CORE CONSERVATION PRACTICES 1 CORE C ONSERVATION P RACTICES : A DOPTION B ARRIERS P ERCEIVED BY S MALL AND L IMITED R ESOURCE F ARMERS Bulletin 646 May 2001 Alabama Agricultural Experiment Station Auburn University Luther Waters, Director Auburn, Alabama 2 ALABAMA AGRICULTURAL EXPERIMENT STATION C ONTENTS INTRODUCTION .................................................................................. 3 Objectives ................................................................................................ 3 Definition of Limited Resource Farmers ................................................... 4 Small and Limited Resource Farmer Program Participation ...................... 4 Black and Minority-operated Farms ......................................................... 5 METHODS ....................................................................................... 7 Sample and Data Collection ..................................................................... 7 Measuring Adoption ................................................................................ 8 RESULTS ......................................................................................... 9 Income Sources ...................................................................................... 11 Conservation Tillage .............................................................................. 13 Conservation Tillage Adoption ............................................................... 15 Crop Nutrient Management .................................................................... 16 Crop Nutrient Management Adoption .................................................... 18 Rotation and Fertilization Practices ........................................................ 19 Integrated Pest Management .................................................................. 21 Integrated Pest Management Adoption ................................................... 23 Conservation Buffers ............................................................................. 24 Conservation Buffer Adoption ............................................................... 26 Conservation Program Participation ....................................................... 27 Determinants of NRCS Contact .............................................................. 28 Information Sources ............................................................................... 30 Information Mode .................................................................................. 33 Land and Water Resources ..................................................................... 34 CONCLUSIONS ................................................................................. 36 REFERENCES .................................................................................... 38 ACKNOWLEGEMENT: We thank the USDA-Alabama Agricultural Statistics Service for its assistance in instrument design, sampling, and data collection. First Printing 2M, May 2001 Information contained herein is available to all persons without regard to race, color, sex, or national origin. CORE CONSERVATION PRACTICES 3 CORE C ONSERVATION P RACTICES : BY A DOPTION B ARRIERS P ERCEIVED S MALL AND L IMITED R ESOURCE F ARMERS AND JOSEPH J. M OLNAR, ANNETTE BITTO, GAIL BRANT INTRODUCTION F OUR SETS OF FARMING PRACTICES—conservation tillage, crop nutrient management, weed and pest management, and conservation buffers—are the central focus of technical assistance efforts by conservation agencies. Although small and limited resource farms comprise more than threequarters of the operations in Alabama, Georgia, and Mississippi, this segment of the farm population has disproportionately low levels of adoption of these farming practices (also called the Core 4 practices), which are established measures for conserving soil and protecting groundwater. The purpose of this report is to provide baseline infomation for technical assistance for achieving national conservation objectives—specifically the adoption of the Core 4 Practices—on small and limited resource farms in the Deep South. Statewide samples from Alabama, Georgia, and Mississippi are used to present detailed profiles of the conservation practices and understandings of these practices among small and limited resources farmers. 1. Profile core conservation practices utilized by small and limited resource farmers in Alabama, Mississippi, and Georgia. 2. Compare the practices and perceptions of black and white farmers in Alabama, Georgia, and Mississippi. 3. Identify perceived barriers and disadvantages to the implementation of core conservation practices. 4. Describe patterns of information source utilization and preferences among small and limited resource farmers. Molnar is a professor and Bitto is a graduate research assistant in the Department of Agricultural Economics and Rural Sociology. Brant is a sociologist with the USDA-NRCS-Social Science Institute. O BJECTIVES 4 ALABAMA AGRICULTURAL EXPERIMENT STATION OF D EFINITION L IMITED R ESOURCE F ARMERS Research suggests that no all-purpose definition of a small farm can be readily established, but that a number of common characteristics can be identified (Tweeten, 1983). Working definitions have centered on the size of the operation, gross farm sales, and the number of hours contributed to labor and management of the farm operation. Small and limited resource farmers have been shown to be more riskaverse and posses fewer slack resources to invest in conservation measures (Dishongh, 1991; Zabawa, 1989; 1991). Most small farmers depend on farming to obtain a significant part of family income, but not necessarily a majority of it. In addition, the limited resource farmer and family members usually provide most of the labor and management for the farm operation. A part-time owner-operator obtains a percentage of total family income through off-farm employment, providing a substantial part of the household’s overall budget (Molnar and Adrian, 1980). For the purpose of this report, an income figure of $40,000 is used to distinguish limited resource farmers from commercial farmers, although other studies with other purposes may use different standards or combinations of criteria.1 As a target audience for USDA-NRCS programs limited resource farmers have many of the following characteristics (NRCS, 1991b): • Gross farm sales average $40,000 or less in each of the last three years. • Total household net income, farm and non-farm, is 75 percent or less of the nonmetropolitan median income level for the state or county. • Access to capital, labor, or equipment is not readily available. • Farm or ranch size is significantly smaller than average size. • Social, cultural, customs or language barriers may include the following: minimal awareness of USDA programs, limited management skills, levels of formal education below the county average, and less inclination to take business risks and adopt new technology. S MALL AND L IMITED R ESOURCE F ARMER P ROGRAM P ARTICIP ATION Previous research on agricultural program participation suggests a number of basic patterns that might be expected to apply to the conservation practices used by small and limited resource farmers in the Deep South. Decisions regarding implementing new technology on small farms might actually cause some small farmers to change their operation or stop farming as Gladwin and Zabawa found in their studies of small and part-time farmers in Florida (1985; 1986). McleanMeyinesse (1994) found that Louisiana small farmers do not participate in the Conservation Reserve Program if revenues from cropland are an important source of income, or if they are tenants. She found that actual participation depends on whether payments per acre are comparable to the opportunity costs of removing 1 The USDA National Commission on Small Farms chose to use gross income to categorize farms and defined small farms as “those with less than $250,000 gross receipts annually, on which day-to-day labor and management are provided by the farmer and/or the farm family that owns the production or owns, or leases, the productive assets.” This definition includes 94% of all farms in the United States. CORE CONSERVATION PRACTICES 5 cropland from production. Awareness of the program was positively related to education, income, race, and average return per acre. Willingness to participate was inversely related to age, but positively influenced by the size of the payment per acre. Others have shown similar patterns of difference in the use of information sources (Korsching and Hoban, 1990; Hoban et al., 1986). Limited resource farmers and socially disadvantaged minority farm operators tend not to purchase crop insurance or to participate in insurance-type programs (Dismukes et al., 1997). They tend, more than the typical U.S. farmer, to raise livestock rather than crops. As there are no government-sponsored insurance-type programs for livestock, this seems to reduce the need for contact with public agencies among these producers. In addition, many of those who raise crops tend to concentrate on specialty crops such as fruits and vegetables rather than row crops that are the focus of most government programs. In many cases, farm income makes a minor contribution to a household’s overall income. A lack of insurance for the farm enterprise may be less important for these operators than for others more reliant on farm income. Mishra et al. (1999) investigated the factors affecting profitability of limited resource and other small farms. Profitability on limited resource farms—as measured by net farm income and operators’ labor and management income—depended on the operator’s age, soil productivity, debt-to-asset ratio, and ratios of variable and fixed costs of production to value of agricultural production. A major source of variation in the performance measures of small and limited resource farms is the ratio of variable costs to value of agricultural production. Unexpected variable costs can have a disastrous effect on the profitability of a particular farm enterprise as well as the viability of the entire operation. One piece of conventional wisdom is that farmers must either get bigger or get out of farming, but this assertion fails to recognize the diversity of niches for farming in nature and society. The future is dim for small-scale production of basic agricultural commodities such as corn, hogs, soybeans, cattle, etc. Nonetheless, Ikerd (1999) makes the case that there is a future in producing food and fiber products by methods that