"W '— ". '—-—- USE OF SOIL MANAGEMENT GROUPS AND RELATED INFORMATION IN EVALUATION OF FARMLANDS Thesis Io: tho 0.9m OI M. S. MICHIGAN STATE UNIVERSITY Thomas Wesley Fries? I960 LIBRARY Michigan State University Page I USE OF SOIL MANAGEMENT GROUPS AND HEIATED INFORIflTION IN EVALUATI ON OF FARMS By Thomas Wesley Priest AN ABSTRACT Submitted to the College of Agriculture Michigan State University of Agriculture and Applied Science in partial fulfinmnt or the requirement for the degree of MASTER OF SCIENCE Department of Soil Science 1960 A // ' . N ,1" Approved /£/70// “KEV“CJ) AN ABSTRACT A stucw was made in Baton County, Michigan to test a method of arriving at equitable evaluations of farm lands. The essential steps of the method are: (l) the soils represented in an area are assigned to soil mnagement groups, (2) the most comon land use for the slope goups in each soil management group is determined, (3) the acreage of each combination or soil management group, slope class and land use on each tract are measured and recorded, (1;) the average per acre yield of each soil management group and slope class for each use is determined, (5) the total value or the average production per acre on each soil mnagement group and slope class for each use is determined, (6) the cost of production per acre for each land use on each soil management group and slope class is determined, (7) the net income per acre for each soil group, land use and slope class is determined by subtracting the values in step number 6 from those in step number 5, (8) the expected net income for each tract is determined by multiplying the net income per acre by the acreage of each combination of soil management group, slope class and land we and totaling these resultsg (9) the evaluation or the farmland on the tract is completed by capitalizing the expected net income per tract at a rate consistent with sale prices of farm land in the area, (10) the total value or the property is the sum of the land value, the stumpage value of any timber on the land and the building or improvemnt values. Page III This method.sas used to make evaluations on a number of farms in Baton County, Michigan. These values were then compared.with.values determined by the Nichigan State Tax Commission and with.farmers' estimated land values. The computed land values averaged 112 percent of the Commission's appraised.va1ues uith.a correlation coefficient of .921 for the two values. The computed land.values averaged 97 percent of the farmers' estimated land values. On the basis of the results of this study the following conclusions seemuwarranted: (l) the computed land.values as determined by the soil magement group method compares favorably with both the Michigan.State Tax Commission's appraised.values and with farmers' estimates of the value of their land, (2) the use of soil maps can‘be of aid to township or county assessors in comparing farms, (3) the use of the values based upon the soils and land use would tend to remove bias and relative overtaxation of low value farms, (h) the soil management group method of land.evaluation could.provide a sound base for all appraisals of farmland, including those for sale, purchase or condemnation. (5) the soil.management group method of'land evaluation could.be used by management to determine the relative economic benefits from.various cropping systems on the soils of a specific tract. ACKNG‘YIEDGEMENT The author expresses his sincere appreciation to Dr. E. P. Whiteside, under whose guidance and interest this investigation was undertaken and whose suggestions were instrumental in bringing this thesis to a conclusion. He is also indebted to Mr. W. H. Heneberry for his interest and help in the progress of the study. Grateful acknowledgement is also due Mr. I. F. Schneider and Dr. R. L. Cook for their guidance and help, and to his fellow students for their helpful suggestions and assistance. USE OF SOIL MANAGEMENT GROUPS AND RELATED INFCRMATION IN EVALUATION OF FARMANDS By Thomas Wesley Priest A THESIS Submtted to the College of Agriculture Michigan State University of Agriculture and Applied Science in partial fulfillmnt of the requirements for the degree of MASTER OF SCIENCE Department of Soil Science 1960 Page V TABLE OF CONTENTS THE URPOSE REVIEW OF THE LITERATURE PROCEDURE Selection and.Description of the.Area Used to Test the Method Field Survey Soil Management Groups Land Use on the Soil Management Groups measurement of.Acreages Estimation of Crop Yields on the Soil management Groups by Slope Classes Estimated Net Income Per.Acre from Alternative Uses of Land Net Income for Woodland Determination of Net Income for various Tracts Capitalization of Net Income Total Value RESULTS Discussion .Additional Research Needs CONCLUSIONS BIBLIOGRAPHY APPENDIX Page VI PAGE 10 15 19 21 22 25 27 29 30 32 33 36 1:5 h6 149 TABLE I. II. III. IV. Ve VI. VII. VIII. LIST OF TABIES Estimated.Proportions of Slope Classes of Each Soil Management Group Used for Cropland, Permanent Pasture,‘WOOdland.and Other Uses in Eaton County Estimated Proportions of Cropland Occupied by Different Cr0ps on the Soil Management Groups by Slope Classes in.Eaton County Estimated Average Per Acre fields of the Principal Crops of Eaton County by Soil Management Groups and Slope Classes Estimated Per.Acre Yield of Rotational and Permanent Pasture by Soil management Groups and Slope Classes Prices of Products USed in Computing Net Income ‘Average Production Costs for Common Crops in Eaton County Average Production Costs for Bay and Pasture in Eaton County Estimated Net Incone Per Acre from Alternative Uses of Crchand, in.Eaton County by Soil Management Groups and Slope Classes Page VII PAGE 19 50 SI 52 53 Sh 55 TABLE IX. X. XI. XII. XIII. XIV. XV. XVI. Page LIST CF TABLES Estimated Net Income Per Acre from Alternative Uses of Land in Eaton County Volume Per Acre of Forest Products by Stand Size and Stocking Class Estimated Annual Increment Per Acre of Various Woodland Products for Each Soil Marngement Group, Eaton County Estimted Value of Annual Increment Per Acre from Various Woodland Uses for Each Soil Management Group, Eaton County Estimate of Percentage of Annual Increment Occurring as Saw Timber and Pole Timber by Woodland Species Estimated Proportion of Each Soil Management Group Occupied by the Various Groups of Woodland Species Estimate of Annual Net Incone Per Acre from Woodland Species on the Soil Managemnt Groups in Eaton County Ratio of Computed Net Income to Sale Price on Unimproved Farmlands or Those with Low Timber and Improvement Values in Eaton County VIII PAGE 57 58 S9 60 61 62 63 6h TABIE XVII. XVIII . XIX. XX. HI. XXII. HIII. Page DI LIST OF TABLES PAGE Ratio of Conputed Net Income to Farmers' Estimate of Farmland Value on Farm Account Farms in Eaton County 65 Ratio of Computed Land Value Per Farm to Appraised Land Value Per Farm on 26 Farms, Eaton County 66 Ratio of Computed Land Value to Farmers' Estimated land Value, Eaton County 68 Ratio of Computed land Value to Calculated Sale Price of land on 23 Farms, Eaton County 69 Ratio of Assessed Valm to Sale Price of Farm Real Estate on 99 Farm in Eaton County by Value Groups 71 Ratio of Assessed Value to Owners Estimte of Farm Market Value on 15 Farms in Eaton County by Value Groups 72 Ratio of Total Appraised Farm Value Per Farm to Sale Price on 23 Farms in Eaton County 73 Page X LIST OF FIGURES FIGURE PAGE 1. Location of Farms Used in This Study 75 2. Illustration of the Method Used in Measurement and Recording of Acreages 76 3. Relation of Assessed Value to Omers Estimate of Farm mrket Value on 15 Farms in Eaton County 77 h. A Graph Showing Relationship Between Farmers' Estimated Farmland Value and the Computed Net Inconn 78 S. A Graph Showing Relationship Between Computed Net Income and Sale Price of the Land on 6 Unimproved Properties in Eaton County 79 6. Relationship of Farm Sale Price to Michigan State Tax Commission's Appraised Farm Value on 23 Farms in Eaton County 80 70 A Graph Showing Relationship Between Computed Land Value and Michigan State Tax Commission's Appraised Land Value on 26 Farms in Eaton County 81 8. Relationship of Assessed Values to Sale Price on 99 Farms in Eaton County, Michigan 82 USE OF SOIL WEMEM‘ GROUPS AND RELATED INFCRMTION IN EVALUATION OF FARMLAN'DS THE PURPCSE The purpose of this study is to test a method of arriving at equitable evaluations of farm lands. These values, based upon the ability or land to produce income, could provide an equitable base for farmland evaluation. Equitable farmland evaluations are important to both borrower and lender as fair estimates of income potential and collateral as security, respectively. Individual farmers or farm management agencies could use these values in planning the choices of kinds and amounts of crops to grow on different soils in order to naximin farm incomes. These values could also be used as an equitable basis for tax assessments. REVIEW OF THE LITERATURE Interest in improving appraisal procedures of fam property taxes is becoming increasingly widespread. The large rise in property values and taxes during recent years is probably the most important reason for this increased attention. Property taxes rose 91 percent from 1950 to 1955 in a sample or agricultural townships in northern Michigan (3). The increase was due to a rise in tax rates as well as assessed valuations. Assessed valuations rose 66 percent during the five-year period while tax rates on the assessed valuations rose 25 