February 2005
Volume 43 Number 1

Research in Brief

Iowa Producers' Perceived Benefits and Obstacles in Marketing to Local Restaurants and Institutional Foodservice Operations

Mary B. Gregoire
Professor and Chair
mgregoir@iastate.edu

Susan W. Arendt
Lecturer
sawarendt@aol.com

Catherine H. Strohbehn
Adjunct Assistant Professor
cstrohbe@iastate.edu

Apparel, Educational Studies, and Hospitality Management
Iowa State University
Ames, Iowa

Introduction

Alternative marketing of produce by local growers through direct sales to schools and restaurants can increase producers' profits (U.S. Department of Agriculture, 2001). The Leopold Center for Sustainable Agriculture in Iowa has provided financial support for several projects to find ways to better link local growers with restaurant and institutional foodservice operations (see http://www.leopold.iastate.edu). These efforts have resulted in limited sustained local buying once grant funding ended.

Research has been published from the perspectives of foodservice buyers and operators regarding the purchase of locally grown products (Institute of Agriculture and Natural Resources, 2003; Gregoire & Strohbehn, 2002). Chefs of local restaurants and foodservice operations have recognized the benefits of local purchasing, including higher/better quality and fresher product (Institute of Agriculture and Natural Resources, 2003). Gregoire and Strohbehn (2002) found that Midwest school foodservice directors perceived the benefits to purchasing locally as good public relations; aiding the local economy; and ability to purchase smaller quantities and fresher food. In another study (Institute of Agriculture and Natural resources, 2003), chefs indicated that they purchase locally because it supports local producers and they perceive food is of better quality and fresher.

Barriers to purchasing locally also have been cited by buyers in different foodservice sectors. Lack of year-round availability, adequate quantity, and quality products have been noted as obstacles and concerns by foodservice managers who purchase locally grown produce (Gregoire & Strohbehn, 2002; Cottingham, Hovland, Lenon, Roper, & Techtmann, 2000; Gregoire et al., 2000).

Despite these known works identifying benefits and barriers by foodservice buyers, no published work has empirically assessed producers' perceptions of marketing to local restaurants and other foodservice operations. Therefore, the objective of the study reported here was to determine, in one state, local food growers'/producers' perceptions of the benefits and obstacles of marketing and selling to local foodservice operations, including restaurants, schools, hospitals, and nursing homes. The researchers believe these data, combined with the foodservice operator perception data, could help identify strategies for more successful sustained local purchasing by foodservice buyers.

Methods

Previous work by Strohbehn and Gregoire (2001, 2002, 2003) was used for the development of a questionnaire to assess the benefits and obstacles of selling to local foodservice operations. Questionnaire items had been found to be valid and reliable (Strohbehn & Gregoire, 2002). The questionnaire included a combination of multiple choice and open-ended questions. The questionnaire collected perceptions of benefits and obstacles of direct marketing to restaurants and foodservice operations, as well as general information about the growers/producers and their operations.

Benefits and obstacles were rated on a 5-point Likert-type scale, ranging from "No Benefit"/"No Obstacle"(coded as 1) to "Strong Benefit"/"Strong Obstacle"(coded as 5). Nineteen items were included in the "benefit" section, and 18 in the "obstacle" section. Space was allowed for unlisted benefits and obstacles.

General information collected included questions regarding amount and type of produce sold, production practices, sales venues, sources of information producers used, and reasons why the producer had never sold or stopped selling to foodservice operations. For those who had sold to foodservice operators, questions about what items are sold, how long they had sold, and average delivery distance were asked. The questionnaire was pilot tested and validated using a group of four members of a local Iowa producer group and three university faculty members.

The questionnaire was mailed to a total of 560 Iowa producers. Names were gathered from the 2002 Fruit and Vegetable Growers Directory (Iowa Department of Agriculture), the 2002 Iowa Family Farm Meats Directory (Iowa Department of Agriculture), and a list of local growers/producers provided by Practical Farmers of Iowa. Duplicate names were eliminated prior to mailing. No follow-up was done after the initial mailing due to limited funding.

