. 1( .99) 36.1(2.37) 5.6(3.29) 16.6(4.61) 11.1(10.09) 69.8(1.12) 13.3(1.25) 1.2( .03) 44 Table 5. — Continued Soil Percent Association of County Area County Productivity Index classes - high levels of management < 70 70-85 85-100 100-115 115-130 130-145 > 145 MOULTRIE OGLE PEORIA PERRY PIATT PIKE POPE PULASKI PUTNAM RANDOLPH RICHLAND ROCK ISLAND ST. CLAIR SALINE SANGAMON B H A B G H I L M T W Y A N W Z F P Q w B M W Z 0 p w z A B G L M N V X Z E F 0 P Q Z F Q Z A L W X Z A D E 0 P Q W Z Q R W A N Z 76.9 23.1 30.2 8.2 1.6 1.7 16.2 13.1 3.3 3.3 17.5 5.0 27.8 64.9 2.0 5.3 30.6 9.4 58.5 1.4 84.7 12.5 2.8 12.0 44.3 24.1 19.6 21.1 65.9 4.7 8.3 5.5 51.3 29.1 14.2 38.1 1.8 9.2 3.4 3.7 14.6 5.8 13.4 10.0 10.1 2.0 20.8 30.6 20.2 16.2 46.4 48.4 5.3 24.4 42.6 15.3 8.8 8.8 3.5 9.9 6.2 22.6 37.3 2.1 4.1 14.3 40.7 13.6 45.8 70.7 19.2 10.0 1.4(1.75) 12.2(1.42) 3.0(1.58) 5.1(6.38) 8.6(1.34) M -33) .6( .17) 9.4(4.09) 2.3(1.92) 6.0( .73) 18. 4( .87) .9( .26) 15.6(1.18) 8.0(2.22) 19.5(2.79) 1.1( .17) 13.2(1.02) .6( .26) 4.2( .93) 1.7( .77) 4.3( .41) 10.5(2.02) 15.6(7.09) 24. 5( .63) 51.9(5.46) 7.7(1.64) 18.0(1.01) 1.6( .15) 17. 6( .52) 7.8( .54) 21.7(1.53) 5.5(1.06) 14. 1( .89) 1.6( .33) 16. 5( .59) 17.1(1.16) 21.5(4.39) 11. 9( .64) 6.8( .55) 29.0(1.32) 16.0(1.33) 22.2(2.16) 19.9(1.86) 8.9( .56) 32. 3( .95) 15.0(1.30) 15.4( .70) 5.4( .65) 44.1(1.74) 19.8(2.79) 10. 7( .89) 8.5( .86) 4.1( .13) 1.0( .34) 88.0(1.10) 34.8(1.75) 42. 8( .69) 30. 1( .38) 5.3( .47) 3.2( .10) 49.7(1.09) 9.8(1.18) 28.6(1.44) 10. 2( .69) 32. 7( .95) 2.1( .20) 59. 1( .95) 8.0( .75) 100.0(2.89) 2.6( .36) 1.2< .71) 3.2(5.33) 23.8(3.90) 17.7(5.06) 1.8(2.25) 14. 2( .73) 1.0( .14) 1.9( .83) 6.9(3.14) 9.2( .41) .!( .06) 21. 5( .84) 7.7( .74) 16. 9( .78) 44.7(1.59) 39.6(3.47) 5.6( .37) 21.7(1.02) 22.9(1.56) 29.5(1.08) 4.6( .19) 83.9(1.21) 18. 5( .79) 9.4( .41) 5.9( .39) 2.1( .43) 28.7(1.02) 27.5(1.87) 25.9(1.19) 27.6(1.01) 7.8( .32) 8.4( .36) 4.3( .41) 21.5(1.41) 22. 6( .93) 35.3(1.20) 24.2(1.04) 14. 5( .95) 14.4( .59) 11. 7( .80) 14.6(2.98) 16. 2( .87) 13. 2( .61) 32.8(1.17) 28.9(1.05) 6.6( .29) 3.7( .39) 25.4(1.04) 62.8(1.44) 52. 3( .75) 29.9(1.01) 27.6(1.18) 11. 9( .52) 34.5(1.41) 71.0(1.02) 29.3(1.27) 47.9(1.96) 20.8(1.41) 21.6(1.00) 10. 3( .68) .4( .04) 23.7(1.61) 8.0( .73) 22. 2( .51) 23. 9( .81) 32.8(1.41) 38.9(1.69) 44.7(2.94) 65.8(2.10) 21. 7( .94) 40.0(3.85) 25.4(1.67) 4.7( .32) 21. 1( .77) 3.0( .12) 10.6(1.31) ,6( .07) 5.8( .26) 1.8( .95) 12.2(1.03) 1.1( .58) 14.2(2.25) 1.0( .53) 7.2( .77) 6.9( .87) 15. 9( .99) 1.5( .19) 2.0( .54) 21. 7( .78) 8.6(1.95) 88.8(3.62) 5.7( .58) 33.5(1.86) 53.6(1.30) 94.1(6.53) 1.2( ) 16.0(1.51) .3( .07) 19.4(1.11) 12. 5( .91) .5( .63) 14.1(1.64) .6( .50) 1.9( .53) 9.8( .95) 34.1(1.56) 21.3(1.78) 8.2( .71) 8.3( .84) 68.5(2.17) 2.8(1.27) .1(1.00) 2.6( .10) 56.8(1.80) 85.8(1.07) 1.6( .08) 100.0(2.89) 44. 9( .72) 1.0( .12) 5.9( .56) 15.2(1.85) 3.7( .51) 3.6( .19) 8.8( .34) 6.3(1.21) 17.8(1.00) 34.5(2.18) 8.1( .33) 18.2(1.01) 2.2( .46) 38.1(2.65) 15. 9( .65) 35.3(1.20) 31.1(1.73) 59.3(4.12) 47.1(1.92) 2.1( .40) 33. 6( .87) 3.1( .17) 28.6(2.70) 12. 8( .81) 8.4( .68) 17.0( .56) .5( .02) 12. 3( .62) 14.2(1.45) 40.4(1.37) 23.9(1.33) 42.2(1.02) 24. 3( .99) 10.9(1.11) 44.8(1.08) 41.8(1.71) 2.7( .52) 10. 9( .61) 27.3(1.90) 74.2(2.43) 10. 3( .42) 23.7(4.56) 21.2(2.36) 11. 4( .57) 32.5(1.10) 19.5(1.08) 18. 5( .45) 28.0(1.94) 7.4( .30) 45.6(1.10) 2.5( .52) 31.8(2.21) 4.7( .90) 9.4( .59) 5.3( .22) 20.9(2.58) 2.8( .44) •4( .21) 7.5( .95) 50.8(1.51) .7( .37) .6( .32) 22.6(1.71) 12.1(2.69) 15. 