percent. In Michigan, property tax collections have been rising for several decades except for the period from 1930 to 1935 (h). From 191p to 1956 the annual increase averaged ten percent. By 1956 the total property taxes in Michigan had risen to more than 600 million dollars, 70 percent of which was levied on real estate. Taxes on farm real estate averaged $1.32 per acre, which was the highest acreage rate in Michigan's history and almost three times the rate for 19140. Property taxes were once the main source of revenue for Michigan's state and local governments. Their relative importance has decreased since the early 1930's, but they still constitute close to half of the total state and local taxes, and for many farmers this is the most important of all taxes. Because of the importance and dimensions of these property taxes, it would appear that every attempt should be made to have an equitable base upon which to apply these taxes to the various Page 3 classes of property. Although state laws in general specify that all property is to be assessed at, or at a percentage of, the actual value it is consistently noted that lower valued properties are assessed at a higher proportion of their sale price than the properties of high value. This would indicate that assessors do not have true evaluations upon which to apply their tax. rates. This condition was pointed out in Iowa (114), where farms appraised at $2,500 or less, averaging 31,933, were assessed at almost their appraised value or $1,905, while holdings of over 810,000 in value, averaging $15,!47h, were assessed at but 57 percent of their appraised value or $8, 880. Based upon detailed study of the facts with reference to 1,5151; farm properties in South Carolina (1), the ratio of assessed to normal market value tended to decline with each increase in average normal market value. The range in this instance was from 31.3 percent on farms having an appraised normal market value of less than $1,000 and 28.7 percent on those appraised for between $1,000 and $2,000 to 18.8 percent of those appraised for $15,000 and above. This regressive tendency was also reported in Georgia (16), where properties which sold for less than $1,000 each were assessed for an average of 111;.9 percent of sale value whereas those which sold for $10,000 or more were assessed for an average of only 114.6 percent of sale value. In Montana (13), an analysis was made of more than 5,200 Page )4 voluntary sales of farm.land in 19 selected counties covering the period 1919 to 1935 inclusive. The average ratio of assessed value to sales value for the entire sample was found to be 1.09, showing an average overassessment for the period. However, the ratio varied considerably when applied to various value groupings. The ratio for the group valued at less than.$500 was 3.51, with the group valued $500 to $1,000 the ratio was 1.93 while for those sales of over $10,000 the ratio was 0.62. The tendency round in Nebraska (12) was also for assessment values to concentrate around an.average, rather than.vary with the sale values of the land. In this study the average assessed value per acre was $60, while the sale price averaged.$lh0, giving an assessment-sale ratio or h3. For the three years studied the assessmentésale ratio for tracts that were sold ranged from.22 to 159. The sale price per acre ranged from.about $h0 to $330. In contrast to this wide range, the assessed.va1ues varied only from $25 to $90 per acre. The result was that land or lower value tended to be overassessed compared to land of higher value. Theluichigan.assessor's manual states that all property is to be assessed on the basis of current cash value. In the determination of farmland value this manual gives two general groups of factors for consideration, each.of'which.primarily consists of production and location flactors. Ideally, the county equalization committee helps in setting land values and in developing a land value map for the entire county. The method of Page 5 assigning value by replacement cost is considered merely a refined comparative method and is included as a part of the comparative method recommended for appraising ferns. Sales and capitalization methods are considered to have disadvantages for most uses, and the assessor is left with his own judgment as his most inmortant tool in making assessments. Investors who purchase land are interested in the potential income from the land, and will bid more for that which offers greater possible return. Difficulties emerienced by loan agencies (2) during and follming the depression period of the 1930's emphasized the need for the most accurate values. Just as cropping systems and yields are considered in arriving at farmland values, the reverse of this procedure is also possible. Given farmland values or the soil groupings upon which these values have been prepared, farmers or nanagers from farm managemnt agencies can determine cropping systems yielding the greatest net returns on specific tracts (7). Yields can also be estimted for uses such as planning the acreage of a certain crop to produce for feeding operations or to provide an income to meet economic obligations. These values also provide a basis for comparing one group of soils with another. in early attempt to find a true basis upon which to evaluate land is that of Kellogg and Ableiter (8), in which groupings of soils based upon the natural landscape and defined principally by the climte, soil type, topography, and stoniness, were evaluated Page 6 as a whole. In California each soil type and phase was rated according to the Storie Index (15), so as to give their value for general agricultural purposes in relation to all other soils in the state. This rating was based solely on soil characteristics and conditions such as profile development, depth, texture, drainage, alkali, erosion, and fertility. The soils were first grouped into five "natural land types": (1) alluvial fans and terraces 3 (2) basins; (3) low terraces; 0;) high terraces; and (5) uplands. The natural land types were divided into subgroups according to soil characteristics. in index was then assigned to each soil according to its rating for use in tax assessment. In each of the two cases above, factors which affect the productive capacity of the land are of major importance in the evaluation or rating. This is also true in Nebraska (12), where soil productivity differences are considered the principal reason for differences in land values. In outlining the method proposed there, a soils nap is made, then a net income rating is prepared for each soil based on the cropping system, yields, and cost of production. By measuring the acreages of each soil on a tract, a weighted economic rating for the tract can be determined. From this weighted economic rating, an estinete of the value of the land can be made. Location of the tract with respect to distances to schools, market centers, hard surfaced roads and railroads is considered to be one of the minor factors in setting values, and Page 7 provision is made for adjustments of the estimated value to allow for unfavorable locations. These studies indicate that the values of farmland are based upon the ability of the farm to produce income. The most important influences on the values, as judged by the selling price of land for agricultural purposes, are closer related to the nature of the soils and the ways in which they are used. PROCEDURE Ch the basis of a review of literature, and considering conditions as they exist in Michigan, the following method of farm land evaluation essentially as used by Aandahl et a1, (12) is proposed. The essential steps of the method are: (1) (2) (3) (h) (5) (6) (7) (3) the soils represented in an area are assigned to soil management groups, the most common land use for each soil management group and slope class is determined, the acreage of each combination of soil management group, slope class and land use on each tract are measured, and recorded, the average per acre yield of each soil management group and slope class for each use is determined, the total value of the production per acre on each soil management group and slope class for each use is determined, the cost of production per acre for each land we on each soil management group and slope class is determined, the net incone per acre for each soil group, land use and slope class is determined by subtracting the values in step number 6 from those in step number 5, the income for each tract is determined by multiplying the net inconn per acre by the acreage of each combination of soil management group, slaps class and land use and totaling these results, Page 9 (9) the evaluation of the farmland on the tract is completed by capitalizing the net income per tract at a rate consistent with sale prices of farm‘land in the area, (10) the total value of the property is the sum of the land value, the stumpage value of any timber on the land and the building or improvement values. Page 10 Selection and Description of the Area Used to Test the Method To test the value or accuracy of this method, values of farmland could be computed using the soil management group method and this computed value then compared to results of other methods of evaluation, actual sales values, and with estimations of value by farm owners. Eaton County, Michigan was selected as an area in which to test the method. The availability of a soil survey of the county (18) and a current review of land values being nade by the