both can be sustained by nature and will be sustained by society. Sustainable systems must conform to marketing and ecological niches inherent in nature—including human nature. Those niches are small and diverse, not large and uniform. Many families that operate small units depend on farming for a significant part of their economic, social, and spiritual way of life, if not their whole livelihood. For example, Feldman’s (1999) analysis of maple sugar operators describes their activity as a sideline and a lifeline, illustrating how small farms can conform to the economic and ecological niches of markets and of nature. B LACK AND M INORITY - OPERA TED F ARMS The number of black-owned farms is declining at a more rapid rate than other farms, which has called into question the treatment of minority farmers in receiving federal assistance (Yeboah and Wright, 1985). GAO (1997) reviews efforts to 6 ALABAMA AGRICULTURAL EXPERIMENT STATION treat minority farmers in the same way as non-minority farmers in delivering program services. Many minority and limited resource farmers blame government policies and practices for the severe decline in farm ownership by minorities, especially black farmers, in the last 70 years. Much of the black-owned land had been held for generations, in some cases acquired by these farm families after slavery was abolished in the 1860s. According to the Census of Agriculture, the number of farms owned by blacks fell from 925,000 in 1920, 14 percent of all farms, to only 18,000 in 1992, one percent of all farms. Although the number of farms owned by other minorities has increased in recent years, particularly among Hispanics, the total acres of land farmed by these groups has actually declined. Only women have seen an increase in both number of farms and acres farmed. During this time, the number of non-minority farmers also has dramatically declined, although at a slower rate. Minority farm advocates blame farm program regulations that—intentionally or not—shut out minority and limited-resource farmers from the benefits of the programs that have helped larger non-minority producers survive the changes in agriculture in the last 50 years (Brown and Larson, 1979). And they identify institutional insensitivity to the differing needs of minority and limited-resource customers and pubic agency tendencies to neglect their responsibility to reach out and serve all that need assistance. Some farm advocates liken minority farmers to an “endangered species” (USDA, 1997a; 1997b). GAO (1997) identified 101 U.S. counties with the largest concentration of minority farmers, several of which are in Alabama. One-quarter had no minority employees in their farm service agency (FSA) offices. In those offices that did employ minorities, most were program assistants, although one-quarter of the offices had minority county executive directors. Perhaps the lack of diversity that minority and limited-resource customers deem to be most critical is the lack of minority and female representation on the county committees, which can affect access to FSA programs. In 1994, 94 percent of all U.S. county committees had no female or minority representation. Bagi (1984) examined the likelihood of a farmer being visited by an extension agent in West Tennessee, given the personal characteristics of the operator and economic aspects of 80 farm-firm households. The results show that extension agents visit some small farm operators, but even among this group of small farms, extension agents tend to visit operators of relatively large farms. Within the small farm group, extension agents are more likely to visit white farmers than black farmers, and tend to visit better-educated small farm operators. In other words, extension agents are less likely to visit those small farm operators who need more help due to their perceived lower level of organizational and management ability. Most of the small farm operators in the Bagi study were not being served by regular extension services. Onianwa et al. (1999) identified factors that affect conservation practice choices among Conservation Reserve Program (CRP) participant farmers in Alabama. Analyzing 204 useable surveys from farmers with CRP contracts, they found CORE CONSERVATION PRACTICES 7 that education, ratio of cropland in CRP, farm size, gender, prior crop practice, and geographic location of contract each had a significant influence on the choice of conservation practice. No significant differences by race were reported, however. This study also determined that limited resource farmers do not implement conservation practices as frequently as full-time farmers. The disparity in participation and treatment of non-minority and minority farmers may be partially accounted for by the smaller average size of minority and female-operated farms, their lower average crop yields, and their greater likelihood not to plant program crops. In addition, minority farmers tend to have less sophisticated technology, insufficient collateral, poor cash flow, and poor credit ratings (GAO, 1997). However, representatives of minority and female farm groups point out that previous discrimination in USDA programs has helped to produce these very conditions now used to explain disparate treatment. Many perceive that public agencies do not place a priority on serving the needs of small and limited resource farmers and do not support any official effort to address this problem (USDA, 1997b). The several public agencies that serve farmers have developed their own separate programs that may or may not be successful in responding to the numerous differences found among minority and limited resource customers. Some minority and limited resource farmers feel they do not receive the technical assistance they require nor the basic information about programs for which they might be eligible. Many who need help to complete application forms also need help to understand and meet eligibility requirements for programs. They need information about how their applications will be processed. If their application is denied, they need information on how they might succeed in future applications. When they do receive loans or other program benefits, they need assistance to use those benefits most effectively to improve their operations (Schor, 1992; 1996). This report provides basic information profiling the conservation practices and technical assistance preferences of black and white small farm operators, a body of information not available from any other source. METHODS S AMPLE AND D ATA C OLLECTION The sampling design for the study was structured so as to yield approximately equal numbers of black and white farmers in Alabama, Georgia, and Mississippi.2 A simple, random sample of white farm operators included those operations with 2 Each USDA-National Agricultural Statistics Service state office maintains a constantly updated list of all known agricultural producers. Names and information from the 1997 Census of Agriculture were used to supplement the farm operator list. Every effort is made to maintain and keep the list as up-to-date as possible. However, any list frame of farm operators will always be incomplete because of constant changes in population due to retirements, farm sales, farm consolidations, entry of new farm operators, changes in operating arrangements, etc. Consequently, there is an undetermined amount of incompleteness in the list frames for the states involved in this study, but it is minimal. 8 ALABAMA AGRICULTURAL EXPERIMENT STATION less than $40,000 gross value of sales and row crop control data for cotton, corn, soybeans, or peanuts. All list names of black and other minority farm operators were selected for the survey. The sample sizes and number of completed mail surveys that were returned by black and white respondents in each state are shown in Table 1. TABLE 1. P OPULATION C OUNTS , S AMPLE SIZES , AND SURVEY RESPONSES State Alabama Georgia Mississippi Total ——White farm operators—— Population Sample Responded 2,332 2,763 1,496 6,591 507 552 487 1,546 138 115 127 380 BY STATE, 2000 ——Black farm operators—— Population Sample Responded 1,062 688 1,053 2,803 1,062 688 1,053 2,803 157 119 178 454 Survey data were collected by mail using a self-administered survey instrument adapted in part from previous research conducted in a sample of farm operators in the Midwest (CTIC, 2001). A second request questionnaire was used to increase the mail response. To further boost response counts, a limited amount of non-response follow-up was done for both race groups in Georgia and the white sample in Mississippi. Trained telephone interviewers from the NASS Alabama State Statistical Office conducted the follow-up. Responses are tabulated by race and state to facilitate comparisons of the data for educators and technical assistance providers, farmers, and other professionals with interest in the pattern of results in a particular state. Four respondents did not provide race identification so all tables were constructed on a base of 830 cases. Chi-square statistics are presented where appropriate to draw attention to important differences by race or state. Chi-square statistics are not appropriate for multiple response items where respondents could indicate more than one category in response to a question. There are several statistical caveats to the use of significance tests on these data due to the nature of the sampling, low response rates that signal some concerns about representativeness, and other shortcomings that suggest caution in interpretation of the observed differences. Nonetheless, significance tests do draw attention to patterns of differences that are less likely to have occurred by chance and may be worth interpreting in a qualified way given the aforementioned limitations. M EASURING A DOPTION Conservation Tillage (CT) adoption was measured by four variables reflecting precursor conditions associated with the actual use of specific CT practices. Respondents were asked to rate their level of familiarity with CT and the perceived practicality of CT. They were asked to note possible reasons for using CT on their farms. The measure counts how many they cited. They also were asked to check a CORE CONSERVATION PRACTICES 9 series of CT practices that they had implemented in their farms and the measure counts the number of practices they reported. Crop Nutrient Management (CNM) adoption was measured by four variables reflecting precursor conditions associated with the actual use of specific CNM practices. Respondents were asked to