2( .87) 32. 0( .88) 6.0(2.73) 47.8(1.73) 10. 7( .74) 31.1(4.86) 4.1( .53) 27.4(1.56) 35.5(1.28) 23.2(3.63) 28.6(3.67) .!( .04) 2.0( .16) .2( .09) .5( .32) .!( .06) 9.2(1.16) 1.3( .68) 1.5( .06) 9.5( .30) 8.6( .72) 6.6( .64) 4.8( .45) 17.4(1.51) 15. 3( .70) 18.2(1.84) 13. 8( .75) 3.7( .25) 54.3(1.72) 76.1(1.22) 78. 8( .98) 29.5(2.63) 1.3( .68) 2.8( .46) 66.3(3.42) 12.3(1.68) 19. 8( .77) 14.2(5.07) 17.2(1.18) 10.3(6.87) 3.2( .76) 10. 7( .88) 10. 5( .60) 9.4( .69) 3.0(2.00) 4.3(1.02) 10. 1( .74) 1.4( .93) 4.3( .67) 8.8(1.07) 3.2( .37) 8.4(1.33) 28.1(1.60) 14.8(1.44) 1.7( .89) 7.5( .63) 12.3(1.32) 2.0( .51) 6.2( .78) 27.6(1.73) 5.1(2.68) 10.5(1.13) 13.4( .84) 7.2(3.79) 9.8(5.16) 16.4(2.02) 1.5( .79) 2.2( .21) 4.2(1.17) 7.1(1.58) 22.6(1.10) 22.1(1.43) .7( .09) 10.6(1.36) 21.3(5.76) 16. 0( .91) 31.7(1.14) 8.8(2.00) 17.3(2.22) 1.6( .43) 2.4( .55) 1.8( .23) 11.9(5.17) 11. 2( .85) 1.5( .23) 8.8( .57) 3.7( .47) 1.1( .48) 3.6(1.71) 56.4(7.23) 17. 0( .97) 24. 4( .88) 25.9(5.89) 16.1(2.52) 16.1(2.06) 2.7( .61) 13. 6( .94) 7.4(1.16) .6( .26) 9.0(2.00) 4.5( .58) 3.6( .18) 4.8( .45) 6.4(1.14) 21.6(4.70) 7.1( .87) 3.5(2.06) 1.0( .16) .!( .05) 15. 8( .50) .9( .31) .7(1.00) 11. 6( .97) 14.6(1.27) 28.2(1.11) 14. 4( .95) 33.3(1.05) 15.6(1.30) 38. 9( .59) 2.1( .19) 10.5(1.69) 4.3(1.95) 43. 2( .69) 6.5( .78) 30. 8( .89) 52.7(6.43) 35. 9( .58) 10.3(1.84) .8( .47) 5.6(5.09) 10.0(2.78) 16.7(15.18) 18. 8( .97) •5( .23) — 3.3(1.06) 7.0(1.67) 9.8( .80) 6.3( .36) 14.7(4.08) .6( .15) 2.6( .33) 10.0(4.55) 2.7(1.80) 3.3( .24) 8.6( .24) .8( .36) 1.1( .65) 23. 1( .90) 12.1(8.07) 1.3( .68) 1.8( .95) 26.6(1.66) 35.3(1.05) 6.6(3.47) .3( .16) 1.1( .17) 14.6(7.68) 6.1( .19) .3( .04) 28.0(1.11) 9.4( .78) 15.1(1.53) 44.8(1.42) 79.1(1.27) 21.2(2.00) 15.7(1.91) 45 Table 5. — Continued Soil Percent Association of County Area County Productivity Index classes - high levels of management < 70 70-85 85-100 100-115 115-130 130-145 > 145 SCHUYLER SCOTT SHELBY STARK STEPHENSON EUBRtt UNION VERMILION WAS ASH WARREN WASHINGTON WAYNE A D I N Z A L N W X ^ I D E F M P Q w z A D N W A L T W Y A N W X z 0 P z B I J K M V W F 0 P Q w X z A L N E F P Q W Z 1 Q w z 2.7 S.2 19.0 62.2 10.8 16.8 16.3 30.0 9.4 13.9 13.6 19.4 6.3 24.4 6.5 9.6 14.4 13.0 3.2 3.3 41.6 2.1 29.2 27.1 32.5 13.3 4.4 12.2 37.6 50.2 15.1 2.8 11.1 20.8 17.8 62.0 20.2 25.4 11.1 27.0 2.8 11.5 5.4 16.8 12.6 16.8 17.6 7.6 14.9 5.0 25.6 77.3 13.7 9.0 14.4 40.9 4.3 34.1 4.4 1.9 28.1 51.6 8.5 11.8 2.0( .25) 2.4( .38) 14.4(6.26) 9.7( .73) 2.2( .49) 32. 5( .86) 28.4(3.16) 33.3(1.87) 21.3(1.35) 34.4(1.40) 13.4(2.58) 10. 8( .61) 13. 7( .87) 43.8(1.44) 41.7(1.70) 6.5( .33) 17.4(1.78) 7.6( .72) 15. 2( .84) 42.1(1.02) 29.7(2.06) 15. 2( .62) 2.7( .52) 4.6( .51) 19.8(1.25) 4.5( .31) 9.9(1.90) 18.1(1.02) 29. 2( .86) 10.4( .72) 20.9(1.47) 2.4( .46) 29.0(1.84) 11. 9( .81) 22.5(2.06) 24.1(1.11) 28.0(1.02) 19. 7( .81) 16.3(1.11) 21. 3( .98) 22. 5( .82) 4.1( .27) 14.3(1.52) 8.2( .34) 6.6(1.35) 49.5(4.54) 70.1(1.60) 53. 1( .77) 22. 3( .79) 20. 2( .87) 19. 7( .86) 43.2(2.84) 1.3( .05) 24.5(1.67) 20.9(1.92) 25. 1( .92) 14. 8( .97) 13. 7( .93) 38.2(1.76) 41.2(3.61) 17.9(1.18) 27.3(1.28) 10. 1( .69) 28.7(1.05) .3( .03) 10. 8( .45) 39.0(1.32) 8.2( .35) 50.3(2.06) 6.7(1.37) 4.8( .46) 40.3(1.29) 13. 8( .49) 13.4( .59) 13. 0( .86) 77.6(1.12) 44.8(1.52) 37.0(1.59) 50.5(2.20) 10. 3( .68) 1.3( .14) 5.2( .21) 12. 9( .88) 13. 9( .64) 11. 6( .42) 17. 2( .39) 60. 2( .87) 33.0(1.42) 28.5(1.24) 30.0(1.97) 27.5(2.29) 49. 0( .75) 14.7(1.28) 9.8( .99) 28. 