Michigan State Tax Commission, together with the availability of farm- account records of several farms in the area led to the selection. Eaton County is located in the central part of the southern half of Michigan's lower peninsula. Dairy and general farming predominate in the area. The minor livestock enterprises are hogs, poultry and sheep. Most of the crops grown are the feed crops of hay, pasture, corn and oats. Wheat is the major cash crop, with white field beans and sugar beets being important on a few farms where soil conditions are favorable. The najor factors influencing the selection of enterprises in this area are the relatively long growing seasons, which range from lhO to 160 days, the predominance of sandy loam, silt loam and loam soils of medium to high fertility, and the good markets for whole milk. Approximately 500 sales of farmland over 35 acres in size took place in Eaton County during the period July 1, 1952 to June Page 11 30, 1957. From this group, farms were selected which were considered to represent valid sales of farm real estate to be used for farming purposes. Sales to relatives, to corporations and companies not engaged in farming operations, properties which were sold soon after purchase or transferred several times during the five-year period, or those having incomplete records and faulty descriptions were among those not considered in this study. Only tracts of 37.5 acres and larger in size were used in an effort to further insure that the sample represented valid sales for agricultural purposes. One-hundred twenty-five of this youp of farms were selected to insure study of as many soil management groups as possible, and to give a good area and value distribution in the county. The accompanying farm location map of Eaton County (Figure 1) shows the location and the distribution of farm.units used. Page 12 Field Survey' Field work consisted of checking the soil survey for accuracy and adequacy, the determination of land use on the sample farms, and recording;the amount and.kind of wood products occuring as stunpage. It was determined that the soil areas designated contained the soils as described, and were well within the limits set forth in the soil survey report. Many of the areas designated as a single soil series would under the present day system.of soil classification (21) be further separated into units containing less variation. However, when these units are combined into the soil management groups as outlined herein, practically all of these separations would be regrouped into the same units as are the soil series as outlined.later in this report. The various uses of the land were grouped into major land use groups, consisting of: (l) cropland, which includes rotational pasture; (2) permanent pasture; (3) woodland; and (h) undifferent- iated land use which included land used for farmsteads, roads, and drainage ditches. Each.of these were then plotted on the map of each farm, and designated by L, P, F, and.x.respectively. This was done by using aerial photographs as base maps, and outlining the various uses directly upon the farm.outline. In order to determine the amount of merchantable forest products on the land, the procedure as outlined in the Michigan State Taleanual (10), pages 229 and 230, was used as follows: First, the diameter range of the trees: including seedings, Page 13 saplings, pole timber, etc. was determined for the majority of the trees present. Second, the volume range was determined, that is, within the diameter range if the trees ran heavy to the large size the high volume range was used, or if the stand.ran mostly in the smaller size, the low volume range was used. Third, the stocking class of the woodland was determined. The stocking class was rated poor if 10 to 39 percent of the growing space was effectively utilized by trees, medium if no to 69 percent, and good when over 69 percent. From.this information and use of Table)(, the board feet per acre or the cords of pole timber per acre was determined. Sale prices and assessed valuations were needed of the farm. tracts as a basis for comparison with the values to be computed for the farmland. Sale prices were estimated by examination of the value of internal revenue stamps attached to records of the transfer of property according to the method outlined by Nybroten (11). These sale prices were then.adjusted to 1955 levels by multiplying the price by the farm.real estate index number for the year of the sale. The index number was determined by comparison of farm.real.estate values for the years 1952 through 195? relative to the value for 1955 (17). The index number as determined for the years concerned follows: Page 11; 1311: Index No. 1952 1.08 1953 1.06 19514 1.03 1955 1.00 1956 .91: 195 7 .86 Example: (1) a 1953 sale at $25,000 would be 325,000 x 1.06 = $26,500 at 1955 prices. (2) a 1957 sale at $25,000 would be $25,000 I .86 = $21,500. Assessed valuations were taken from the records of the Eaton County assessor. Page 15 Soil Management Groups Soil management groups are basic interpretive groupings based on similar soil properties and similar adaptations or management requirements. Examples of soil properties most generally considered include the texture of the profile, reaction of the profile, depth of profile, and natural drainage. Sane of these groups are subdivided into classes of slope and degree of erosion. Adaptations or management requirements pertain to specific purposes as forestry planting, irrigation design, drainage, crop rotations, and fertilizer or lime recommendations. In this study the soil management groups are used as a basis for evaluation of farmland. This grouping of soils provides for natural combinations of many soils into a convenient number of units which will still express the main differences in production and so be useful as the basis of land evaluation. In the event that more specific information pertaining to the yields and cost of production for the individual soil series or soil types should becom available, then these units probably would become the better basis. However, for convenience and practicability of use, the more detailed units nay still be combined into such groups as used here. In the developmnt of a system of nomenclature or identification of these soil management groups a combination of letters and numbers is used. The numbers indicate the relative coarseness of the mineral materials from which the soils were Page 16 formed; from.0 for the finest texture clays, to 5 for coarsest texture sands. The small letter following this number indicates the natural drainage under which the mineral soil developed, "a" for the best drained, “b” for imperfectly drained, and “c” for the most poorly drained conditions. .A combination of two small letters, such as 'bc', indicates a range in natural drainage conditions from.imperfectly (b) to poorly drained (c). ‘Where a small letter precedes a number or capital letter, it has a different meaning. Thus, a small 'a' preceding a capital M (for mucks) represents very acid soils and 'b' stands for soils well supplied with bases and less acid in reaction. .l small 'h' preceding a number or capital letter indicates that the subsoils of that group are hardened or compacted so as to interfere with root penetration and water movement. The capital letters indicate other soil characteristics quite important to their use and may be used with or without the numbers. For example, G is for gravelly or stony soils, L is for lowlands subject to seasonal overflow; Miis for mucks and pests; and.R is for rocky soils, where bedrock is close to the surface. Thus, the L3a soil management group includes lowland soils developed from.sandy loam.parent materials, that were formed under well drained conditions. The 2b soil management group includes upland mineral soils formed from.loam.to silt loam.parent materials, under imperfectly drained conditions. Page 17 Following is a list of the soil series of Baton County with the abbreviated soil series designation as reported in the county soil survey report, and the soil mnagement groups into which they have been combined on the basis of the soil characteristics as they occur in the Eaton County Soil Survey Report (18). Soil Management Map Group Symbols Soil 23. H]. new loan Ms Miami silt loam H1 Hillsdale loam 2b Cl Conover loam Cr Crosby loam 2c Br Brookston loam Bc Brookston clay loam 3: Ha Hiledale sandy loam Bm Bronson loam B1 Bellefontaine loam Bs Bellefontaine sandy loam F1 Fox loam F Fox sandy loam W Warsaw loam Ts Tuscola silt loam Pl Parma loam 3b Bo Brady loam 3c Gd Gilford loam ha 01 Oshtemo loamy sand (except areas south and northeast of Eaton Rapids) Of Colona loamy fine sand B Berrien loamy sand Bf Berrien fine sandy loam 08 Ottawa loamy fine sand hc Mm Maumee loam Soil Management Group 53. all WP Symbols 01 Gf G1 EEB GP Page 18 Soil Oshtemo loam sand (in areas 5. and N.E. of Baton Rapids) Genessee fine sandy loam Griffin loam Kerston muck Carlisle muck Houghton muck Rifle peat Greenwood peat The well drained soil management groups were subdivided on the basis of slope. Those areas having slopes lessthan 6 percent were placed in slope class A-B, and those areas having slopes between 6 and 18 percent, in slope class C-D. Areas in Eaton County of poorly-drained and imperfe ctly—drained soils having slope gradients steeper than 6 percent were considered too small to have any important effect upon the outcome of this study, and when they did occur, were