rate their level of familiarity with CNM and the perceived practicality of CNM on their farms. They were asked to note possible reasons for using CNM. The measure counts how many they cited. They also were asked the frequency at which they obtained soil tests for the nutrient properties of their farmland or pastures, the central feature of any program of CNM. Integrated Pest Management (IPM) adoption was measured by four variables reflecting precursor conditions associated with the actual use of specific IPM practices. Respondents were asked to rate their level of familiarity with IPM and the perceived practicality of IPM on their farms. They were asked to note possible reasons for using IPM and the measure counts how many they cited. They also were asked to check a series of IPM practices that they had implemented in their farms; this measure counts the number of practices they reported. Conservation Buffer (CB) adoption was measured by four variables reflecting precursor conditions associated with the actual use of specific CB practices. Respondents were asked to rate their level of familiarity with CB and the perceived practicality of CB on their farms. They were asked to note possible reasons for using CB and the measure counts how many they cited. They also were asked to check a series of CB practices that they had implemented in their farms; this measure counts the number of practices they reported. Statistical weighting was employed in regression analysis to restore representativeness to the combined data set due to the differential rate at which black farm operators were sampled. The weights restore statistical representation in the sample mirroring the statistical representation in the population of farm operators in the three states. RESULTS Table 2 shows the respondents’ characteristics by state and race. Most of the small-scale operators who responded to the study were male and—due to sample selection procedures—were nearly equally divided between black and white in each state. About one percent of the overall sample was Native American. These respondents are tabulated with the white respondents primarily because there were insufficient cases for specific analysis of this category of farmers and one focus of the study was to examine the problems challenging black farmers. Education varied significantly by race and state. Thirty seven percent of the Alabama black respondents had a college education or higher, suggesting that many part-time, hobby, or heir-property landowners may be included in the sample. In Georgia, 28 percent of the black respondents had advanced education, compared to 20 percent of the white farmers. This was a parallel pattern across the three states. The black respondents had higher levels of education than the white respondents. 10 ALABAMA AGRICULTURAL EXPERIMENT STATION T ABLE 2. R ESPONDENT C HARACTERISTICS BY R ACE AND S TATE , SMALL AND L IMITED R ESOURCE F ARMERS , 2000 All % What is your gender? Male 94 Female 6 Race African American White Native American 54 46 1 —Alabama— White Black % % 97 3 0 99 1 94 6 100 0 0 —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % 93 7 0 98 3 92 8 100 0 0 96 4 0 98 2 91 9 2.2 100 0 0 N/A What is the highest level of formal education you (the operator) completed? Less than high school 18 13 20 18 27 13 17 High school diploma 29 37 19 42 29 30 22 or GED Some college 24 25 25 19 16 34 24 Completed 4-year 15 16 16 10 10 16 16 college degree Graduate school 14 8 21 10 18 7 21 19.4* 36.7** How old were you on your last birthday? Under 35 3 6 1 35-44 13 17 7 45-54 22 17 26 55-64 35 27 32 65-69 27 13 14 70 and over 24 20 20 3 10 14 29 16 28 4 12 22 26 9 27 4 16 21 22 12 25 0 15 27 15 19 24 21.4* How many days did you work at least 4 hours off this operation last year (1999)? Did not work 25 25 24 27 24 31 22 off the farm 1-49 days 19 19 13 12 18 14 19 50-200 days 22 22 26 18 27 17 30 200+ days 34 34 37 44 32 39 28 1.7 Did your spouse work at least 4 hours per day off this operation last year (1999)? No spouse 13 12 13 13 14 10 15 Spouse did not work 37 28 40 37 36 39 40 off the farm 1-49 days 13 18 15 12 6 9 14 50-200 days 9 9 8 8 12 9 9 200+ days 29 33 24 31 33 34 22 6.9 Number *p < .05 **p<.01 830 137 154 118 116 129 176 16.8* N/A 3.2 10.3* 4.5 CORE CONSERVATION PRACTICES 11 Age varied significantly by race and state, though these patterns were not consistent across categories. About 44 percent of Georgia white farmers were age 65 or over, as were about 43 percent of Mississippi black farmers. About a fourth of all operators did not work off the farm in the previous year. The test statistic suggests that differences by race, but not by state, are worth attending to. More Mississippi white farmers did not work off the farm (31 percent), but Mississippi black farmers were least likely to not work off the farm (22 percent). About 44 percent of Georgia white farmers worked full-time off the farm, the highest rate in the sample. About 34 percent of the sample had spouses who worked 200 or more days off the farm, but differences were not significant by race or state. About half either had no spouse or had a spouse who did not work off the farm. I NCOME S OURCES Table 3 shows the sources of farm income in the sample of small and limited resource farmers. There were large differences by race and state. Row crops such as cotton, soybeans, and other items were grown by approximately a third of the farmers. In each state, more white farmers reported growing row crops and they were consistently more likely to report this enterprise as a source of 75 percent or more of their farm income. Only 15 percent of Alabama and 20 percent of the Mississippi black farmers reported growing row crops. Around 70 percent of the sample had income from livestock with large differences by race and state. More white farmers did not have any livestock. Black farmers were more likely to report that more than 75 percent of their farm income came from livestock. Only three percent of the sample had poultry, primarily white farmers. The test statistics for race and state were not significant. Central to the growing industrialized sector, poultry represents the single most important agricultural product in Alabama and Georgia. It accounts for more than half of all farm income in these states, employing many people and generating the majority of farm exports. Small and limited resource farmers are not participating in the most technologically dynamic and economically active components of agriculture. Sixteen percent of small and limited resource farmers reported sales income from fruit, vegetable, horticulture, or specialty crops. There were no significant differences by race or state. Roughly 74 percent of the sample received no income from government payments, though state differences were significant. About 16 percent of Georgia farmers received half or more of their income from government payments, the highest in the sample. About four percent indicated that 75 percent or more their income was from the farm. Overall differences by race and state were not significant. Farm income category differed significantly by race. More white farmers in each state reported farm incomes in the top three categories. More black farmers in each state were in the lower income categories. 12 ALABAMA AGRICULTURAL EXPERIMENT STATION Although the sample was selected to target operators of farms with less than $40,000 in sales, about 3 percent of the sample had a higher level of annual sales. This is due primarily to annual variability in farm income between the reporting year and the year of the sample selection criterion. Data from these operators was not excluded because farm income is variable from year to year and these operations qualified as small and limited resource farms in previous reporting periods. T ABLE 3. F ARM I NCOUME S OURCES AND C HARACTERISTICS BY R ACE SMALL AND L IMITED R ESOURCE F ARMERS , 2000 All % —Alabama— White Black % % AND S TATE , —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % What percent of the sales reported on your operation came from the following commodity groups? Row crops such as corn, cotton, soybeans, etc. None 67 61 85 50 63 53 80 1 to 49 percent 9 9 4 13 11 14 6 50 to 74 percent 8 12 6 14 7 5 5 75 to 100 percent 17 19 6 24 19 28 10 24.5** 45.3** Livestock such as cattle, hogs, sheep etc. None 30 32 18 1 to 49 percent 7 13 4 50 to 74 percent 7 5 6 75 to 100 percent 56 50 72 48 7 8 36 32 14 9 46 40 5 7 48 20 3 6 70 33.2** 34.9** Poultry, including contract broilers, eggs, etc. None 97 96 99 100 1 to 49 percent 1 1 1 0 50 to 74 percent 1 0 0 0 75 to 100 percent 1 3 0 0 Fruit, vegetables, horticulture, or speciality crops None 84 1 to 49 percent 8 50 to 74 percent 2 75 to 100 percent 5 83 7 3 7 83 6 4 6 81 12 2 6 85 7 3 5 86 8 2 5 86 10 1 2 9.5 Government agricultural payments None 74 1 to 49 percent 16 50 to 74 percent 3 75 to 100 percent 7 73 18 3 6 79 17 3 2 58 24 8 9 72 13 2 13 77 12 4 7 78 15 1 6 19.1* 8.8* continued 1.6 97 0 1 2 98 2 0 0 95 2 2 1 11.2 4.7 CORE CONSERVATION PRACTICES 13 T ABLE 3, CONTINUED . F ARM I NCOUME S OURCES AND C HARACTERISTICS BY R ACE AND S TATE , S MALL AND L IMITED R ESOURCE F ARMERS , 2000 All % —Alabama— White Black % % —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % About what percent of your total 1999 household income was from farming? Less than 25% 73 72 78 69 75 70 73 25% 17 19 17 15 15 18 18 50% 6 5 3 10 7 6 6 75% or more 4 4 3 6 3 6 3 7.9 4.4 Including ag payments, what was the total gross value of sales from this operation? Less than $1,000 25 23 33 14 31 17 30 $1,000-$2,499 25 16 26 24 22 15 27 $2,500-$4,999 14 17 15 10 8 18 15 $5,000-$9,999 22 19 17 27 25 30 19 $10,000-$39,999 14 21 10 21 10 19 8 $40,000 and over 3 4 1 4 5 3 1 19.1 44.0** Number *p < .05 **p<.01 830 137 154 118 116 129 176 C ONSERV ATION T ILLAGE Table 4 shows the conservation tillage (CT) experiences reported by study respondents. Only 17 percent of the sample was very familiar with CT, but many differences by race were significant. Black farmers were consistently less familiar with CT than white farmers. Alabama black farmers had the highest proportion indicating they were not familiar with CT, 44 percent. Conversely, 26 percent of the Alabama white farmers said they were very familiar with CT, the highest proportion across the three states. About a third of the respondents felt that CT would be practical on their farms. Differences were significant by race showing that 20 percent of Alabama and 29 percent of Mississippi black operators saw CT as