4( .90) 7.4( .62) 8.4( .73) 5.2( .53) 22. 6( .89) 13. 8( .22) 13. 3( .69) 28.7(1.12) 2.9( .35) 7.6( .72) 17.6(2.15) 55. 6( .89) 15.0(1.81) 16.7(1.58) 55.5(1.60) 6.9(1.50) 23.6(2.88) 63. 8( .80) 2.2(1.29) 29.1(1.50) 25. 0( .98) 12.9(5.86) 1.3( .68) 11.9(1.47) 4.0( .63) 4.9(2.58) 3.9(1.70) 3.6( .27) 12.9(2.87) 35.0(2.26) .9( .75) • 7( .37) 2.0(2.50) ,3( .08) 1.5( .13) 4.2( .45) 5.2( .60) 1.2( .15) 14. 7( .92) 25. 9( .82) 26.7(2.59) 50. 2( .77) 16.4(1.52) .6( .21) 6.5( .30) 4.2(1.91) 2.0( .48) 15.4(3.67) 26.0(3.56) 21.4(1.22) 18.8(1.37) 3.6( .46) 3.5( .95) 11.0(3.06) 9.5( .34) 3.2( .73) 1.3( .20) 1.4( .61) 3.3(1.57) .7( .16) 5.8(8.29) 21.4(1.08) 28.4(7.89) 1.4(1.27) 3.2( .09) 70.9(8.65) 64.3(1.03) 58.8(10.50) 14.3(1.35) 68.7(1.99) 44. 2( .71) •9( .11) 2.6( .18) 43.7(1.26) 8.9( .86) 80.8(1.30) .9( .08) 45.6(1.32) 14.6(1.78) 22. 6( .89) 12. 7( .40) 6.4( .53) 3.9( .06) 14.9(1.51) 11. 5( .45) 20.8(1.73) 24.7(2.15) 13.6(1.64) 25.6(1.01) 6.6( .93) 6.6( .55) 8.9( .90) 8.7( .34) 4.4( .29) 55.2(1.75) .6( .10) 1.1( .50) 38.5(1.22) 10.3(1.00) 30.7( .90) 24.7( .75) •4( .24) .3( .16) 8.5(2.36) 8.0(1.27) 17. 2( .67) .5( .23) 2.4(1.41) 16. 0( .82) 1.8( .95) 1.4( .17) 3.9( .18) .5( .26) 4.3( .36) 7.2(3.13) .7( .05) 9.4(1.34) 1.9( .86) 19. 9( .89) 12. 1( .93) .!( .04) 2.4( .53) 22. 8( .89) 7.3(1.16) 45.6(24.00) 8.7( .84) 6.6(3.48) 2.4( .62) 19.0(2.41) 23.5(1.61) 3.2(2.13) 21.5(1.76) 10. 0( .57) 22.9(1.48) 3.1( .40) 13. 8( .78) 50.6(1.83) 4.8( .62) .7( .58) 40.2(1.32) 6.4( .26) 22. 8( .77) 11. 1( .62) 6.4( .26) 2.6(1.18) 7.8(1.66) 9.6(1.96) 99.3(7.64) 19.3(1.82) 27.7(2.23) 3.3( .23) 10.9(1.11) 29. 3( .99) 23.2(1.29) 25. 8( .62) 8.4( .58) 48.5(1.59) 27.5(1.12) 3.3( .63) 15. 8( .89) 19.1(1.21) 1.3( .07) 9.3( .95) 28.9(1.61) 37. 1( .90) 51.9(3.60) 4.6(7.67) .9(1.13) 74. 3( .93) 56.7(1.25) 15. 0( .64) 1.5(5.00) 13.8(1.89) 6.2(2.21) 1.5( .68) 2.7(2.70) 6.3( .98) .7( .06) 5.0(1.39) 9.6( .47) .9( .14) 2.6( .70) 13. 0( .74) 20. 1( .73) 6.3( .73) 5.1( .29) 27.0(1.23) 36.3(1.97) 16. 7( .66) 8.6(1.39) 13.0(5.91) 66.0(2.61) 28.3(1.87) 58.2(1.84) 9.8( .82) 22.1(1.92) 25.4(2.57) 12.6(1.17) 1.0( .34) 1.0( .45) 14. 9( .75) 1.7( .30) 64.6(1.87) 8.9( .96) 4.2(1.08) 3.7( .47) 20.5(1.28) 1.6( .84) 13.0(1.26) .8( .42) .5( .26) 8.5(1.05) 3.0( .17) 3.2( .23) .4( .18) 13.2(2.06) 8.8( .57) 8.4(1.08) •5( .22) 4.5( .34) 2.6( .58) .!( .01) 3.6( .97) 10. 8( .39) 4.8(1.09) 11.6(1.80) 21.8(2.79) l.9( .51) 3.2( .73) 3.1( .48) •9( .12) 3.1(1.82) 4.2( .22) 24. 1( .94) 10.1(2.40) 9.7(2.31) 7.3( .42) 14.5(1.06) 4.7(2.14) 2.7( .64) 11. 9( .87) 70.0(1.13) 31.0(3.73) 17.2(1.62) .3( .18) 58.4(4.91) 16.3(1.75) 19.0(2.41) 15. 1( .94) .9( .47) 1.4( .74) 3.9( .42) 13. 0( .81) — .9( .04) 76.8(2.43) 20.6(2.10) 52.5(1.27) 68.6(4.76) 92.6(3.78) 70.8(1.02) 19. 3( .84) 24.3(1.60) 4.4( .18) 4.0( .16) • 5( .33) 1.6( .84) 46 Table 5. — Concluded County Soil Percent Association of Area County Productivity index classes - high levels of management < 70 70-85 85-100 100-115 115-130 130-145 > 145 WHITE WHITES IDE WILL WILLIAMSON WINNEBAGO WOODFORD 0 P Q R W X z A L W X Z G I J V W X Y F P Q R W A G H L T W Y A B C N X 6.2 29.1 21.8 2.3 17.3 7.3 15.9 19.1 14.0 42.2 5.3 19.4 3.1 8.6 44.9 27.1 3.1 8.8 4.4 5.2 17.9 53.4 13.7 9.9 15.7 .9 16.7 2.6 18.0 37.1 9.1 39.9 19.6 6.7 31.0 2.8 .8( .07) 10. 5( .60) 13. 1( .96) 28. 9( .79) .!( .05) 14.1(3.62) 10.5(1.33) 22.3(1.39) 32. 9( .98) .7( .37) 2.1( .20) 4.7(2.47) 12.5(6.58) 11.5(1.42) 5.8(3.05) 6.9( .67) 2.0(1.05) 6.6(1.03) 7.3(6.08) 6.1( .35) 23. 7( .86) 5.3(1.20) 13. 