placed in the next lower slope class. Page 19 Land Use on the Soil management Groups The estimation of the percentages of each soil management group used for cropland, permanent pasture, woodland, and other uses are based upon Observations on the individual tracts. Specific estimates from several other sources were compared with these measurements on approximately 15,000 acres in.Eaton County. Other sources of information included census data; the land use study made in Odessa township in.Ionia County, Michigan; the land use study made of.Almont township in Lapeer County, Michigan; and estimates prepared for Oakland County, Michigan. The estimated proportions of slope classes of each soil management group for each of the four groups of land use based on the above data are shown in Table 1. In the determination of the percentages of cropland occupied by different crops, emphasis was placed upon average harvested acreage figures for the various crops as reported in the Michigan Agricultural Statistics (9) for the period 1952 to 1956 inclusive. In this statistical report, the acreage of each crop is reported annually. By finding the average acreage of each crop and dividing this by the total acreage of cropland, an average per- centage of the cropland occupied by each crop is obtained. Adjustments of these average figures for all croplands must then be made for each specific soil management group and slope class. These adjustments were based on studies of land use in Odessa township of Ionia County, in.Almont township of Lapeer County, and Page 20 also upon specific estimates prepared for Oakland County, Michigan which were based upon data of the United States Census of Agriculture (20), Michigan Agricultural Statistics, and land use studies made in four southern Michigan townships in 19524. Table II lists the estimated proportions of cropland occupied by the different crops on different soil groups by slope classes in Eaton County. In the preparation of Table II, acreages of crops occupying less than 2 percent of the cropland total were combined with acreages of crops having comparable land and management requirements, production costs, and net returns. For example, acreages of beans were combined with those of corn and acreages of barley with those of oats. Page 21 measurement of.Acreages The individual sales tracts were first drawn to scale on.a sheet of paper. The information from the soil survey map was then transferred to this farm.outline. Next, the land use information from.the aerial photographs was transferred to the farm.outline -with the soil survey information. From this farm outline, measurements of each land.use on each soil.napping unit were made. Several methods of measuring were tried including use of the planimeter, the electric grid counter, and the counting of squares on a small grid overlay. The methods were comparatively equal for accuracy, but the latter method.proved to be the more rapid because of small areas which predominated. The accompanying farm.outline (Figure 2) shows the soils and land use on a farm together with the chart containing acreages of each land use for each mapping unit and illustrates the application of the method used in measuring each farm. Page 22 Estimation of Crop Yield of the Soil management Groups by Slope Classes The determination of average yield for each of the soil groups by slope classes consisted essentially of determination of average yields of each crop for the county or area as a whole, from census data, and then estimating the yield for individual soil groups and slope classes based on their relative properties affecting production to arrive at specific estimated yields for the various soils. The Clinton County, Michigan.Soil Survey Report (19) contains a productivity rating table that has withstood the test of use since publication of the report in l9h0. This county corners Eaton County on the northeast, contains most of the same soils, and has very similar yields of all crops which.are common to each. Thus, with slight adjustment of this table on the basis of differences of soils as they occur in Eaton County and on the basis of the grouping of these soils into soil management groups, a table was developed giving a productivity index for eaoh of the soil management groups. The yields of crops which‘were used as standards of 100 in the Clinton County report required upward.adjustment in most cases because of the general increase in average yields from.the time 'when the report was prepared to the 1952 to 1956 period. This was done by comparing average yields during each of the periods for the United States, for the State of Michigan, and for the counties Page 23 Clinton and Eaton. The averagesthat are used herein as standards of 100 in computing the average yield of crops on each soil management group are shown below for the principal crops of Eaton County and compared to the average yield given in.the l9h0 Clinton County report. Rye, beans, and alfalfa were not changed as they were considered to have been set too high originally. Unit Average per Acre Average per Acre CROP (bu.) Yield-1910 report yield 1952-56 Corn ' 50 70 Wheat " 25 to Oats " 50 55 Barley " no '45 Rye " 25 25 Beans " 25 25 Potatoes " 200 1400 Corn (silage) (tons) 12 18 Timothy and Clover Hay " 2 2.5 Red Clover Bay a 2 3 Alfalfa Hay " h 1; Sugar Beets " 12 16 The productivity rating times the average per acre yield which is used as the standard gives the estimated yield per acre for the respective soil management group. Adjustment of this per acre yield is then necessary for the areas of those soil management groups which occur on steeper slopes. This adjustment was made on the basis that yield is generally reduced in direct relation to the amount of topsoil lost (22), and that the effect of erosion in Eaton County is less on coarser textured soils and as vegetative cover becomes more effective in stopping erosion. Final adjustments were nade of those yields on the basis of specific yields as recorded in Michigan State Agricultural Experiment Page 2h Station records on experiment fields on similar soils and by estimates of agricultural specialists in southern Michigan. The estimated average per acre yields of the principal crops of Eaton County for each of the soil management groups and slope classes is given in Table III. Yields of rotational and permanent pasture were estimted on the basis of the number of animal unit days of forage produced per acre on each soil mnagement group and slope class. These are reported in Table IV. The average annual increment of each group of woodland species on each soil management group on which it occurs was estimated both as board feet of saw timber and cords of pole timber, and is reported in Table II. Page 25 Estimated Net Income Per Acre from Alternative Uses of Land Net income was determined for the respective soil management groups and slope classes by multiplying the yield times the value of the yield and subtracting the cost of production as adjusted for the various soil units on the basis of variable costs due to such operations as seeding, clipping, and fertilizer applications. . Prices of products used in computing the value of production and the net income are listed in Table V. The estimated costs of production of the various crops are shown in Tables VI and VII. The common custom prices as reported for Michigan (9) for the common Operations and materials used in the production of each crop are given as adjusted for local conditions. These adjustments were based upon census data, farm account records, economic surveys and the judgment and observa- tions of agricultural economists. Some costs, such as plowing, were assumed to be relatively stable under all conditions. For other operations such as harvesting, though some parts of the operation as the rate for wheat combining is quite stable, the cost was considered to vary almost directly with the yield of the crops due to such factors as additional cost of hauling and storage of a larger yield. Fertilizer costs were based on census data for the total amounts used, and scaled up or down for individual soils according to the proportions of the various crops grown and the yields of those crops. Page 26 The combimtion of the three basic values of crop yields, values of raw plant products and crop production costs, into estimated net incomes expected from each crop on the slope classes on each soil group is illustrated in Table VIII for cropland, which includes rotational pasture. The estimated net income for the various crops are then combined for each soil group and slope class in proportion to the percentages of cropland occupied by the different crops, to give a weighted average net income for all cropland, which is shown in Table II. The estimated net incomes per acre from permanent pasture and woodland are also listed in Table II for the slope classes of the soil management groups. Page 27 Net Incom for Woodland The procedure in determining the net income from woodland is similar to that for cropland. In Eaton County there are four principal groups of woodland species represented. These groups, with their map symbols, and the species of trees which predominate in each group are as follows: Map Group Predominant Symbol Name Species LH Lowland Hardwoods Elm, ash, red maple NH Northern Hardwoods Sugar maple, beech, yellow birch, basswood OH (bk-Hi ckory Oak, hickory AP Aspen—Birch Aspen, white birch These are comparable to the individual crops on cropland. The