The SPSS version 11.0 (Norusis, 2001) statistical software was used for all data analyses. Frequencies were calculated for all variables. Means and standard deviations were calculated for ratings of perceived benefits and obstacles. Analysis of variance was utilized to compare perceived benefits and obstacles between producers who had sold to local foodservice operations and producers who had not.

Results and Discussion

A total of 195 (35%) producers responded to the questionnaire. Fourteen questionnaires were not used in data analysis due to excessive missing data.

Characteristics of Growers

Production practices used by surveyed Iowa producers were as follows: 31% conventional methods, 31% conservative pesticide and antibiotic use, 27% sustainable practices, 17% other practices, and 9% organic practices. Producers indicated that tomatoes, onions, and peppers were the most frequent types of produce sold (Table 1). Meat items, such as chicken, ground beef, ground pork, and ham, were items least sold. This may be due to uncertainty by foodservice buyers regarding regulations of purchasing these products (Strohbehn & Gregoire, 2003).

Several producers had sold (27%) or were currently selling (25%) their products to local foodservice operations. Producers reported using: workshops (34%), producer organizations (25%), Extension publications (24%), arranged meetings with buyers (24%), and networks of food buyers (13%) to help learn more about selling to foodservice institutions.

The producers' main marketing channels were direct sales to consumers (82%) and the farmer's market (74%). Additional marketing channels included restaurants and institutional foodservices, Community Supported Agriculture (CSA), wholesale, and cooperative (Table 2).

Almost half of the Iowa producers (44%) who responded had never sold to local foodservice operations. Those producers who had never sold to a local operation indicated that some buyers were not receptive and/or they could not produce the quantity, year-round availability, color, and size of produce needed by the buyer (Table 3). Additionally, their own lack of knowledge about regulations and the same lack of knowledge by purchasers were given as reasons for not selling to restaurants or other foodservice operations.

Benefits to Direct Marketing and Selling

Most statements received a mean rating of three or greater, suggesting that producers perceived them as beneficial to selling to a local restaurant or institutional foodservice operation (Table 4). Items rated as strongest benefits were: supporting local farmers, providing fresher food for the customer, and a shorter distance for the food to travel. No statistically significant differences were noted in perceived benefits of producers who currently sell or had sold, and those who had never sold to a local foodservice operation. Producers currently selling and producers who had sold were grouped for comparison purposes as both groups had experience selling to foodservice operations.

Obstacles to Direct Marketing and Selling

Producers in this study indicated year-round availability, lack of a dependable market, ability to change price for a product, communication with the food buyer, and ability to produce needed quantity as major obstacles to selling to local foodservice operations (Table 5). While producers perceived year-round availability to be a major obstacle (m>4.0), all other obstacles were rated less than 4.0 on the 5-point scale. Almost half of the obstacle statements were rated less than 3.0 indicating a little to slight obstacle.

Ratings of perceived obstacles by producers who currently sell or have sold to foodservice operators in the past differed significantly from ratings of those who had never sold for three obstacle statements: local and state regulations, knowledge of restaurant's/foodservice's purchasing practices, and ensuring a safe food supply. For all three statements, producers who had never sold to local foodservice operations perceived these to be more of an obstacle than other producers did.

Comparison with Other Studies

In contrast to results from this study, Colorado producers appear to utilize wholesale marketing channels more frequently. Starr et al (2002) reported that 38% of Colorado farmers surveyed sold all of their produce to middlemen such as elevators, distributors, brokers, or packing sheds. Farmers who direct marketed their products perceived selling local and using environmentally friendly practices as significantly more important than farmers who do not direct market. Tubene and Hanson (2002) found that Pennsylvania wholesale could be successful for small farmers as an alternative marketing strategy. Still, common concerns identified by farmers included: produce unavailability, limited volume, and price fluctuation.