4( .92) 3.4( .53) 10. 3( .66) 5.5( .71) 2.4(1.04) 13. 0( .98) 4.8( .75) 17.8(1.15) 9.5(1.22) 16.7(2.04) 2.5( .74) .6( .09) 28.6(1.39) 16.1(2.52) 12. 2( .79) 10. 7( .82) 30.2(1.09) 3.9( .89) 25.7(1.77) 70.0(10.94) 10.1(4.39) 11.1(1.35) 29.0(1.37) 19.6(1.48) 25.7(3.67) 2.9( .45) 10. 2( .78) 2.3(1.00) 6.3(5.25) 8.9(2.12) .3( .07) 18.2(1.17) 18. 7( .63) 16. 0( .89) 38. 0( .92) 12.8(2.67) 25.8(1.79) 41.8(1.37) 14. 7( .60) 4.8( .92) 15. 2( .85) 22.1(1.53) 35.8(1.17) 21. 3( .87) 15. 7( .41) 2.2( .47) 9.6(1.96) 7.5( .60) 8.4( .28) 1.4( .10) 5.5( .56) 18.0(1.00) 31. 5( .76) 5.4(1.13) 1.5( .10) 17.6(3.38) 24. 1( .62) 6.1( .64) 56.6(1.92) 37.5(1.61) 21. 3( .93) 12.1(1.16) 41.3(2.72) 19.5(2.07) 46.9(1.92) 23.6(1.61) 36.1(1.66) 16.6(1.09) 26.0(2.77) 38.2(1.57) 27.9(1.49) 6.4( .62) 47.1(1.50) 31.1(1.38) 21.4(1.41) 42.2(4.49) 9.8( .45) 93.7(1.35) 18. 1( .78) 16. 5( .72) 10. 0( .96) 26.1(1.78) 7.4( .40) 10. 5( .91) 3.8( .61) 1.7( .77) 28.7(1.13) 24.5(1.62) 28. 1( .89) 10. 3( .86) 9.9( .86) 30.4(1.20) 10. 9( .72) 20. 1( .64) 3.0( .28) 30. 2( .87) 34.8(1.06) 17. 2( .93) 46.5(1.84) 12. 9( .85) .7( .10) 1.7( .37) 45. 9( .74) 9.8(1.18) 19. 5( .56) .9( .20) 8.4(1.02) 51.0(1.12) 7.2( .31) 3.6( .64) 16. 1( .47) 2.8( .61) 2.3( .22) •5( .29) 4.5( .23) .9( .41) 1.7( .12) •5( .33) 30.2(4.95) .4( .50) .6(2.00) 1.4( .50) 10. 7( .61) 2.4( .23) 23.3(1.97) .8( .09) 1.5( .19) 36.6(2.29) 17. 9( .53) 10.4(5.47) .3( .16) 19.1(1.31) 51.7(2.32) 32.2(1.84) 11. 5( .84) 41.0(1.12) 10.8(4.91) 2.9(1.71) 3.3( .94) 6.7(2.91) •3( .14) 30.2(1.35) .8( .47) .4( .67) 18. 5( .72) 2.6( .18) 7.3( .29) 7.3( .61) 57.4(5.36) 1.3( .08) 61.4(5.34) 11.1(1.34) 37.6(1.49) 35. 7( .57) 9.0(1.55) 40.7(1.25) 19.0(2.29) 6.1( .41) 32. 3( .93) 2.0( .19) 76.3(1.23) 77. 9( .97) 12. 5( .32) 10. 1( .95) 3.9( .85) 19. 9( .90) 1.0( .53) 4.3( .36) .5( .26) •1( -13) 25. 2( .74) 11. 9( .83) 45.7(3.22) 1.1( .21) •5( .23) -5( .21) 14. 8( .94) 32.5(1.07) 5.4( .47) 14. 1( .93) 7.6( .36) 9.4( .64) 4.6( .94) 4.1( .43) 30.4(1.11) .6( .06) 9.7( .81) 10.3(1.00) 74.0(1.64) 11.4(1.15) 21.4(1.42) 14.5(2.30) 20.8(2.02) a particular soil association at the county level. County data by soil association (Table 5) are the most detailed information presented in this bulletin and, it is hoped, will be useful in evaluating soil productivity within soil associations at the subcounty level. The high management Pi's of all 26 soil associations were analyzed to identify soil factors associated with various PI categories. The soils of 22 Illinois soil associa- tions had characteristics whereby the slope of the land and the depth of the topsoil were parameters that could be used to estimate the specific high management PI category of any soil association area from field observa- tion (see Table 6). In four terrace and bottomland soil association areas soil texture, color, and drainage were the parameters that permitted an accurate estimation of the high management PI category for a specific soil area. SUGGESTED RURAL LAND EVALUATION PROCEDURE Hancock County, Illinois, is used to illustrate the pro- cedure that could lead to more equitable and consistent rural land evaluation in the period before detailed soil survey reports become available for all counties. The average high management PI of all Hancock County soils is approximately the same as or slightly below the state average (Figs. 2 through 5). Hancock County contains numerous soil series repre- sentative of Illinois soil associations A, D, L, N, and Z. Soil productivity distribution data