average annual increment or each woodland species on each soil management group on which it occurs was estimated both as board feet of saw timber and cords of pole timber, Table II. The value of this estimated yield was determined using the stumpage prices as listed in Table V. Net income for the woodland Species on each soil management group, Table XII, was determined by weighing the values of the annual increment produced as saw timber and pole timber according to their proportions on each group, Table XIII. The weighted average net income for all wood- land on each soil management group was determined by weighing the net income by species, according to the proportion of each species Page 28 on each soil management group, Table XIV, and this is shown in Table IV. Page 29 Determination of Net Income for Various Tracts The total computed net income per tract was determined by multiplying the net income per acre for each of the major land uses, soil management groups and slope classes (Table IX) by the acreage of these respective units on the tract. The total of these figures gives the expected net income for the tract. Page 30 Capitalization of Net Income To change the estimated average net income of a tract to farmland value, this net income may be capitalized at a single rate, or as was done in this study the areas of land having widely different uses and net returns, and consequently widely different values may be capitalized at different rates. As a test to select a rate of capitalization to apply to the computed net income in computing land value, the computed net income was compared with sale prices of farmland sold, and with estimates made of farmland value by farmers. These comparisons are listed in Table XVI and XVII, and are shown graphically in Figures 5 and #. Farms were selected in Table IVI which had no improvements, or with very low value improvements, and with no woodland or with low acreages of woodland which had low stumpage value of timber on the land. Estimates of farmland value were made by farmers who have been keeping farm account records in cooperation with the Agricultural Economics Department of Michigan State University. The computed net income averaged 14.01 percent of the sale price of the farmland on the tracts in Table XVI. When compared with farmers' estimates of farmland value on farm account farms, the computed values averaged 13.8 percent of the estimated values, Table XVII. The cropland and permanent pasture were capitalized at approximately 1% percent (1#.29%), based on the comparisons previously mentioned. This capitalization rate was also Page 31 consistent with similar findings nude in a study of net income and land values in Arenac County, Michigan (5). The estimated net return from woodland was capitalized at 5 percent in Arenac County. However, because this rate gave values which were considered too low for the woodland, and as the woodland in Eaton County produces products of higher value per acre than that of Al‘enac County, the rate of approximately 3 percent (3.03%) was used in Eaton County. Page 32 Total Value The total computed value of the farm property is the sum of the land value, the smmpage value of any timber on the land, and the building or improvement values. The methods of arriving at the land value and timber value have been described. The value of the buildings or improvements cited herein has been that assigned to them in the course of the equalization studies made by the Michigan State Tax Comission in Eaton County. RESULTS The purpose of this study was to investigate a method of arriving at equitable evaluations of farm lands. The method has been outlined.and.used to make evaluations on.a number of farms in Eaton County, Michigan. Tests of the accuracy of the method proposed include comparisons of the values obtained with: (1) another method of land evaluation, and (2) farmers' estimtes of'land values. The computed Land value was compared with the Michigan State Tax Commission's appraised.land.va1ue. Results of this test are shown in the chart of Table XVIII, and graphically in Figure 7. There was a wide variation in values obtained, with the computed land value ranging from.65 percent to 170 percent and.averaging 112 percent of the Commission's appraised value. A.correlation coefficient of .921 was determined for this comparison of computed and.appraised values. To compare the computed farmland values with farmers' estimates of the value of the land, values were taken from farm account records kept in cooperation with the Michigan State Universitynigricultural.Economics department. These values were the farmers' estimates of the value of their land (improvements not included), and were used here as an example of comparison of land value with the computed land value. The results of this comparison are shown in Table XIX. These data show a wide variation.between many of the computed and the farmer estimated land values, and also Page 3b shows the computed land value to average 97 percent of the estimated land value in this test. Another test made was to compare the sale price of the farms with the county assessed valuations. Results of this test are shown in Figure 8 and in Table XXI, where the wide range which occurred in the assessed value-sale value percentages for the various value groups is shown. The assessed value averaged h9 percent of the sale price for the 99 farms compared. is the assessed value appeared to be quite low, it was further compared with the farm owners' estimtes of the value of their farms. The results of the test in which the assessed values averaged 36.5 percent of the estimated farm value, are shown in Table XXII by value groups and graphically in Figure 3. Using the computed value of farmland obtained by the method as outlined herein, a comparison was made with sale price of the land. Sale price in this test was calculated by subtracting the appraised value of the improvements, which was determined by the Michigan State Tax Commission, from the price for which the farm sold. As an average for the 23 farms tested, the computed land value of the farms averaged 170 percent of the calculated sale price of the land (Table DC). This is obviously a poor method for arriving at the calculated value of the land as indicated by the wide variations when compared to the computed values that agree well with actual sale values of land, appraisers' values of the land and farmers' estimations of farmland values. Page 35 To determine the accuracy of the appraised farm values, the farm values as determined by the Michigan State Tax Commission's appraisal were compared with the farm sale values. These comparisons are listed in Table mm, and are shown graphically in Figure 6. In this case, the appraised values averaged 1214 percent of the sale values. is the Commission's land values, while about 10% lower, agree well with the computed land values, it appears that the Commission's values of buildings are much too high on the average. Page 36 Discussion .a method by which 'Soil management Groups' and related information on their use, their productivities and production costs can be used to arrive at equitable land evaluations has been presented. It was used to make evaluations of a number of farms in Eaton County, Michigan. Tests were made to determine the accuracy of these evaluations. The computed land values using the above method were quite close to the appraised.1and.va1ues as determined.by the Michigan State Tax Commission. The computed land value averaged 112 percent of the appraised.va1ues, with.a correlation coefficient of .921 between the two values. This means that 85 percent of the variation in the computed land value can be associated with a variation in the appraised land value. The computed farmland values averaged 97 percent of the land values as estimated by a group of farmers and.were about equal to the sale values of bare lands. These three values averaged very close together, though this close relation could have been due to the manner in which the capitalization rate for the net income was determined. tittempts to compare the computed farmland values and total computed farm values with the sale prices of the land and of the farms respectively, indicated the probable overvaluation of the improvements in relation to the land values. ‘A possible explanation for this overvaluation of improvements may be that with Page 37 the general trend toward larger sized farm units, many of these improvements are going out of use and.have much less influence in determining the price of the farm unit than they would during a period of time when their use would be continuing or in an area where the size of farm.units is not increasing. Changes in the types of farming operations with time, as dairying to cash crops, could also leave many improvements on a farm which would contribute little to the new operation. .Assessed value-sale value ratios of the farm.units in this area was typical of conditions as found in other areas as mentioned earlier in the review of literature. The general trend was that farm units of low value were assessed at values near to or higher than their market values, while units of higher value were assessed.at a much lower percentage of their sale values. The comparison of the farmers' estimates of value of their farms with assessment values confirmed this trend for farms of higher value groups. Several reasons or explanations of these inequalities in assessments are as follows: (1) absence of an objective land evaluation procedure for relating reliable sales or other data to assessments of unsold properties, (2) influence of people who own the more valuable units of land, or (3) the reluctance of assessors to appraise large properties in proportion to their market values. Page 38 These emphasize the need for more objective assessment procedures to arrive at more equitable taxes. In the determinations of the accuracy of the various determined land values, it was shown that the Michigan State Tax Commission's appraisals avoid the above mentioned bias of undervaluing the more valuable properties and were closer to the actual sales values. A close relationship between the computed land values by the use of soil management groups and related data and the tax commission's appraised land value has been shown. It is also mentioned that adjustments of the computed farmland values may need to be made because of local factors which influence value, as location of the tract, flooding or overflow hazards, or poor soil drainage. To correct for a factor such as reduction of yield due to the effect of poor drainage or flooding, the average annual proportion of each crop that is lost is multiplied by the propor- tion of the area of that crop on.the land, the average yield of that crop on the particular soil management group and slope class and the average price per unit of the crop, after subtracting the harvesting cost per unit, to give the amount to deduct for that crop from the expected net crop income on that particular soil unit. The method of arriving at farmland valuations as previously outlined 'would be applicable and best suited to an area such as a 'Type of Farming.Area' (6). This is an area of relatively uniform.agricul- tural enterprises. Therefore, the price of land is determined by competition for an average use. In the use of this method in such Page 39 an area, periodic checks should be made on the land use. The intervals of time at which to make these checks is dependent upon changes in cropping system because of such factors as changing economic trends, technological trends or advances, soil changes and/or adaptations of cropping system to fit the soil, or acreage controls. When the average cropping system or land pattern for an area is changed, or specialized crops become part of the normal operation of a tract as indicated by census data, then new calculations of values for the area or tract should be made using the net income from the new uses on the soils represented. The farmland valuations by the 'Soil Management Group' method could provide an objective basis for all appraisals of farmlands. Appraisals based on this method would also be useful to people who wish to sell their property and to others who have purchases of property as their concern. People who sell farmland are usually primarily interested in having facts available which point out the better characteristics of their property. These include not only the value for a definite use, but also the possibilities for, and values of the property under several systems of management, so that the possible market may be broadened to include more buyers to compete for the property. These data are readily available, or can be easily determined after the values have been computed by the method as outlined. A purchaser of farmland usually is primarily concerned about the income that can be expected from the kind of management that he plans to apply to Page to the tract. By application of the principles of the method as outlined, the net income which could be expected from a particular type of management can be computed. Credit agencies could use the method.as'well as individuals to determine the value of a tract as security for loans of all types. The loans could then be made on the basis or the income the tract was actually able to produce. By application or the principles of the soil management group method, farm.managers or farm.management agencies could determine the relative economic benefits from.different crops on the same soils and on different 80113. For example, it is shown in Table VIII (which gives the estimated net income per acre from alternate uses of cropland.by soil management groups and slope classes in Baton County) that for soil management group 2a on slopes of six to twelve percent, the production ofhalralfa hay will give the highest net income. From the same table it is seen that the production of corn gives the highest net income on the soils of group 2b, and that on the soils of group 2c the highest net income is obtained by production of corn and the second most profitable crop is wheat. It is also shown that the highest net income from.the production of corn is Obtained on the soils of groups 2c, 2b, and 3b, in.decreasing order. Highest net incomes from the production of wheat is obtained on the soils of groups 2b, 2c, and 3b, in decreasing order. Some crops are actually grown at a loss to the operator on some soils. Page hl It is shown in Table II that while much of the area of some soil groups may be used for cropland, this is done with the production of very low income or even.at a cost to the operator, and that higher net incomes could be expected if the soils were used for permanent pasture or woodland. Thus, it is seen that the farm.manager can use this type of information to determine the relative economic benefits from various cropping systems on the soils of a specific tract. Page hZ Additional Research Needs The accuracy of the method as outlined for evaluation of farmland is directly dependent upon the accuracy of the data used in the various computations. Therefore, the description of the soil nanagement for each soil, along with yield, cost, and price estimates should be as complete as possible. Accurate information concerning the percentages of the different crops grown and of the land use on each soil are needed, and should be revised as changes occur in an area. Accurate informtion concerning crop sequences, erosion-control measures, and application of fertilizer should be known as they effect total yield, cost of production, and there- fore net income. Additional data on yields, especially specific yields of the various crops on individual soils, are especially needed. While average or fixed costs for farms or for operations in general are usually well known, specific information concerning variable costs as they apply to individual soils is needed. These variable costs include such items as additional cost of drainage on some soils, variation in cost of preparation of seedbeds and other tillage operations, and costs of harvesting and storage of increased yields. Prices of products which apply to the specific areas under consideration are needed. For examle, in the area to be considered, not only the prices of products in the mrket centers within the area, but also the prices at any other location Page LO available to the operator should be considered. Location of a tract is often reported to be an important factor in determining the value. In Nebraska (12), distances to market centers, schools, hard surfaced roads, and railroads were considered.to influence the cost of operation.and living because of increased costs of transportation.and amounts of time required to reach these locations or services from outlying areas. Such distance can influence and often regulate the type of farming which can‘be carried out on a tract. The location in respect to the type of land or of farming which surrounds the tract is often important in setting value. For example, the values of individual small tracts of very good land which are widely distributed in an area of much.poorer quality land are usually brought down because of the association. The way of life or habits of people in an area often influence land values through the selection of a type of farming 'which may or may not be most profitable in the area.. To illustrate this point, the people of an.area may have chosen a dairy type of agriculture, and continue to operate on that basis even though the land is well suited to other types, such.as production of cash crops, and'would give higher profits under that use. .Additional research is needed to more accurately evaluate the influence of location on the value of farmland. The rate at which to capitalize the net income is one of the most important factors in setting values by the method as outlined. Comparisons of the relationship between the computed net income and Page hh sale price on.a large number of farm.tracts in each area would be very desirable. 'While the author believes this comparison provides a true basis for the capitalization rate, further investigation may provide refinements in the method. Comparisons made to show the accuracy of the method of land evaluation pointed out the need for a reliable method of appraisal of farm improvements. Studies which show the use which is made of these improvements after a sale may help in the determination of more accurate appraised values. CON CLUSI 0113 On the'basis of the results of this study the following conclusions seem warranted: (l) the computed land values as determined by the soil management group method compares favorably with both the Michigan.State Tax Commission's appraised land values and with farmers' estimates of the value of their land, (2) the use of soil maps can be of aid to township or county assessors in comparing farms, (3) the use of these values based upon the soils and land use 'would tend to remove bias in relative overtaxation of low value farms, (h) the soil management group method of land evaluation could provide a base for all appraisals of farmland, including those for sale, purchase or condemnation, (S) the soil management group method of land.evaluation could be used.by management to determine the relative economic benefits from.various cropping systems on the soils of a specific tract. l. 2. 