practical on their farms, the lowest levels in the sample. Only about 15 percent of the respondents had crop acreage planted used CT practices. More whites consistently had more land under CT than blacks. Less than 10 percent used any single CT technique. No-till was the overall most used tillage practice. Respondents were given a number of reasons for using CT and asked to mark all that applied to them. The table ranks them in terms of the overall frequency that each was chosen. About 20 percent felt that the main reason for using CT was reducing soil erosion, but this was highly variable across the states. Around 10 percent noted conserving soil moisture, and 9 percent marked increasing organic matter and saving time as reasons for using CT. There were few consistent differences by state or race, though more Mississippians felt that CT increased yields per acre. 14 ALABAMA AGRICULTURAL EXPERIMENT STATION The main perceived problems with CT were more weeds, higher herbicide costs, and high equipment costs, each cited by about 10 percent of the sample. More white farmers cited disadvantages. In each state, slightly more black farmers noted that how-to information was not available. T ABLE 4. C ONSERV ATION T ILLAGE E XPERIENCES AND P ERCEPTIONS BY R ACE SMALL AND L IMITED R ESOURCE F ARMERS , 2000 All % —Alabama— White Black % % AND S TATE , —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % 31 55 14 19 63 18 37 50 13 7.2 31.0** How familiar with conservation tillage (CT) are you? Not at all familiar 30 24 44 20 Somewhat familiar 53 50 45 60 Very familiar 17 26 11 20 Is CT practical on your farm? It would be good 32 40 Not very practical 21 23 No opinion 47 37 20 20 60 32 30 38 30 18 52 40 25 35 29 15 56 3.1 32.6** What percentage of your total crop acreage was planted last year (1999) using any CT practices? No crop acreage 85 79 93 85 83 78 89 Less than 50 percent 5 6 4 3 7 7 5 50 percent 3 4 1 2 4 3 2 More than 50 percent 7 11 2 10 6 12 4 1.3 18.1** What conservation tillage practices did you use? No till 5 8 1 8 5 9 3 Reduced till 5 8 2 3 3 9 3 Mulch till 3 3 3 1 5 4 3 Strip till 1 2 1 2 1 2 2 Ridge till 1 1 0 3 3 0 1 N/A N/A What are the main reasons you would use CT on your farming operation? Reduces soil erosion 20 29 12 18 18 30 19 Conserves soil 10 14 5 10 10 14 9 moisture Increases organic 9 9 6 11 11 13 4 matter Saves time 7 9 3 6 8 13 6 Lowers production 6 9 5 6 5 8 5 costs Increases yields 6 4 3 3 8 9 8 per acre Reduces soil 5 3 3 6 5 7 4 compaction Other 0 0 0 0 1 0 0 N/A N/A continued CORE CONSERVATION PRACTICES 15 T ABLE 4, CONTINUED . C ONSERV ATION T ILLAGE E XPERIENCES AND P ERCEPTIONS BY R ACE AND S TATE , S MALL AND L IMITED R ESOURCE F ARMERS , 2000 All % —Alabama— White Black % % —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % What are the main problems you might have with CT on your operation? More weeds 11 14 5 13 13 15 8 Higher herbicide costs 11 18 3 13 5 21 6 Equipment costs 10 12 6 11 6 15 13 too much “How to” Information 3 3 5 3 4 2 3 not available Crop yields are lower 2 3 1 1 3 5 2 Disease problems 1 1 1 1 3 3 1 More insects 1 0 2 2 1 2 1 Tried CT and 1 0 1 1 1 0 2 it didn’t work Other 1 1 0 1 2 0 1 N/A Number *p < .05 **p<.01 830 137 154 118 116 129 176 N/A C ONSERV ATION T ILLAGE A DOPTION Table 5 shows regression analyses of conservation tillage adoption variables on selected characteristics of small and limited resource farmers. These data show the variables that best predict a number of dimensions associated with the implementation of CT by limited resource farm operators. Education predicted three of the adoption variables. Respondents with more years of schooling thought that CT was more practical on their farms, they gave more reasons for using CT on their operations, and they had actually adopted more of the CT practices on their land. Total gross value of sales predicted familiarity with CT and the number of reasons given. It was not significantly related to the perceived practicality nor the actual number of practices adopted. Farm sales as percent of total income was associated with familiarity, perceived practicality, the number of reasons for using CT, and the actual number of practices adopted. Dependence on farming for livelihood was linked to conditions associated with the use of CT practices as well as how many were actually adopted. Black farm operators were significantly less familiar with CT. The equations explained 10 percent or less in the variation in each of the adoption variables. 16 ALABAMA AGRICULTURAL EXPERIMENT STATION T ABLE 5. R EGRESSION A NALYSIS OF C ONSERV ATION T ILLAGE A DOPTION V ARIABLES ON S ELECTED F ARM AND I NDIVIDUAL C HARACTERISTICS , SMALL AND L IMITED R ESOURCE F ARMERS , 2000 ———————Conservation tillage——————— Familiarity Practicality Reasons Practices Formal education Age Total gross value of sales Your outside work Spouse outside work Land Row crops farmed Livestock raised Poultry raised Fruits and vegetables raised Government assistance payments received Farm operator’s gender Race Farming receipts as percent of total income R2 Adjusted R2 F-value *p<.05 ** p<.01 0.051 0.038 0.093* 0.103* 0.011 0.075 0.163* 0.088 0.053 0.114* 0.069 0.019 -0.087* 0.132** 0.100 0.078 4.570** 0.096* -0.081 0.029 0.011 -0.013 -0.037 -0.029 -0.138* -0.122** -0.036 -0.117* 0.005 0.020 0.183** 0.059 0.036 2.598** 0.114** -0.037 0.120* 0.061 -0.041 0.020 -0.080 -0.143* -0.056 -0.058 -0.113* -0.024 -0.068 0.160** 0.077 0.055 3.446** 0.098* -0.054 0.066 0.026 -0.004 -0.064 0.039 -0.034 -0.068 0.015 -0.012 0.026 -0.071 0.106* 0.044 0.021 1.924* C ROP N UTRIENT M ANAGEMENT More than half of the farmers in this study were familiar with crop nutrient management, (CNM), Table 6. Around 11 percent were very familiar, but differences were not significant by state or race. Alabama black farmers had the highest proportion that was not familiar, 43 percent. A quarter (24 percent) of the sample believed that CNM practices would be practical on their operation. Mississippi black farmers gave it the highest rating, 42 percent. There were important differences by state and race in the frequency of soil testing. By a large margin in each state, more black than white farmers reported never soil testing. More Georgia farmers reported testing every year. Less than 10 percent of the sample soil tested every year, and about 44 percent of the sample tested every three years or less often. Farmers use CNM for a variety of reasons. Overall, 21 percent of the respondents thought CNM would increase crop yield per acre. Reduction in fertilizer costs motivated other farmers to implement CNM practices, a reason consistently cited by more whites than blacks. About 12 percent felt that CNM improved crop quality. CORE CONSERVATION PRACTICES 17 T ABLE 6. C ROP N UTRIENT M ANAGEMENT E XPERIENCES AND P ERCEPTIONS BY R ACE AND S TATE , S MALL AND L IMITED R ESOURCE F ARMERS , 2000 All % —Alabama— White Black % % —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % 32 56 11 3.0 Is CNM practical on your farm No opinion 55 46 It would be useful 24 37 Not very practical 20 17 59 31 10 48 36 16 53 36 11 53 33 15 45 42 13 1.9 About how often do you have your soils tested? Never 34 27 42 15 3 years or more 44 48 47 43 2 years 14 18 8 25 Every year 8 7 3 18 40 30 17 13 30 48 14 8 46 45 7 2 4.8** 39.8** What are the main reasons you would use CNM in your operation? Increases crop yields per acre 21 20 18 20 26 17 Reduces fertilizer cost 17 22 11 25 15 19 Improves crop quality 12 10 11 7 14 14 Better soil and water conservation 9 12 9 9 7 9 Reduces soil erosion 7 6 6 6 5 9 Slows water runoff 3 3 2 3 2 4 Other 0 0 1 0 1 0 0.3 2.6 How familiar with crop nutrient management (CNM) are you? Not at all familiar 35 26 43 36 40 36 Somewhat familiar 54 63 49 51 48 54 Very familiar 11 11 8 13 12 10 26 13 14 8 10 2 0 N/A N/A What are the main problems you might have with CNM on your operation? Equipment costs too much 12 15 10 10 11 11 16 Information on “how to do it” is not readily available 10 9 10 7 9 12 13 It is not cost effective 10 8 9 15 10 8 10 Takes too much of my time 5 5 5 6 6 6 6 Can’t find enough labor3 1 3 1 5 2 4 Crop yields per acre are lower 2 2 1 0 1 2 6 I’ve tried CNM and they didn’t work 1 0 1 0 2 0 1 Other 1 0 1 0 1 1 1 N/A Number *p < .05 **p<.01 830 137 154 118 116 129 176 N/A 18 ALABAMA AGRICULTURAL EXPERIMENT STATION Around 12 percent of the farmers said that expensive equipment was the greatest problem they had with CNM on their operation. More black farmers felt they did not have readily available information on how to use CNM. The perception that CNM was not cost effective kept many of the respondents from using CNM on their farm. Fifteen percent of white Georgia farmers gave this particular reason. C ROP N UTRIENT M ANAGEMENT A DOPTION Table 7 shows regression analyses of crop nutrient management adoption variables on selected farm and individual characteristics of small and limited resource farmers. These data show the variables that best predict a number of dimensions associated with the implementation of CNM by limited resource farm operators. Education predicted two of the four adoption precursor variables, but not familiarity with soil testing. Respondents with more years of schooling thought that CNM was more practical on their farms, and they gave more reasons for using CNM. Whether or not the respondent farmed row crops predicted perceived practicality, the number of reasons given for CNM use, and the frequency of soil testing. The variable was not linked to differences in familiarity with CNM. Similarly, those who raised livestock gave more reasons for using CNM and were more convinced of its practicality. Farmers growing fruit and vegetables were more familiar with CNM, tended to view it as practical, and gave more reasons for its use. T ABLE 7. R EGRESSION A NALYSIS OF C ROP N UTRIENT M ANAGEMENT A DOPTION V ARIABLES ON S ELECTED F ARM AND I NDIVIDUAL C HARACTERISTICS , SMALL AND L IMITED R ESOURCE F ARMERS , 2000 —————Crop nutrient management————— Familiarity Practicality Reasons Testing Formal education Age Total gross value of sales Your outside work Spouse outside work Land Row crops farmed Livestock raised Poultry raised Fruits and vegetables raised Government assistance payments received Farm operator’s gender Race Farming reciepts as percent of total income R2 Adjusted R2 F-value *p<.05 ** p<.01 0.084 0.011 0.035 0.001 -0.011 0.085 0.089 0.121 0.051 0.179* 0.040 0.013 -0.011 0.091 0.051 0.028 2.221** 0.200** -0.076 0.088 -0.003 0.064 -0.077 0.296** 0.308** -0.045 0.178** 0.096 