for all Hancock County soil associations except Z are given in Table 5. Soil association area Z has limited areal extent in Han- cock County and was not included in the 2 percent CNI sample. In cases in which productivity distribution data for county soil associations are missing, state soil asso- ciation productivity distribution data (Tables 3 and 4) can be substituted to give insight into common soil qual- ity variations within a soil association area. The guidelines in Table 6 supply the information for evaluating Pi's for each soil in Illinois. These guidelines 47 were developed by analyzing the PI characteristics of all areally significant soil series found within the soil asso- ciation or associations area represented by each guideline. Within a soil association, however, it is possible that the Pi's of a few soil series of very limited distribution are not as accurately evaluated as the major and more widely distributed minor soil series. Each guideline does not necessarily contain all seven PI categories or all feasible combinations of percent slope, topsoil thickness, texture, soil color, and drainage class. Only the PI categories and soil properties characteristic of Illinois soil association soil series are included. Table 6. — Field Guidelines for Estimating High Management Soil PI Categories for Soil Association Areas of Illinois* Soil pl association areasb Soil pj Relevant characteristics association areas Relevant characteristics Slop' (%) Inches of topsoil Soil texture Surf ace soil color A, B, I 145-160 130-145 0-4 a. 0-4 b. 4-12 More than 7 W Less than 7 More than 7 145-160 130-145 Soils with silty or loamy materials over medium textured materials Dark Moderately dark 115-130 a. 4-12 b. 12-18 Less than 7 More than 7 115-130 Light 100-115 85-100 <85 12-30 >30 >30 Less than 7 3-7 Less than 3 130-145 115-130 Soils with more than 30 inches of medium textured soil material over sandy or clayey material Dark-moder- ately dark Light C, D, H, JT Tk/f 130-150 0-4 More than 7 100-115 Soils with less than 30 Dark-moder- inches of medium textured atelv dark , L, M, N,U 115-130 a. b. 0-4 4-12 Less than More than 7 7 85-100 soil material over sandy or clayey materials Light 100-115 85-100 a. b. 4-12 12-18 12-30 Less than 7 x More than 7 3-7 100-120 85-100 Loamy topsoil Loamy topsoil Dark Light 70-85 >30 3-7 85-100 Sandy topsoil Dark <70 >30 Less than 3 <70 Sandy topsoil Light Soil texture characteristics E, F, G, K, O, S, T 115-135 a. b. 0^ 0-12 Less than More than 7 Y 7 100-120 More than 30 inches of medium textured material over limestone 100-115 a. b. 4-12 12-18 Less than More than 7 7 85-100 Between 12 to 30 inches of medium tex- tured material over limestone 85-100 12-30 Less than 7 <85 Less than 1 2 inches of medium textured material over limestone 70-85 >30 Less than 7 <70 >30 Less than 7 Surface Surface texture color Drainage Z 145-160 Medium Dark Well P,Q,V 100-120 a. b. 0-4 0-12 Less than More than 7 7 130-145 Medium Dark Moderately well/some- 85-100 a. 4-12 Less than 7 what poorly b. 12-18 More than 7 115-130 Medium Light Moderately 70-85 12-30 Less than 7 well/some- <70 >30 Less than 7 what poorly 100-115 Medium Light Poorly R 85-100 a. 0-4 Less than 7 85-100 a. Fine Light Poorly b. 0-12 More than 7 b. Coarse (sandy) Dark Well 70-85 a. 4-12 Less than 7 70-85 a. Fine Light Very poorly b. 12-18 More than 7 b. Coarse (sandy) Light Very well <70 a. >18 Less than 7 <70 a. Very fine Light Very poorly b. >2 Less than 3 b. Very coarse