3. ll. 0 S. 6. 7. BI BLI OGRAPH‘I Aull, G. H., and Riley, Ernest. Some Inequalities _i_1_1_ the Assessment of Farm Real Estate in South Carolina. South Carolina Agricultural Experiment Station Bulletin 313, 1938. Gaddis, P. L. m m in 31.92.11 and Practice. Paper presented at a conference for land appraisers held at the College of Agriculture, University of Illinois, June 15-17, 19h8. Heneberry, William H. Propertz E M E selected townships, @4252 Unpublished manuscript, Michigan State University. 1956. Heneberry, William H. Pmpgrtz E m 22 £32 and nonfarm propertz 21.30}; 22133. Unpublished manuscript Michigan State University. 1956. Heneben'y, William H. .U_S_e_ g; §_o_}_l_ £25 £03 m 3‘3 Assessment Procedure £95 £833 Propertl in £39219. Countz, Michigg n. Unpublished manuscript, Michigan State University. 1955. Hill, Elton 13., and mwby, Russell G. 22235 93 Farrflg _i_n_ Michigan. Michigan State College and Agricultural Experiment Station Special Bulletin 206. September 1951;. Soil 2223 Associations. Paper presented at a conference for land appraisers held at the College of Agriculture, University of Illinois, June 15-17, 19h8. 8. 9. 10. ll. 12. 13. l4. 15. Page 47 Kellogg, C. E. and Ableiter, K. J. A M g; Rural Land Classification. United States Department of Agriculture, Technical Bulletin 4-69. Michigan Department of Agriculture. Michigan Agricultural Statistics. Michigan Department of Agriculture, Lansing, Michigan 1952-1957. Michigan State Tax Commission. Assessor's Manual. Michigan State Tax Commission, Lansing, Michigan 1955. Nybroten, Norman. Estimating gash Considerations in R_e_al_ Mg Transfers from Internal Revenue m. Journal of Farm Economics. Vol. 30, 558-561. Ottoson, H. W., Aandahl, A. R., Kristjanson, L. B., & Burbank, L., Valuation g; .F_a_r_m Land £93 23:; Assessment. Nebraska Agricultural Experiment Station, Bulletin 427. 1954. Renne, R. R., and Lord, H. H. Assessment 9}: Montana lag Lang. Montana State College Agricultural Ebcperiment Station Bulletin 548. Spaulding, Lloyd J. Farm taxes and the cost 9; M Services in relation _1_:_<_>_ land resources in ES. ggld County, Iowa. Iowa Agricultural Experiment Station, Research Bulletin 288. 1941. Storie, R. Earl and Weir, Walter W. 1113 Egg 9; _S_9_il_ M_gp_§ £9; Assessment Purposes _i_n_ California. Soil Science Society of America Proceedings. Volume 7, #16418. llll'll. 16. 17. 18. 19. 20. 21. 22. Page h8 Taylor, C. C. .1353 323}. m Assessment _i_n_ Georg. Georgia Agricultural Experiment Station Bulletin N.S. 22. 1956. United States Department of Agriculture. AJincultural Statistics 1251. United States Government Printing Office. Washington 1958. United States Department of Agriculture. 'S_gi_}_ m 93 m MI, Michigan. Bureau of Chemistry and Soils, in cooperation with the Michigan Agricultural Experiment Station. Series 1930, No. 10. United States Department of Agriculture. _S_9_i_._1 m _J‘_."_ Clinton Countz, mchign. Bureau of Plant Industry in cooperation with the Michigan Agricultural Experiment Station. Series 1936, No. 12. United States Department of Commerce. £25}; 93113 9; Agriculture - M l. 3.11 6 -- MicEgan Counties and §t_a_t_e_ Economic A_I_'g_a_§. Bureau of the Census. Washington 1956. Whiteside, E. P., Schneider, I. F., Engberg, C. A. Taxonomic Classification 23 Michigan S3295. Michigan Agricultural Experiment Station and United States Department of Agriculture. December 1955. Zingg, Austin W. m and M 2;: {Eng Slog Ag It Affects Soil _I£_s_g in M. Agricultural Engineering, Volume 21. February 19140. Page ’19 Table I. Estimated Proportions of Slope Classes of Each Soil Management Group Used for Cropland, Permanent Pasture, Woodland and Other Uses in Baton County. 511 fixing Permanent wristeads 3 Slope Classes Cropland Pasture Woodland etc.) 2a A-B .87 .05 .03 .05 2a C-D .75 .12 .08 .05 2b A-B .80 .09 .06 .05 2c A-B .70 .17 .08 .05 3. 1—3 .82 .09 .011 .05 3a c-n .65 .20 .10 .05 3b 1-3 .78 .12 .05 .05 3c A-B .65 .18 .12 .05 ha A-B .75 .111 .06 .05 ha c-n .50 .25 .20 .05 he A-B .60 .20 .15 .05 5a 1—3 .65 .22 .08 .05 Sa (H) .30 .30 .35 .05 L38 A—B .39 .39 .17 .05 13-11:: A-B .11 .5h .30 .05 13M A-B .211 oh? 021!» 005 Page 50 Table II. Estimated Proportions of Cropland Occupied by Different Crops on the Soil Management Groups by Slope Classes in Eaton County. S351— Management Groups and Alfalfa Other Rotational Slope Classes Corn Wheat Oats Bay Bay Pasture 23 A-B .28 .15 .16 .20 015 0% 23 6-D .25 .16 .17 .20 016 0% 2b A-B .36 .15 .13 .16 .111 .06 2c A-B .116 .16 .10 .08 .12 .08 33 A-B .29 .16 .16 .18 012 009 33 0.1) .20 .16 .18 .20 .111 .12 3b A-B .33 .18 01,4 016 0111 .05 30 A'B 039 018 .12 .12 .11], .05 ha A-B .28 .16 .18 .18 .12 .08 ha- C-D .19 .17 .19 .17 .15 .13 ’40 A‘B .30 .114 .16 020 015 .05 58 A-B .21.} .16 .19 .18 .11], .09 5a c-n .18 .17 .19 .18 .16 .12 L33 A‘B .36 .16 .124 .111 .15 .05 1341c A-B .33 .13 .15 .17 .16 .06 bM A-B .2 5 .12 .08 .111 .26 .15 Page 51 Table III. Estimated Average Per Acre Yields of the Principal Crops of Eaton County by Soil mnagement Groups and Slope Classes. 3—6—11 Management Alfalfa Other Groups and Corn Wheat Oats Hay Hay Slope Classes (bu. ) (bu. ) (bu. ) (tons) (tons) 2a A-B h? 28 38 2.6 1.8 20 A-B' 63 31 51; 2.1; 2.1 3a A-B hl 26 35 2 .0 1.7 33 C-D 3h 22 30 1.8 105 3b A-B 53 30 ML 2.6 2.2 30 A-B 56 28 38 2 oh 2.]. ha (H) 23 1h 18 1.11 1.1 521 A-B 21 12 17 1.0 0.75 I30 A-B 112 20 36 2 .h 2 .10 L3-hc A-B (110)» (18) (30) (2.2) 1.50 bM A-B 1:9 (26) (to) 2.0 1.3 ( )«n- These crops are not extensively grown on these soils, but yields are estimated for use in computing expected net income. Page 52 Table IV. Estimated Per Acre Yield of’Rotational and Permanent Pasture by Soil management Groups and.Slope Classes. SET management Rotational Permanent Groups and Pasture Pasture Slope Classes (Cow-days) (Cow—days) 2a A-B 165 90 2a can 1245 80 2b .A-B 170 100 2c A-B 170 110 3a A-B 1245 80 3a 04.1 3.30 70 3b tA-B 160 90 3c A-B 165 100 ha A-B 80 60 ha 041 70 50 he A-B 120 80 5a A—B 55 35 5a 0-0 55 35 13c .AéB th 88 IB-tc.A-B 131 8h bM A-B 160 90 Page 53 Table V. Prices of Products Used in Computing Net Income. Corn $ 1.25 per bushel Wheat 1.96 " " Cats .61; " " Alfalfa hay 21.00 " ton Other hay 17.00 " ton Pasture .088 " cow day Wood Products, stumpage values. Northern hardwoods, lumber 12.00 per 1.1. bd..f.‘t. Northern hardwoods, pulpwood 1.00 per cord Oak-Hickory, lumber 9.00 per M. bd.ft. Oak-Hickory, pulpwood 1.00 per cord LOWJand Hardwoods, lumber 8.50 per 31. bd.ft. Lowland hardwoods, pulprrood 1.00 per cord Aspen, pulpwood 1.00 per cord Page 51; Table VI. Average Pr0duction Costs for Common Crops in Eaton County. Expense Per Acre of Land in Corn Wheat Oats Yield 15 bushels 28 bushels 38 bushels Labor and mchinery: Plowing, fitting, planting and cultivating $13.50 $11.00 $ 7.75 Harvesting, loading, hauling and storing 7.50 7.08 6.80 Fertilizer 70,41 6.37 14.30 Seed and crop expense 2.50 5.50 2.00 Overhead 3.09 3.00 2.08 TOtal $3hooo $33.05 $22.93 Page 55 Table VII. Average Production Costs for Hay and Pasture in Baton County. Expense Per Acre of Land in Alfalfa Rotation Permanent H32 Other Hag Pasture Pasture YiBld 2.0 tons 1.6 tons 130 days 100 days Labor and Machinery, Planing, fitting planting and Harvesting, loading, hauling and storing 15.35 12.31 Fertilizer .75 .50 .50 .30 Seed and crop expense 2.50 2.25 2.00 .140 overhfiad 2.06 1.71 1.20 1.01]. Total $22.66 $13.77 3 5.50 a. 2.10 Page 56 Table VIII. Estimated Net Income Per Acre from Alternative Uses of Cropland, in Eaton County by Soil Management Groups and Slope Classes. 5E1 Managemzrb Groups and Alfalfa Other Rotation Slope Classes Corn Wheat Oats Hay Hay Pasture 2a. A-B $25.87 $21.61. $1.23 $27.11. $10.33 $ 8.h8 2a C—D 15.68 111.53 - .81; 21.911 8.67 6.81 21) A-B 3h.75 27.07 6.69 29.73 111.33 8.90 2c A-B 39.51 26.68 7.65 211.53 12.55 8.90 33 A-B 13.55 19.57 0&3 19.311 9.57 6-31 33 C-D 11.78 13097 -1032 170M 707,4 5089 3b A-B 29.80 25.00 3.68 27.111 13.83 8.06 30 A‘B 32077 21083 1.39 2,4053 12.55 6081 ha- A‘3 7013 3 089 '14003 13 055 5069 2 0 ’49 ha (H) 2.53 0.60 -6.58 12.23 h.99 1.66 he A-B 190524 160111 4.26 20.65 10.’17 5.06 58. A"B "' 5065 - 6.116 “-7.06 5016 0.75 101,4 53 0".) " 9.61 "' 8.111 .8050 5.16 0.75 10111 L3c A-B 19.51. 10.61 0.91 2h.53 12.55 5.9h 1.3-1.6 A-B 17.56 7.32 ~1.32 21.914 7.71: 5.50 bM A-B 25.87 19.317 2.19 19.31; 5.9!. 8.06 Page 57 Table II. Estimated Net Income Per Acre from Alternative Uses of Land, in Eaton County. soil Managemnt Weighted Weighted Groups and Average Permanent Average all Slope Classes all Cropland Pasture Woodland 2a A-B $18.18 3 6.10 .92 2b A-B 211. 73 6. 7O . 98 20 A-B 270111 7053 .61 38. A-B 13 o 82 5 02,4 0 91 3a 0‘0 9 0 73 he 70 091 3b A-B 21.56 6010 o 92 30 A-B 22.01 6070 .68 ha. A-B 5.22 3 .93 . 73 11a C-D 2.110 3.08 .73 he A.B 11.70 502,4 .66 58 A-B " 3 .62 lo 88 061], 5a C-D - 3 .55 1. 88 .614 L30 A-B 1’4057 5097 .66 LB-hc A-B 11.88 5.60 .66 bit A-B 111.141. 6.10 .3h Page 58 Table X. Volume Per Acre of Forest Products by Stand Size and Stocking Class. Diameter Volume Stockigg Class range range Good medium Poor Inches bd.ft. cords bd.ft. cords bd.ft. cords 0- l ....... 