0.082* 0.061 0.114* 0.109 0.087 5.055** 0.172** -0.041 0.113* 0.021 0.062 -0.013 0.180* 0.236* -0.045 0.172* 0.089 0.064 -0.001 0.079 0.087 0.064 3.915** 0.028 -0.033 0.228** 0.034 0.081 0.040 0.251* 0.131 0.020 0.039 0.031 0.027 -0.099* 0.063 0.168 0.148 8.363** CORE CONSERVATION PRACTICES 19 Black farmers had lower frequencies of soil testing than white farmers. There were no other differences by race on the other adoption variables. Farm sales, as percent of total income, were associated with the perceived practicality of soil testing. Those more dependent on farming for their livelihood knew more about CNM and tested their soil more frequently. R OTATION AND F ERTILIZA TION P RACTICES Fertilizer and crop rotation practices of small and limited resource farmers are portrayed in Table 8. Changes in fertilizer use were significantly different by race. Approximately 62 percent of all farmers indicated that their commercial fertilizer use had remained about the same over the past five years, although only 47 T ABLE 8. F ERTILIZER AND C ROP R OTATION P RACTICES BY R ACE SMALL AND L IMITED R ESOURCE F ARMERS , 2000 All % —Alabama— White Black % % AND S TATE , —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % Over past five years, has the average amount of commercial fertilizer used per acre on this operation: Remained about 62 75 51 75 53 63 47 the same Increased 19 12 24 11 22 19 21 No fertilizer used 12 5 22 5 17 10 22 in past five years Decreased 8 8 3 9 8 8 10 10.1 55.1** When is commercial fertilizer applied? No fertilizer used in past five years At planting time Before crops are planted After crops have come up (side-dressing) Through irrigation system as crops are being watered 12 39 39 41 1 5 48 42 42 0 22 31 30 31 1 5 36 52 59 1 17 40 35 40 2 10 50 42 46 1 22 31 37 33 1 N/A Do you use different amounts of fertilizer in different fields? No fertilizer used 12 5 22 5 17 in past five years Same amount is used 61 68 54 65 55 Different amounts 21 23 17 27 18 are used Don’t know 6 4 7 3 10 10 59 29 2 22 50 19 9 6.8 49.5** continued N/A 20 ALABAMA AGRICULTURAL EXPERIMENT STATION T ABLE 8, CONTINUED . F ERTILIZER AND C ROP R OTATION P RACTICES BY R ACE SMALL AND L IMITED R ESOURCE F ARMERS , 2000 All % —Alabama— White Black % % AND S TATE , —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % Is litter or manure ever applied to the crop/pasture land that you operate? No 78 70 87 73 81 74 82 Yes 20 29 12 27 15 25 16 Don’t know 2 1 1 1 4 1 2 1.9 How often is chicken litter or animal manure applied on your fields? Do not use litter 80 68 83 72 80 74 or manure Every 3 years 8 9 5 10 5 9 Every 2 years 5 9 4 6 2 7 Every year 7 10 3 10 8 9 81 8 3 5 3.8 23.0** 23.7** Is more or less commercial fertilizer used after chicken litter or animal manure is applied? Do not use 80 68 83 72 80 74 81 commercial fertilizer None is used 3 5 1 4 3 3 2 Less 12 19 6 16 9 14 9 Same 5 4 4 6 3 7 5 More 0 1 1 0 0 1 0 3.7 23.3** Do you grow the same crops in the same fields year after year or do you rotate between fields? Do not rotate crops -- 41 36 54 25 28 34 35 Always use the same fields Rotate crops 37 39 17 40 45 33 30 Some of each 22 20 10 28 14 28 18 26.3** 17.9** How often are crops rotated between fields? Do not rotate crops 41 36 54 25 28 34 36 Varies depending 24 24 8 35 18 32 15 Every year 13 15 6 12 24 9 9 2 years 13 12 10 9 14 9 13 3 years or more 9 8 3 13 3 11 11 37.5** 56.6** Do you include legumes in rotation? Do not rotate crops 41 36 54 25 28 34 36 Yes 28 35 10 45 30 36 22 No 16 19 11 13 15 16 19 I do not plant 8 5 6 10 14 8 7 legume crops 32.7** 40.8** Number 830 137 154 118 116 129 176 *p < .05 **p<.01 CORE CONSERVATION PRACTICES 21 percent of the black farmers in Mississippi said so. About 19 percent said that their fertilizer use had increased, though only about an eighth of the white farmers in Alabama and Georgia said so. Black farmers were much more likely to say that they had not used fertilizer in the past five years. Previously, the data showed the black farmers were much less likely to be involved in row crop enterprises where fertilizer is a central tool. Almost 41 percent of the sample used side-dressing for the application of commercial fertilizer, followed closely by application at planting time and before crops are planted. White farmers tended to use more of each approach to crop fertilization. Whites were significantly more likely to adjust the amount of fertilizer they used in different fields. The basic knowledge for such adjustments comes from soil testing. More white than black farmers in each state applied litter or manure to their fields, a statistically significant pattern. About 27 percent of the white farmers applied litter or manure compared to about 14 percent of the black farmers. Similarly, more white farmers than blacks used chicken litter or manure and they applied it more often. White farmers were more likely to indicate that they used less commercial fertilizer after applying litter, a statistically significant pattern. Crop rotation varied significantly by state and race. Forty-five percent of the Georgia black farmers reported rotating their crops, compared to 40 percent of the Georgia white farmers but the pattern was reversed in the other states. Only 17 percent of the black Alabama producers indicated they used crop rotation. Frequency of rotation also varied significantly by state and race. Most respondents indicated that their crop rotation cycle varied from year to year. Inclusion of legumes in rotations differed statistically by race and state. Whites were more likely to include legumes in their rotations in each state, but only 10 percent of black Alabama operators did so. I NTEGRA TED P EST M ANAGEMENT Familiarity with integrated pest management (IPM) varied significantly by race and state, as shown in Table 9. About half of the sample was not familiar with IPM. Less than eight percent of the overall sample indicated that they were very familiar with IPM as a means for controlling weeds, insects, and other threats to crop yield. Black farmers were less familiar with IPM than white farmers. Black Alabama farmers were most unfamiliar with IPM compared to other categories of producers. About a third of the farmers believed that IPM would be practical on their operation, but more whites in each state said that it was not very practical. About three-quarters of the black operators had no opinion. Only a small number of respondents reported implementing any pesticide practices. Georgia white farmers reported using more pesticide management practices than any other category of producer. 22 ALABAMA AGRICULTURAL EXPERIMENT STATION T ABLE 9. I NTEGRA TED P EST M ANAGEMENT P ERCEPTIONS BY R ACE SMALL AND L IMITED R ESOURCE F ARMERS , 2000 All % —Alabama— White Black % % AND S TATE , —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % 53 42 5 12.2* 23.0** 74 11 15 9.7* 1.1 How familiar with integrated pest management (IPM) are you? Not at all familiar 49 46 64 33 51 40 Somewhat familiar 45 45 33 54 44 54 Very familiar 7 9 3 13 5 6 Is IPM practical on your farm? No opinion 31 62 Not very practical 37 22 It would be good 32 16 75 12 13 48 28 24 70 12 18 55 31 14 What are the main reasons you would use IPM on your farming operation? Reduces use 8 10 5 11 11 10 6 of pesticides Increases crop yields 8 7 9 15 6 5 8 per acre Better control of 7 7 6 9 10 5 8 insects and other pests Lowers production 3 2 2 6 3 4 3 costs Improves water 2 1 3 2 3 2 1 quality Maintains soil fertility 1 0 0 2 1 1 1 N/A What pesticide practices have you implemented on your farm? Apply pesticides 10 12 5 18 13 6 as needed Use lowest possible 6 5 3 11 8 6 application rate Calibrate application 5 6 1 14 5 4 equipment Use different 5 3 4 10 5 5 pesticides to reduce pest resistance Use pesticides 5 4 3 10 7 2 less harmful to beneficial insects Keep records 4 7 1 9 5 3 on pesticides used, rates, and applications Train workers 2 4 1 3 3 0 to properly handle and apply pesticides 9 4 3 2 4 3 1 N/A N/A N/A continued CORE CONSERVATION PRACTICES 23 T ABLE 9, CONTINUED . I NTEGRA TED P EST M ANAGEMENT P ERCEPTIONS BY R ACE AND S TATE , S MALL AND L IMITED R ESOURCE F ARMERS , 2000 All % —Alabama— White Black % % —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % What are the main problems you might have with IPM on your operation? Chemicals are 6 4 5 5 8 5 7 too expensive Crop scouting is 4 2 1 7 5 5 3 too expensive Information on 2 2 1 3 1 4 2 “how to do it” not available Equipment needed 2 3 1 1 4 0 3 for IPM costs too much Reliable crop scouts 2 3 3 3 1 0 1 not available IPM takes too 1 1 0 3 3 1 0 much time Tried IPM and 0 0 0 0 0 0 1 it didn’t work for me N/A Number *p < .05 **p<.01 830 137 154 118 116 129 176 N/A About eight percent of the sample said that the main reason for using IPM was that it reduced the use of pesticides, and a similar proportion thought it increased crop yields per acre. Seven percent felt that it provided better control of insects and other pests. The latter reason was particularly important for black farmers in Georgia. The main problems associated with IPM pertained to the expense of the chemicals and the costs of crop scouting. Overall, less than six percent reported any single problem. I NTEGRA TED P EST M ANAGEMENT A DOPTION Table 10 shows regression analysis of IPM adoption variables on selected farm and individual characteristics. The data suggest that farmers with more education were more familiar with IPM and had actually adopted more IPM measures than farmers with less education. Age was not related to the IPM adoption variables. Farmers with more farm sales were more familiar with IPM and gave more reasons for using IPM. Farmers who worked more days off the farm adopted more IPM practices, but the number of days the spouse worked off the farm was negatively related to the number of IPM practices adopted. Those who raised row crops saw IPM as more practical, indicated more reasons for using IPM, and had actually implemented more IPM practices on their farms. 