Light Excessively well * In general, a surface soil color of black, very dark brown, or extremely dark grayish-brown is identified in the guidelines as dark; very dark grayish-brown and very dark gray soils are considered moderately dark; all other soil colors aie considered light. Fine-textured soils identified in the guidelines are clay, sandy clay, and silty clay; coarse- textured soils are the sands and loamy sands; all other textural classes are considered medium or moderate. b Soil association area C soils that have heavy clay subsoils should be evaluated one PI category lower than indicated in the table. Soil association areas D and £ have a few soils of limited areal extent that have severe subsoil problems (Huey and Piasa, for example); such soils should be assigned productivity indexes of less than 85, even in areas with low slope and thick topsoil. A few areas in association F have soils with very severe subsoil problems (Huey, for example). These soils should be assigned a PI of less than 85 even if they have thick topsoils and jow slope. Small areas of soils in associations G and S (Rodman and Stonington, for example) have gravel within a few inches of the surface; these gravelly soils should be assigned Pi's of less than 85, regardless of slope and topsoil thickness. Association area V soils that have clay subsoils should be evaluated at one PI category lower than indicated in the table. Light-colored soils in associations T and U should be rated 10 PI units less than that indicated in the guidelines. 48 D Figure 8. Cross section of Hancock County soil association map. Figure 8 shows a cross section of an area on the pub- lished soil association map of Hancock County (6) . An assessor, after having trained with a soil scientist, should be able to evaluate this area effectively if equipped with the county soil association high management PI fre- quency distribution data and soil association field guide- lines for PI categories. Suppose, for example, an assessor evaluates the soil quality of an area in soil association L, Fayette-Rozetta-Hickory Association (6) . The PI cate- gory for that area could possibly be any one of the seven indicated in Table 5 ; if the approximate slope and topsoil thickness of the soil under analysis are known, however, the specific PI category for the area can be identified. An association L soil area with a slope of 4 percent and 5 inches of topsoil most typically will have a soil PI between 115 and 130 (an average of 122.5), according to the Table 6 guidelines. Another assessor evaluating the same Hancock County soil or evaluating another soil association L area with similar topsoil thick- ness and slope should estimate the same PI category if he follows the suggested procedures. Other soil associations in Hancock County can be evaluated the same way. In the Hancock County exam- ple in Figure 8, soil association areas D, A, and N are encountered from west to east. The soils of these associa- tions developed from good to excellent parent material and have not developed subsoil problems that reduce soil productivity. Variations in Pi's in these soil areas, as in association L, can be related to differences in slope and topsoil thickness. The pattern of PI distribution varies among associations D, A, and N, however; for example, the soils of association areas A and D exhibit a dominance of thicker topsoils and less slope and thus are more productive than those of association N. Never- theless, soils