0 0 0 O 0 O Lam... 0 0 O 0 0 0 1- 5 Average 0 2.5 O 2.2 O 1.5 High... 0 2.9 0 2.8 0 2.0 W000. 700 13.0 500 7.0 200 3.0 5- 9 .Average 1,h00 20.0 1,000 12.1 990 5.0 High... 1,500 211.0 1,500 12.9 1,2m 7.0 LOU}... 6,000 18.0 3,000 13.0 1,500 5.0 9-15 Average 7,700 22.9 h,950 17.6 2,800 10.9 Hj-gh... 10,000 26.0 6,000 20.0 B’W 13.0 Ion.... 10,000 2h.0 5,000 17.0 1,500 6.0 15- .Average 1h,850 33.5 8,100 21.2 h,lh0 12.1 High... 18,000 no.0 10,000 26.0 5,000 16.0 Table compiled by Paul C. Guilkey, Research Forester, U.S.F.S. Table taken from Michigan State Tax Commission.Assessor's Manual (1955). '1‘ gang Page 59 Table XI. Estimated Annual Increment Per Acre of Various Woodland Products for Each Soil Management Group, Eaton County. Soil Woodland Species Management LH NH 0H AP Grow bd.£t. cords bd.i‘t. cords bd. . cords bdffi. cords 23. - - 120 0,48 1110 0’48 - " 2b 125 .68 100 .36 22h . 72 152 . 88 20 75 .118 90 .30 - - 112 .80 3a "’ "' 12 0 0,48 1110 .118 - - 3b 113 - .56 100 .36 22,4 .72 112 .80 3C 100 .112 90 .30 - " 72 .68 14a "' - 111 0’12 88 .36 'l' - 110 100 .I12 - - - - 118 .56 53 - '- 100 036 72 .32 - '- LBC 100 0,42 - " - - ’48 .56 13 Age 100 .112 - - - - 1.8 . 56 b1! 50 .21 - - - - ho .30 Page 60 Table III. Estimted Value of Annual Increment Per Acre From Various Woodland Uses for Each Soil Mamgenent Group, Eaton County. Soil Wofind Species Management L H N H 0 i A P Group bdd’ . cords Ext. cords bd.i‘t. cords bd.ft. cords 2a - - $1.111; $ .hB $1.26 $ .118 - - 2b $1.00 $ .68 1.20 .36 2.02 .72 3 .83 9p .88 2C .614. .118 1.08 .30 "' "' .61 .88 33- " C. 1.11).]. .118 1.26 .218 -' - 3b .96 .56 1.20 .36 2.02 .72 .61 .80 30 .85 0,42 1008 030 "' "' 039 .68 ha " " 1033 0’42 079 036 " " 1W .85 0’42 " "' "‘ " 026 056 5a - - 1.20 .36 .65 .32 - '- LBC .85 0&2 "' ‘ " " .26 .56 LB-hc .85 .112 - - - - .26 .56 ME .133 .21 - f- - - .22 .30 Page 61 Table XIII. Estimate of Percentage of Annual Increment Occurring as Saw Timber and Pole Timber by Woodland Species. Woodland Spe cies Use "”i'fi* N fii <37?* I.i7' Saw . Timber 60 55 no 25 P013 Timber ho __ hS 60 75 Page 62 Table XIV. Estimated Proportion of Each Soil Management Group Occupied by the Various Groups of Woodland Species. Soil Management Woodland Species 1 Group L H N H O H A. P 23 - .60 .110 - 2b 020 .);O .35 .05 20 080 013 "' 007 3a " 055 all; "' 3b .10 .60 .25 ~05 3C .85 .(B "" .10 ha - .50 .50 - 13C 090 " ' .10 Ea - .50 .50 '- 130 090 "' " .10 13'4“? 090 " "‘ .10 bM o 9 O " "' .10 Page 63 Table XV. Estimate of.Annual Net Income Per.Acre Fromeoodland Species on the Soil management Groups in Baton County. Soil management ‘__r woodland Species Group L H N H O H A.Pri 28. 3 "' $1002 $ 079 5 " 2b .87 .82 1.2h .87 26 057 0711 " 07S 33. - 1.02 079 " 3b .80 .82 1.2h .75 3° .68 .711 - .61 ha " 092 05h " he .68 - - .h9 53 -' 082 01-15 " L33 068 "' "‘ 0,49 LB-L'c .68 "' " 0119 bu 03h "‘ " 029 Page 614 Table XVI. Ratio of Computed Net Income to Sale Price on Unimproved Farmlands or Those with Low Timber and Improvement Values in.Eaton County. Farm. Sale Computed Capitalization Number Price met Income Percentage 8 $13,600 $ 867 6.6 19.5 3,750 893 26.h 27 7,250 1,025 lh.2 15 11,000 1,102 13.6 51; 17, 750 3,013 16.1 8h 0,250 750 17.6 Averages $ 9,600 $ 1,3h5 . lh.01 Page 65 Table XVII. Ratio of Computed Net Income to Farmer '8 Estimate of Farmland Value on Farm Account Farms in Eaton County. Farm Estimted Computed Capitalization Number Farmland Value Net Income Percentage 2A 8 13.599 8 1,871 13.8 6A 22,828 h,503 19.8 7A 16,315 1,183 7.2 13A 11,591 3,15L 27.3 11.1 211,312 3,217 13.3 201 314,251 2,923 8.5 211 16,517 2,357 1h.3 Averages 3 19,920 5 2,7148 13.8 Table XVIII. Farm Number 1 Computed Land Value 6 8,888 2461 6,382 9,812 17,612 18,188 10,582 1,535 8,869 11,931 10,165 18,177 22,235 21,102 15,159 3,718 3,872 11,882 16,682 6,592 8.h76 Appraised Land value 8 5,320 3,720 5,775 9,350 15,115 12,300 9,500 8,500 8,000 111,281 7, 700 20,860 11,830 18,188 12,280 5,200 3,100 9,600 15,150 7,000 6.350 170 65 110 105 116 162 110 100 106 105 135 83 150 108 9h 133 Page 66 Ratio of Computed Land Value Per Farm to.Appraised Land value Per Farm.on 26 Farms, Eaton County. Computed/Appraised Z Page 67 Table XVIII (Continued) Farm Computed Appraised Computed/Appraised Number Land Value Land Value $ 73 8 11,1106 8 12.000 95 71 5,153 11,610 112 75 5,123 b, 800 107 93 11,1111 16,910 Eh 99 17,827 16,730 106 Averages ’ 8 11,311 8 10,115 112 Page 68 Table XIX. Ratio of Computed Land Value to Farmer's Estimated Land Value, Eaton County. Farm Computed Estimated Conputed/gstmated Number Land Value Land Value % 2A 3 13,305 5 13,599 98 6A 31,818 22,828 138 71 ‘ 8,103 16,315 52 13A 22,331: 11,591 192 1118 23,001 211,312 95 201 20,h61 3h,251 60 21A 16,6h1 16,517 100 Average 8 19,370 8 19,920 97 Page 69 Table XX. Ratio of Computed Land Value to Calculated Sale Price of Land on 23 Farms, Eaton County. Farm 315%: Computed Conqauted/Calculated Number of Land Land value x 1 8 3,280 8 8,888 278 2 2,808 2,868 88 5 8,386 6,382 186 38 18,160 18,188 129 80 7,263 10,582 185 82 3,788 8,869 228 86 7,852 18,931 191 87 7,310 10,865 182 51 3,992 18,177 855 53 8,895 22,235 500 58 8,260 21,802 500 55 7,621 15,159 199 65 5,805 3,718 69 66 1,555 3,872 289 67 6,898 11,883 172 70 9,515 16,682 176 71 8,025 6,592 163 72 2 ,536 8,876 338 73 8,788 11,806 131 78 6,795 5,153 76 75 5,628 5,123 91 Table XX (Continued) Farm Number 93 99 Average Calculated Sale Price of Land 5 21,277 10, 78.6 9 5, 708 Page 70 Computed Compute d/Calcwflated Land.Value % 8 18,181 67 17,827 166 3 119 39 7 170 Page 71 Table XXI. Ratio of Assessed value to Sale Price of Farm.Real Estate on 99 Farms in Eaton County by Value Groups. Sale Price Assessed value Assessed Number EaIE Sale Price of Farms Total Per Farm. Total Per Farm. % Under $5,000 12 $39,h91 $ 3,291 $h3,100 3 3,592 109 $ 5,000- 7,899 8 88,837 6,055 37,650 h,706 78 7,500- 9,999 19 155,09h 8,689 9h,500 h,973 57 10,000-18,999 31 398,129 12,713 183,900 5,932 87 15,000-19,999 13 230,890 17,730 105,150 8,086 86 20,000 & above 16 817,066 26,066 169,500 10,598 81 All Groups 99 1,29h,707 13,078 633,300 6,h02 h9 Page 72 Table XXII. Ratio of.Assessed Value to Owners Estimate of Farm market Value on 15 Farms in Eaton County by value Groups. market Value Assessed Value Assessed Number Lhrfiet market Value of Farms Total Per Farm. Total Per Farm. Z 815,000-828,999 5 8101.500 820,300 8 39,600 8 7,920 39 25,000- 3h,999 5 150,000 30,000 55,200 11,0h0 37 35,000 & above 5 225,200 85,080 80,000 16,000 35 1111 Groups 15 876,700 36,780 178,800 11,620 36.5 Table XXIII 0 Farm Number 1 2 5 38 80 Page 73 Ratio of Total Appraised Farm.Value Per Farm to sale Price on 23 Farms in.Eaton County. Sale Price 3 3,280 5,130 11,070 21,000 18,850 10,105 20,790 18,805 17,750 13,865 18,815 10,575 5,805 8,500 15,750 18,815 13.750 8,750 22,795 18.750 13,750 Appraised value $ 5,320 6,086 12,899 19,180 17,087 18,317 27,179 15,195 38,618 28,200 32,783 15,138 5,200 10,385 18,856 28,750 16, 725 12,568 26,007 12,565 13,566 Appraised/Sale % 165 117 113 91 115 181 131 102 196 175 178 96 121 113 131 121 85 99 Table XXIII (Continued) Farm Number 93 99 Average Sale Price 832,702 21.385 $111», 732 Appraised value $23,335 27,369 $18,282 Page 78 Appraised/Sale % 87 128 128 FIGURE I. HI" 0 - I Q I I 8 Inc .(All RAIL-nu A..." RAIL-ml URI uni-Inn" Lu" Int-I Au 3n“!- --- IIYIIII'YIIY Snu- OOAIIul Uncut DM- 0" Inn-u Fun-O nut Anvuu Lawn-c nuu CM" Sun 5% H 0.1 ““70 1-0-0|! *5 EATON COUNTY, CO CLINTON Tun mum-c Alto rum-O CAI" no Ina-n aAILIOAofinvIo-s. Foul Coal-us. nc. You Hun SCNOOts CuU-cnu CIKYIIIII Conn-uno- ot'Alf-Nv u-In Faun nu You" Yarn-(N's CAIOIS 'A'IOL CAoINI YOU-In cum no Man Gou Coon” Oununu You“ Hill! 0- Willi. $0.”! on Pun 7v .‘fi L fivb'n- MICHIGAN LOCATION or rANNs USED IN LANO EVALUATION STUDY CO . JACKSON L | 1 L OCALI II IILII 4 LOCATION II IICNIOAN 'fl.‘ CO Page 76 FIGURE 2. ILLUSTRATION OF THE METHOD USED-IN MEASUREMENT AND RECORDING OF ACREACES. Farm Outline C/ If“ 1 V L Ml ' I I M! 8 9 l7] l6 Township - (in Eaton County) Acroa = 30 Scalo -.-. -4‘__.L2zzd: Soil boundary = M Land use boundary : ...... Acreage Chart Soil Land Uu Management Slope Map L P F X Group Class Symbol are A-fi 41/ I72 A 1.7 0.? 2.8 A-IS C/ 3/.3 ‘63 /¢-7 0-9 2; 1‘5 BC /./ 3-‘7” " "5 Totals 7‘76 7.7 2/.¢ /,3 Total 55'” .>Fz:oo 20h bmxm<2 Sm owmmmmw< .10 20.5351 .n maze—u 7 1ooo_a1 u21<> emxqu 2m oz< \o omuauzom I/ o ,1 L i 0 6 63 N — (OOOIQ) 3mm CINV'IWHVJ aslkusa ('3 IO 8 ¢ .>.—.ZDOO 20h0¢a!_za x5 20 024.. Mr; “.0 No.11 m4< .II/ to. O 0 It“. 0 1.0m INHVJ BOIHd 31VS (000! 9) .00 20h 2m< o oo 1,0. O O o O o o o in. O O O O O JION O 0 0 16m JrOm (OOOI 8) some aws .>._.2300 20b 024.. oum_<¢a¢< 920592200 x<._. mh 02¢... awhaazoo zmu3hmm EImZOrrdJum 02.302w 73410 < .h maze: 1000. f .131; owmzmuuq m mm on . mm ON 0. 0. m 0 m. 1 1 A. 1 w w 1 3 P O 0 0 0 . Ito M n o I. m. .3245: . oo o u I o \ou: 351.28 m>< 1. 1 o o. v N o o O A e w o 0 I6. 0 3 o o o o “W O Lomm O 335.: name... «3 .2322: .Czaoo 20:; 2. mix: on zo 3:: min oe $3.3; oummmmm< .10 1:529:15 .m manor. 800. 3 meme 3% 2 ow MN ON 0.. o. m .o 3 1 _ 1 1 _ m o e o 0 O O 6 II. o o .HNM mnmqt o 0 game .131; .10 .m>< u o 3.... :51. 113923. .I. o o to I1 :0. m4< oummumm< .m— (OOOIH) BOWVA OBSSBSSV ROOM USE ONLY m NOV 231965 a! FWII’) {3523? I LU W 2:11“ wéfi FE?“ ‘ 17:111.." JQE§*£3* NOV cg 33,1965 6:? ,, 1.1:“? "mama Uff"£ F11"? 5 f '1" ,' , 1'; . ' ‘ -,‘ I {(UUIN 5.11:3 " 3 . $811§¥T3§~ . NOV 23 1955 $87 $527?! 51% -- . 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