24 ALABAMA AGRICULTURAL EXPERIMENT STATION Farm sales as a percent of total income predicted the four IPM adoption variables. Farmers who were more dependent on farm income were more aware of IPM, gave more reasons for using it, and had actually implemented more IPM practices on their farms. The background and farm characteristics explained about 12 percent of the variation in the awareness and adoption variables, but less of the practicality and reasons variables. C ONSERV ATION B UFFERS Familiarity with conservation buffers (CB) varied markedly between black and white farmers, Table 11. Between 10 and 14 percent of the black farmers indicated that they were very familiar with the concept while between 17 and 31 percent of the white farmers indicated familiarity. More whites than blacks reported using grass filter strips on their farms. Thirty percent of white Alabama farmers used grass filter strips compared to seven percent of black Georgia farmers, who used filter strips the least. More white farmers than black farmers used all the various kinds of conservation buffers. The perceived practicality of CB varied significantly by race. Whites consistently viewed CB as more useful than black farmers. Alabama white farmers had the highest rating at 46 percent but only 25 percent of the black farmers in Georgia thought CB to be useful on their farm. T ABLE 10. R EGRESSION A NALYSIS OF I NTEGRA TED P EST M ANAGEMENT A DOPTION V ARIABLES ON S ELECTED F ARM AND I NDIVIDUAL C HARACTERISTICS , SMALL AND L IMITED R ESOURCE F ARMERS , 2000 ————Integrated pest management———— Familiarity Practicality Reasons Practices Formal education Age Total gross value of sales Your outside work Spouse outside work Land Row crops farmed Livestock raised Poultry raised Fruits and vegetables raised Government assistance payments received Farm operator’s gender Race Farming reciepts as percent of total income R2 Adjusted R2 F-value *p<.05 ** p<.01 0.108** 0.079 0.113* 0.066 0.055 0.098* 0.085 -0.123* 0.008 0.028 -0.070 -0.040 -0.097* 0.125** 0.145 0.124 7.003** 0.037 0.005 0.014 0.072 -0.062 -0.012 0.207* -0.008 -0.033 -0.015 -0.004 0.069 0.141** 0.095* 0.072 0.049 3.187** 0.078 0.057 0.098* 0.091 -0.049 0.001 0.206* -0.073 -0.048 0.033 -0.024 0.049 0.039 0.151** 0.119 0.098 5.583** 0.101* 0.015 0.082 0.137* -0.099* 0.066 0.196* -0.065 0.002 0.035 -0.055 0.029 0.010 0.190** 0.145 0.125 7.027** CORE CONSERVATION PRACTICES 25 More than 41 percent of the Alabama white respondents identified reducing soil erosion as the main reason to use CB, but only 18 percent of the Georgia black farmers did so. Similar patterns of difference were found for protecting soil and water from runoff and the creation of habitat for birds and animals as reasons for using CB. The main perceived problem with CB was that they take too much land out of production. There were no consistent differences by race, but white farmers were TABLE 11. C ONSERV ATION B UFFER PERCEPTIONS BY RACE AND STATE, SMALL AND LIMITED RESOURCE F ARMERS , 2000 All % —Alabama— White Black % % —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % 22 61 17 41 47 11 8.1 Which CB are currently used on your operation? Grass filter strips 14 30 8 14 Grass or shrubs planted on land that erodes 8 12 8 10 Grass waterways 8 22 5 9 Trees or shrubs planted for windbreaks 8 11 8 8 Contour buffer strips 4 6 3 3 Other 0 1 0 1 None 4 4 4 9 Are CB practical on your farm? No opinion 44 32 They would be useful 33 46 Not very practical 23 22 7 9 3 10 2 0 3 23 7 9 6 6 0 2 10 0 3 0 5 0 2 N/A 56 26 18 31 36 34 51 25 24 37 39 24 55 26 19 4.5 What are the main reasons you would use CB on your farm? Reduce soil erosion 26 41 19 25 18 Protects soil and water from runoff 21 30 14 20 17 Supports more birds, animals, etc. 8 12 5 14 7 Reduces pollution 5 4 4 7 5 Promotes more hunting and fishing 4 4 4 5 5 Makes the area look nicer 3 4 4 3 5 Other 0 0 0 1 0 34 26 10 8 6 4 0 21 18 6 3 2 2 0 N/A N/A continued 22.1** N/A 31.7** How familiar with conservation buffers (CB) are you? Not at all familiar 32 22 40 27 35 Somewhat familiar 51 47 46 51 55 Very familiar 17 31 14 22 10 26 ALABAMA AGRICULTURAL EXPERIMENT STATION T ABLE 11, CONTINUED . SMALL All % C ONSERV ATION B UFFER P ERCEPTIONS BY R ACE AND L IMITED R ESOURCE F ARMERS , 2000 AND S TATE , —Alabama— White Black % % —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % What are the main problems with CB on your farm? Takes too much land out of production 8 12 6 6 Costly to build and maintain buffers 8 12 5 10 Difficult to farm around buffers 7 10 3 11 “How to” information not available 4 4 5 3 Other 1 2 1 1 Tried buffers and they didn’t work 0 0 0 0 Number *p < .05 **p<.01 830 137 154 118 10 6 6 2 1 0 116 14 11 11 5 1 0 129 5 9 6 5 1 0 N/A 176 N/A more likely to cite most of the problems. The option to indicate that they had tried buffers and they did not work was provided in the questionnaire, but was not selected by any respondent. C ONSERV ATION B UFFER A DOPTION Table 12 shows regression analysis of conservation buffer adoption variables on selected farm and individual characteristic. Education was a significant predictor of the operators’ familiarity with conservation buffers, the number of reasons for using CB, and the number of practices that had been adopted. Older farmers were less convinced of the practicality of using CB. Farmers with more days of outside work had higher scores on each of the CB adoption variables. Farmers with more acres of land gave more reasons for using CB. Those who raised fruits and vegetables were more likely to be familiar with CB and to give more reasons for using CB. Similarly, those who received more government payments were more familiar with CB. Black farmers consistently had lower scores on three of the adoption measures. Black operators were less familiar with CB, gave fewer reasons for using them, and had actually implemented fewer CB measures on their farms. Neither gender nor dependence on farm income was related to any of the CB adoption measures. CORE CONSERVATION PRACTICES 27 The four equations explained a significant proportion of the variation in each CB adoption variable. The adjusted R2 value ranged between 7.3 for practicality to 11.8 for the number of reasons given for using CB. C ONSERV ATION P ROGRAM P ARTICIP ATION Approximately 30 percent of the sample reported having conservation plans for their farms, Table 13. The differences by race and state were not statistically significant. Of those with conservation plans, about 26 percent indicated that the plan was fully implemented, and another 27 percent indicated it was three-quarters completed. Differences by race were statistically significant. Whites consistently reported higher levels of conservation plan completion in each of the three states. A fourth of the black farmers said their plans were less than 25 percent completed. The Conservation Reserve Program was the most often cited government program in which respondents participated. Ten percent of Alabama black farmers participated in the Forestry Incentive Program compared to five percent of the Alabama white farmers. The rates of participation in the different programs varied widely across states and race categories, but were most nearly equal in Georgia. T ABLE 12. R EGRESSION A NALYSIS OF C ONSERV ATION B UFFER A DOPTION V ARIABLES ON S ELECTED F ARM AND I NDIVIDUAL C HARACTERISTICS , SMALL AND L IMITED R ESOURCE F ARMERS , 2000 ——————Conservation buffers—————— Familiarity Practicality Reasons Practices Formal education Age Total gross value of sales Your outside work Spouse outside work Land Row crops farmed Livestock raised Poultry raised Fruits and vegetables raised Government assistance payments received Farm operator’s gender Race Farming reciepts as percent of total income R2 Adjusted R2 F-value *p<.05 ** p<.01 0.109** -0.034 0.09* 0.075 0.063 0.079 0.147* 0.172* 0.004 0.226** 0.133* 0.035 -0.114* 0.043 0.117 0.096 5.495** 0.066 -0.113* -0.034 0.146* -0.029 0.098 -0.093 -0.080 0.074 -0.068 0.004 -0.025 -0.040 -0.012 0.073 0.041 2.293** 0.088* -0.065 -0.007 0.170** 0.026 0.158** 0.102 0.169* 0.079 0.168* 0.090 0.011 -0.100* -0.045 0.118 0.096 5.506** 0.140** -0.069 -0.005 0.131** 0.038 0.081 0.000 0.036 0.092* 0.069 0.060 0.016 -0.158** -0.026 0.112 0.091 5.215** 28 ALABAMA AGRICULTURAL EXPERIMENT STATION The participation rate in the Environmental Quality Incentive Program was highest among Alabama black farmers, at 11 percent. Georgia black farmers had the highest participation rate in the Farmland Protection Program at nine percent. Ten percent or less participated in the Wildlife Habitat Incentive Program, but six percent of Georgia black farmers were in the Wetland Reserve Program, a rate twice that for the other states. A tenth of the respondents indicated participation in the wildlife and wetland programs. Less than a fifth of the respondents cited a lack of understanding of program requirements as a reason for not participating in the various conservation programs that were mentioned to them. Mississippi white farmers were least likely to indicate lack of understanding, at 11 percent, but 23 percent of the Mississippi black farmers cited a lack of understanding as a reason for not participating. Half the sample had no contact with Natural Resources Conservation Servie (NRCS) in the past year, but differences by race and state were not statistically significant. Mississippi farmers reported the most frequent contacts. Around 40 percent indicated contacts through visits to county offices, a fifth by letter. Georgia had the highest rates of no contact. Forty percent of Mississippi white farmers had visited an NRCS office compared to 20 percent of Georgia black farmers who had done so. There were no other consistent patterns of difference by race or state. Mississippi black farmers were most likely to have received a letter from NRCS (23 percent). White farmers were more likely to report phone contacts in Alabama and Georgia (around 20 percent), but farmers were slightly more likely to report phone contact with NRCS in Mississippi. Respondents were asked to indicate their satisfaction with the information or services received from NRCS. Overall, 80 percent were very or somewhat satisfied with this conservation agency. Whites were more satisfied than blacks in Alabama and Mississippi. Seventeen percent of Alabama black farmers were dissatisfied compared to seven percent or less in all the other state or race categories. D ETERMINANTS OF NRCS C ONTACT Table 14 regresses conservation plan and NRCS contact variables on small and limited resource farm characteristics. Those with more education, more land, and higher levels of government payments were more likely to have a conservation plan, to have a greater proportion of it implemented, to have more previous contacts with NRCS, and to express higher levels of satisfaction with the services they received from the agency. Farmers with higher gross sales had implemented more of their conservation plans, had more contacts with NRCS, and were more satisfied with the agency. Men and those with income from row