in association area N that have slopes and topsoil thicknesses comparable to those in associations A and D have Pi's comparable to those of soils in associa- tions A and D. State and county patterns of PI distribu- tions for associations A, D, and N suitably indicate to an assessor the distributional characteristics of soil pro- ductivity within the general association area that can be used to evaluate (and adjust) an assessor's preliminary land assessment. Productivity evaluation of soil association area Z at the eastern edge of the Hancock County example area illustrates two points. First, association area Z was not identified by CNI sample data, which means that pro- ductivity distribution patterns for association Z specific to Hancock County are unavailable. Under these cir- cumstances, the state PI distributions for soil association Z (Tables 3 and 4) should be used. Secondly, soil association Z, Sawmill-Lawson-Wake- land Association (6), in the Hancock County cross sec- tion will be more difficult to evaluate than other associa- tions. After training and some experience, an assessor will find that he needs to observe soil color, soil texture, and soil drainage rather than slope and topsoil thickness, since this soil association is composed exclusively of allu- vial soils. For example, a high management PI between 85 and 100 is expected if the observed association Z soil in Hancock County is well drained, light in texture (loamy sand) , and dark colored (Table 6) . Tract Pi's can be translated into average dollar sale value per acre of rural land by plotting recent rural land value sales against the corresponding PI average of the land sold (3) . Figure 9 illustrates this suggested ap- proach. In a hypothetical example, the sale values of 89 tracts of land were plotted against the Pi's for each tract. 900 iu K O HI Q. UJ D UJ < (0 8OO TOO 6OO 5OO 4OO 300 O 6O 8O 1OO 12O 14O TRACT - PRODUCTIVITY INDEX Figure 9. Hypothetical example of relationship between sale value and tract PI. 49 Through statistical analysis a regression line was estab- lished for these data that gives the average sale value of rural land per acre corresponding to a specific produc- tivity index. For example, a soil area with an overall high management PI of 100 will, on the average, have a sale value of approximately $550. With information simi- lar to that presented in Figure 9, assessors can relatively easily convert raw Pi's to actual land sale values. DISCUSSION Rural land can be evaluated consistently and equitably when the area under evaluation is analyzed by means of a single system of soil productivity data in conjunction with soil distribution data of comparable quality. The CNI soil distribution data combined within a high man- agement soil productivity framework are now available for each county of the state. As in the Hancock County example, these data can be used to help estimate the value of the soil land resources of a specific area in any part of Illinois. The resulting estimation of rural land values should thus be as fair and accurate as possible regardless of the area evaluated, even for counties with- out recent soil survey reports (provided the assessors apply the guidelines and data equally) . Other states might want to develop similar data and evaluation procedures if they have access to unprocessed CNI data, comparable county soil association maps, and a measurement of soil productivity that can be adopted for the purpose of land evaluation. The