crops were more likely to have a conservation plan and to have more of it implemented. Those more dependent on farming for income were more likely to have a conservation plan and to indicate that they had more of it implemented. They also had more contacts with NRCS, but were not more satisfied with the agency’s services. CORE CONSERVATION PRACTICES 29 T ABLE 13. C ONSERV ATION P ROGRAM P ARTICIP ATION BY R ACE SMALL AND L IMITED R ESOURCE F ARMERS , 2000 All % —Alabama— White Black % % AND S TATE , —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % 53 33 14 54 33 13 59 28 13 2.5 3.5 Do you have a conservation plan for your farm? No 57 53 67 54 Yes 30 34 24 29 Don’t Know 13 14 9 16 About how much of the conservation plan has been implemented? Less than 25% 16 4 30 6 29 7 25% 10 9 16 9 8 12 50% 21 17 11 24 32 17 75% 27 30 27 35 18 29 100% 26 39 16 26 13 36 Are you currently participating in any conservation programs? Conservation Reserve 23 22 13 29 32 19 Program (CRP) Forestry Incentive 11 5 10 9 9 12 Program (FIP) Environmental Quality 8 5 11 4 7 5 Incentive Program (EQUIP) Farmland Protection 6 3 6 5 9 5 Program (FPP) Wildlife Habitat 10 4 2 3 4 4 Incentive Program (WHIP) Wetland Reserve 3 1 3 3 6 2 Program (WRP) Why are you not participating in EQIP? Don’t understand 16 17 14 program requirements Other reasons 7 7 6 Cannot afford this 7 6 5 particular program EQIP excludes 4 0 6 poorer farmers Application takes 3 1 3 too much time and paperwork I don’t like this 2 2 1 particular program EQIP is not flexible 2 1 1 My county is not 0 1 0 eligible 20 8 27 24 20 5.9 20 11 0 6 3 3 N/A N/A 25.0** 13 8 8 3 2 2 3 0 17 10 5 4 2 3 3 1 11 8 6 3 6 2 1 0 23 8 10 6 3 1 1 1 N/A N/A continued 30 ALABAMA AGRICULTURAL EXPERIMENT STATION T ABLE 13, CONTINUED . C ONSERV ATION P ROGRAM P ARTICIP ATION BY R ACE SMALL AND L IMITED R ESOURCE F ARMERS , 2000 All % —Alabama— White Black % % AND S TATE , —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % How often did you have contact with the NRCS during the past twelve months? No contact 49 48 51 51 58 43 45 1-2 times 24 28 22 25 21 25 23 3-4 times 15 13 15 14 12 17 14 5+ times 11 8 10 8 9 15 15 10.5 How was contact made with NRCS? No contact reported 49 48 Visit to an NRCS office 28 28 By letter 16 14 Received the NRCS 16 20 Newsletter Telephone 16 19 Someone from NRCS 7 7 visited my farm Heard an NRCS 4 3 employee speak at a meeting 51 24 12 19 14 9 5 51 29 9 12 20 8 2 58 20 17 7 12 6 5 43 40 20 21 15 5 2 45 30 23 16 15 9 8 N/A How satisfied were you with the information or services received from NRCS? Very satisfied 39 49 33 32 48 38 37 Somewhat satisfied 40 40 36 45 29 41 45 Neither satisfied or 14 9 15 16 19 15 12 dissatisfied Somewhat dissatisfied 4 3 10 5 2 1 4 Very dissatisfied 3 0 7 2 2 4 1 4.9 Number *p < .05 **p<.01 830 137 154 118 116 129 176 2.2 N/A 2.7 The farm and individual characteristics explained around 12 percent of the conservation plan variables but less than nine percent of the NRCS contact and satisfaction variables. Having a conservation plan is a linked qualification for many farm programs associated with crop production. Thus, those more dependent on crops and income from farming were more attentive to having a conservation plan. I NFORMA TION S OURCES Respondents were asked to rate a series of information sources on a fivepoint scale as to the importance of each source for making conservation decisions. Table 15 ranks the sources in terms of the mean importance of each item where a high score means more important. F-tests of analysis of variance indicate whether means differ significantly by race or by state. CORE CONSERVATION PRACTICES 31 T ABLE 14. R EGRESSION A NALYSIS OF C ONSERV ATION P LAN AND NRCS C ONTACT V ARIABLES ON S MALL AND L IMITED R ESOURCE F ARMERS , 2000 ———Conservation plan and NRCS contact——— Conservation Percent NRCS NRCS plan implemented contact satisfaction Formal education Age Total gross value of sales Your days of outside work Spouse days of outside work Land operated Row crops farmed Livestock raised Poultry raised Fruits and vegetables raised Government payments received Male Black Farm sales as percent of total income R2 Adjusted R2 F-value *p<.05 ** p<.01 0.210* -0.019 0.029 0.041 0.045 0.102* 0.149* 0.153* 0.009 0.151* 0.234** 0.071* 0.038 0.169* 0.140 0.117 6.106* 0.179* -0.020 0.098* -0.009 0.062 0.103* 0.186* 0.146* -0.005 0.099 0.233* 0.085* -0.023 0.135* 0.151 0.129 6.719** 0.158** -0.005 0.105* 0.073 0.033 0.077* -0.033 0.042 -0.007 0.086 0.164* 0.041 0.026 0.101* 0.109 0.086 4.636** 0.172* 0.017 0.156* 0.055 0.002 0.088* 0.080 0.085 -0.022 0.107 0.159* 0.025 0.003 0.062 0.112 0.088 4.757** The mean importance of the cooperative Extension agent as an information source varied significantly by race but not by state. Limited resource farmers consistently ranked the cooperative extension agent as the most important information source across states and race categories, except white Alabama farmers. This segment ranked extension as the second most important source. In each state, black farmers gave higher importance ratings to extension than white farmers. Farm magazines or newsletters were the next most important source. Again black farmers tend to give higher ratings to this source than white farmers, but the differences were not significant. The third most important information source was “another farmer or family member.” This source was particularly important for white farmers in Alabama— rating even higher than extension for that group, but there were no significant differences by state or race. NRCS was fourth ranked as an information source in the overall sample. Black farmers, particularly in Alabama and Mississippi, tended to give higher ratings to NRCS as a conservation information source but these differences were not statistically significant. Farm demonstrations and field days were ranked next. Media information was particularly important for black farmers in Mississippi and Alabama. The rated importance of these two information sources differed significantly across race categories. 32 ALABAMA AGRICULTURAL EXPERIMENT STATION TABLE 15. M EAN I MPORTANCE OF I NFORMA TION SOURCES BY RACE AND STATE, SMALL AND LIMITED RESOURCE F ARMERS , 2000 —Alabama— —Georgia— —Mississipi— All White Black White Black White Black mean mean mean mean mean mean mean ––F-ratio–– State Race How important is each source of information for making decisions about conservation practices? Cooperative extension agent Farm magazine or newsletter 3.6 3.4 3.5 3.5 3.6 3.3 3.7 3.7 3.3 3.4 3.5 3.1 3.1 3.0 3.6 3.3 3.1 3.1 3.4 3.2 3.3 3.2 3.6 3.6 3.3 3.4 1.0 1.3 0.5 0.5 3.1* 2.6 0.5 1.5 Another farmer 3.3 or family member Natural Resources 3.3 Conservation Service (NRCS) Farm demonstrations 2.8 and field days Newspaper, radio, or television Pesticide company reps or dealer 2.7 2.4 2.8 2.3 2.3 2.3 2.2 1.9 137 3.1 3.0 2.4 2.5 2.3 2.1 154 2.6 2.2 2.2 2.0 1.9 1.5 118 2.8 3.1 2.4 2.2 2.2 2.2 116 2.4 2.4 2.4 2.0 2.2 1.8 129 3.0 3.1 2.5 2.7 2.6 2.2 176 2.1 1.6 0.6 0.7 1.0 0.8 3.5* 11.7** 0.9 3.8* 1.6 2.9** A banker, community 2.3 leader or farm leader Private consultant 2.3 Internet 2.0 (World Wide Web) Number *p < .05 **p<.01 830 Newspapers, radio, and television were significantly more important as information sources for black farmers, but particularly so in Georgia and Mississippi. Differences between black and white farmers were wider on this item than on any other. Black farmers relied more heavily on the media for their conservation information. Pesticide company representatives, local leaders, and private consultants were respectively the next most important information sources as rated by the farmers. Black farmers consistently rated leaders as more important information sources than did white farmers, a pattern of differences that was statistically significant. Low importance was given to the Internet as a source of information, though blacks consistently rated it as more important than whites, a statistically signifi- CORE CONSERVATION PRACTICES 33 cant difference. Other research shows that less than10 percent of farmers have home access to the Internet, but the rate is much higher among farms with $500,000 or more in annual sales. I NFORMA TION M ODE Table 16 profiles preferences for receiving government information about conservation. The farmers were presented a list of possible information sources and asked to mark the ones they preferred. Respondents could check multiple items. The table rank orders the items in terms of overall percentage of those who selected it. About 64 percent of the sample indicated that printed materials such as bulletins, newsletters, and other publications was their preferred means of receiving information. There were no statistically significant differences by race or state. T ABLE 16. C ONSERV ATION I NFORMA TION P REFERENCES BY R ACE SMALL AND L IMITED R ESOURCE F ARMERS , 2000 All % —Alabama— White Black % % AND S TATE , —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % 74 63 3.1 0.4 How would you like to receive government information? Printed materials 64 62 68 61 60 such as bulletins, newsletters, etc. Direct contact with 41 Farm Service Agency (FSA) offices Group meetings or seminars 18 36 41 41 38 43 44 1.8 0.3 9 12 24 19 14 10 18 19 12 12 27 24 2.4 2.6 19.5** 14.4** At workshops 16 where I receive “hands on” training The news media 14 (radio, TV, newspaper) By free telephone 13 hotline (1-800 number) Websites on the Internet 10 7 12 10 4 6 3 16 14 9 9 11 2 13 8 7 6 3 0 26 18 11 11 8 3 12 11 13 2 5 2 15 14 9 7 7 1 11.2* 0.0 0.4 2.3 2.5 0.5 6.5 3.9 0.1 7.6* 6.1* 0.6 University specialists 7 Electronic media 7 (videotapes, CD-ROMs) Teleconference or 2 satellite broadcast at a central location Number *p < .05 **p<.01 830 137 154 118 116 129 176 34 ALABAMA AGRICULTURAL EXPERIMENT STATION Farm Service Agency offices were the next most frequently cited, by 41 percent of the sample. There were no significant differences by race or state. Black farmers preferred group meetings or seminars more than whites, a statistically significant difference. Similarly, blacks preferred workshops more than whites did. The news media was preferred as an information source by black Georgia farmers. News media preference differed significantly by state. There were no differences in preference for toll-free hotlines or websites. Black farmers did prefer university specialists as information sources more than white farmers. They also preferred electronic media for home use such as videotapes more than white farmers. Both differences were