rural land evalu- ation procedures set forth in the Hancock County exam- ple can be used without supplementary data; however, all available soils data should be used, which will improve the quality of the final land assessment in selected areas. If detailed and accurate soil maps are available, a similar procedure can be followed except that the Pi's for all tracts are determined directly: Soil mapping units are measured and Pi's assigned; average Pi's for the tracts are then determined as they were determined here for CNI quarter-section tracts. A similar relationship be- tween sale value per acre and PI must be determined before assigning value. The use of additional detailed soils data can assure — with a very high level of confidence — that the correct PI category is associated with a specific soil tract; it can also determine a PI with more precision than the PI categories presented in this study. Additional detailed soils data would sharpen the focus of land evaluation, but using the data and procedures developed in this pub- lication will itself help improve the assessment of rural land. According to correspondence with Mr. Floyd Smith, Farm Land Appraiser, Department of Local Government Affairs, State of Illinois, Springfield, the State of Illinois officials primarily responsible for rural land evaluation have indicated three important needs : 1. To develop soil distribution data that are compa- rable in quality with one another and are associated with soil productivity characteristics. 2. To develop guidelines for using soil distribution and productivity data effectively to evaluate rural land. 3. To educate persons associated with land assessment to use soils data and guidelines that promise to alleviate the problems of assessment inequities. For the first time, comparable data are now available to carry out these functions for an entire state. It is the opinion of the authors and the State of Illi- nois officials involved in this project that the consistent use of data and guidelines developed in this study have a potential for improving a very specific land assessment problem. In addition, these data provide soil geography information of general interest to farmers, students of agriculture, merchants and other citizens who support rural activities, and academicians. The pedagogic func- tion of the data, however, may be secondary to the pur- pose of helping alleviate land assessment inequities. LITERATURE CITED 1. Fehrenbacher, J.B., G.O. Walker, and H.L. Wascher. 1967. Soils of Illinois. Illinois Agricultural Experiment Station Bulletin 725. Urbana, Illinois. 2. Odell, R.T., and W.R. Oschwald. 1970. Productivity of Illinois soils. University of Illinois Cooperative Ex- tension Service Circular 1016. Urbana, Illinois. 3. Oschwald, W.R. 1971. Suggested procedure for utiliz- ing soil surveys in tax assessment of agricultural lands. University of Illinois at Urbana-Champaign, College of Agriculture Agronomy Facts. 4. Mausel, P.W., E.C.A. Runge, and S.G. Carmer. 1975. Frequency distribution of tract productivity indexes and examples of their utilization in rural land assess- ment. SoU. Sci. Soc. Amer. Proc. 39:503-507. 5. USDA Soil Conservation Service. 1958. Soil and water conservation needs inventory sample plot data for all Illinois counties. Champaign, Illinois. 6. USDA Soil Conservation Service and University of Illinois at Urbana-Champaign Department of Agron- omy. 1970. Soil association map of Hancock County (Illinois).