statistically significant. Whites preferred news media more than blacks, a statistically significant difference. L AND AND W ATER R ESOURCES Getting conservation on the ground is a difficult task for public agencies serving a diverse population of resource owners with many different orientations and capabilities of following recommended land treatment strategies. Table 17 suggests that the many small farm operators in the region control a substantial amount of land resources. Acres own differed statistically by race and state, but particularly by race. More white farmers reported owning larger acreages in each state. Most of the respondents in our sample had between 50 and 179 acres, although 41 percent of Alabama black-owned farms were between 10 and 49 acres in size. More Georgia white farmers had larger holdings and more Mississippi black farmers owned farms less than 50 acres in size. Nine percent owned no land. Slightly more blacks than whites in each state owned no land. A third of the sample rented land from other farmers, but the pattern of differences was not statistically significant. More Mississippi and Alabama black farmers rented land from others, but more Alabama farmers of both races rented land from others than did farmers in other states. Roughly 10 percent of the small and limited resource farmers rented land to others, although Georgia farmers of both races were slightly more likely to rent out land. This pattern was statistically significant by race. The net acres operated were computed by summing the acres owned plus the acres rented from others, minus the acres rented to others. The modal category for land operated was 50 to 179 acres except for Georgia black operators who most frequently cited 10 to 49 acres as the category of net acres operated. Differences by race and state were each significant, but the largest contrasts were between races. The last item in the table shows the water bodies found on the respondents’ farm, rank ordered in the frequency that the item was selected in the overall sample. Creeks or streams were the most frequently reported on-farm water resource. Nearly half the farmers had a creek or stream on their property, but about 30 percent had no water body or watercourse on their land at all. Forty-one percent of the Georgia black farmers said they had no water bodies on their land, but only 17 percent Mississippi white CORE CONSERVATION PRACTICES 35 T ABLE 17. L AND AND W ATER R ESOURCES BY R ACE AND S TATE , SMALL AND L IMITED R ESOURCE F ARMERS , 2000 All % —Alabama— White Black % % 11 8 41 34 5 1 —Georgia— —Mississipi— –Chi-square– White Black White Black State Race % % % % 6 4 13 46 26 5 8 6 33 39 11 3 9 2 16 48 23 2 12 12 28 38 9 1 26.6* How many acres do you rent from others, included land used rent free? None 60 57 56 68 67 62 56 1-9 acres 4 4 3 5 3 3 3 10-49 acres 17 17 23 10 20 16 15 50-179 acres 16 19 14 11 8 15 23 180-499 acres 3 2 4 5 2 3 3 500 acres or more 1 1 0 1 1 2 0 15.3 How many acres do you rent to others? None 90 91 97 1-9 acres 1 2 0 10-49 acres 3 2 1 50-179 acres 6 5 1 180-499 acres 0 0 0 What are the net acres you operate? 1-9 acres 4 1 4 10-49 acres 26 22 39 50-179 acres 48 50 47 180-499 acres 19 20 9 500 acres or more 3 6 1 Waterbodies on farm None Creek/stream Drainage ditch Wetlands Swamp Lake Waterway River Number *p < .05 **p<.01 83 1 4 12 0 89 2 3 5 1 91 0 2 8 0 95 1 4 1 0 17.2 3 13 51 27 6 2 42 38 15 3 2 16 47 32 3 7 23 55 14 1 19.6* 57.2** 31 44 23 10 9 8 3 3 830 30 45 21 7 7 9 2 6 137 30 47 24 14 9 7 4 1 154 29 42 13 19 12 17 8 3 118 41 35 12 9 10 6 1 1 116 17 61 28 10 10 9 1 3 129 30 35 35 6 5 5 3 2 N/A 176 N/A 17.7* 6.1 61.1** How many acres do you own? None 9 6 1-9 acres 7 7 10-49 acres 27 26 50-179 acres 40 39 180-499 acres 15 17 500 acres or more 3 5 36 ALABAMA AGRICULTURAL EXPERIMENT STATION farmers said they had none. More than a third of the Mississippi black farmers reported drainage ditches on their farms, the highest proportion across the states. CONCLUSIONS The first objective of this study was to profile the core conservation practices utilized by small and limited resource farmers in Alabama, Mississippi, and Georgia. Research shows that conservation tillage is familiar to three-fourths of the farmers in each state, although not at all familiar to a large proportion of black farmers. A fifth of all the farmers viewed conservation tillage as not practical on their farms. A fifth cited weeds and herbicide costs as main CT problems. These data suggest that many farmers have been reached by the efforts of NRCS, extension, and other public agencies, but they also suggest that many have not been supplied with the CT solutions that fit their farm situations. A lack of how-to information was more often cited by black farmers as a barrier to performing conservation techniques on their operations. Nutrient management awareness and implementation is probably best indicated by the regular practice of soil testing on a farm. Soil testing is a fundamental step in economically sound and environmentally responsible farming. A third of the sample never engaged in soil testing. Given that seven of eight small and limited resource farmers used commercial fertilizer, and that about one in five used broiler litter on the land, the information from a soil test is a basic part of making nutrient management decisions. Reaching the unaware and the uncommitted with the basic precepts of land management will require an extended effort of outreach and technical support. Integrated pest management is not a widely understood concept among small and limited resource farmers in Alabama, Georgia, and Mississippi. About half the sample was not familiar with the term and only a third thought it would be good for their farm operation. Alabama black farmers were most unfamiliar with this technique. Conservation buffers represented the most traditional and well-known category of soil and water protection interventions. Nonetheless, a third of the farmers were not familiar with the term and only a third thought these measures would be useful on their farm. Alabama producers were most familiar with this class of interventions and most convinced of their usefulness. Another objective of the study was to compare the conservation practices and perceptions of black and white small and limited resource farmers in Alabama, Georgia, and Mississippi. Black and white limited resource farmers who participated in the study differed in a number of basic ways. More black farmers had less than a high school education and more white farmers tended to grow row crops and engage in other more intensive farm enterprises. Many of our survey respondents of both races had college educations and advanced degrees, pointing to the rapidly growing segment of part-time, hobby, and lifestyle farm residents that may have felt and unfelt needs for guidance on land treatment strategies. The challenge to public agencies is to provide timely and appropriate responses to the felt needs CORE CONSERVATION PRACTICES 37 for technical assistance. In addition, the agencies must find a way to stimulate a demand for conservation assistance by increasing awareness of the practical tools that are available for protecting soil resources and water quality. The data also pointed to the diversity within the small and limited resource farm segment of the farm population. Some small and limited resource farmers were poor; some were pensioned; some were prosperous by other means. Any initiatives to expand adherence to core conservation principles and increase participation in conservation programs must begin by recognizing this diversity. A third objective was to identify perceived barriers and disadvantages to the implementation of core conservation practices. Each set of core conservation practices has obstacles to implementation by the full gamut of small and limited resource farms. Some obstacles reflect defects and limits in the outreach mechanisms of the public agencies. Some reflect limits in the applicability and fit of the recommended practices on each individual small and limited resource farm. Other obstacles to implementation bear on the interests and capabilities of the individual farm operator. Lifecycle stage, personality, financial capability, and technical capacity all shape an individual farm operator’s ability to consider and use the interventions recommended by NRCS and other public agencies. Nonetheless, the data revealed a large segment of operators who had no contact with NRCS or other public agencies. It was not that core conservation practices have been tried and found wanting on these farms; rather, they have been found wanting to be tried. It was a statistical reality that the overall number of farms tended to decline in the past decades, but now the number of small and limited resource farms are increasing due to better counting methods and the growing number of part-time, lifestyle, and hobby farms. Marketing core conservation to small and limited resource farmers will require mass mailings and other methods to reach farmers not regularly participating in NRCS and other public agency land and water programs (Lovejoy, 1999). There are myriad of reasons why individual producers have not participated in programs. Mass approaches may lead some to seek NRCS technical assistance, but others will require one-on-one personal interaction to realize the possibilities of core conservation principles on their land. The fourth objective of the study was to describe patterns of information source utilization and preferences among small and limited resource farmers. The data suggested that farmers remain wedded to printed materials as a fundamental source of reference information for their conservation decisions. Although information technology is rapidly changing, most small and limited resource farmers will require simple and direct technical materials to implement core conservation measures. The demand for the materials is clearly present, but farmers may not be aware of the actual supply of information that is available or how to access it. Targeted mailings to small and limited resource producers might provide publication lists highlighting the information that is available upon request (Napier et al., 2000). 38 ALABAMA AGRICULTURAL EXPERIMENT STATION It is also clear that NRCS must rely on the goodwill and respect that farmers have for other farm agencies, particularly the Cooperative Extension Service, that are already well-regarded and familiar to farmers. 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