Foodservice buyers responded similarly to producers in this study when asked why their establishment decided to purchase locally. Supporting local producers, better quality, and fresher products were indicated as the top three reasons for purchasing locally (Institute of Agriculture and Natural Resources, 2003). Similarly, institutional and restaurant buyers reported fresher food, good public relations, retained value to local economies, and higher quality food as important benefits (Gregoire & Strohbehn, 2002; Strohbehn & Gregoire, 2001).

Starr et al. (2002) noted that there were differences in the perceptions held by buyers for local restaurants and buyers for institutions. Important factors for local restaurant buyers already buying locally included, in order of most important to less important, freshness of produce, dependable supply, and supporting local businesses. Restaurants not buying locally indicated the same top two important factors as freshness and dependable supply; however, the third most important factor was price. Institutions indicated freshness of produce, dependable supply, and price as most important.

Conclusions and Recommendations

Limitations are recognized when reviewing these study results. The sample included few producers selling meat products and many selling produce; this may not be representative of other regions in the country. The sample provided valuable information about producer perceptions in Iowa; however, producers in other states may not perceive benefits and obstacles similarly. Although a respectable questionnaire return rate was achieved (35%), generalizability of the data is limited.

Iowa producers of fruits, vegetables, and meats who participated in this study perceive few obstacles and many benefits to selling to local foodservice operations; however, only about one-fourth of the producers surveyed currently sell to local restaurants and foodservices. Responding producers were more likely to sell directly to individual consumers or through farmer's markets. Govindasamy, Italia, Zurbriggen, and Hossain (2003) reported profit satisfaction of New Jersey producers through direct marketing at farmer's markets. Although profit margins were not studied in these Iowa producers, profitability is understandably a consideration when selecting markets for products. Iowa producers indicated that ability to change desired product price was an obstacle when selling to restaurants and foodservice operations.

Foodservice buyers in Iowa identified ordering from multiple vendors and payment procedures as obstacles when purchasing food from local sources (Strohbehn & Gregoire, 2002). Findings from a national survey indicated that 71% of chefs reported that their establishment had purchased locally grown food from farmers' markets but their preference would be to purchase foods direct from the farmer, not at farmers' market (Institute of Agriculture and Natural Resources, 2003). The elimination of the "middle man" in direct marketing prevents local food products from entering multiple market channels but appears to be perceived as a an obstacle to buying locally by some foodservice operators (Strohbehn & Gregoire, 2003).

The role of Extension in educating producers to sell to various types of foodservice operations and in helping producers organize into producer organizations may be key. About one-fourth of the participants in this study used Extension publications to learn about selling to foodservices. More widespread coverage of information that focuses on buyer receptiveness, how to price products, regulations, and buyer-seller relationships may be beneficial to local growers and producers.

Additionally, formation of producer groups when selling to foodservices could eliminate some of the perceived barriers by buyers including ordering and payment difficulties. A process to organize producer groups is offered by Lichtkoppler and Passewitz (1992). Extension publications to assist with building linkages between local producers and foodservice operators can be found at <http://www.extension.iastate.edu/hrim/localfoods>.

Additional research is needed with a broader sample of producers to distinguish between characteristics of producers who sell to local foodservice operations and those who do not. Increased marketing to local foodservice operations requires a better understanding of the buyer-seller relationship. Future research should additionally focus on developing characteristics of effective buyer-seller relationships in specific sectors of the foodservice industry. Last, the perception of foodservice regulations as a barrier is of interest and worth further exploration.

Acknowledgments

The authors would like to acknowledge the work of Joy Kozar for her assistance in the survey distribution and data entry.

References

Cottingham, J., Hovland, J., Lenon J., Roper, T., & Techtmann C. (2000). Direct marketing of farm produce and home goods. Madison, WI University of Wisconsin Cooperative Extension Service, A3602. Available at: http://cecommerce.uwex.edu/pdfs/A3602.pdf

Govindasamy, R., Italia, J., Zurbriggen, M., & Hossain., F. (2003). Producer satisfaction with returns from farmers' market related activity. American Journal of Alternative Agriculture, 18(2), 80-86.

Gregoire, M. B., & Strohbehn, C. (2002). Benefits and obstacles to purchasing food from local growers and producers. Journal of Child Nutrition and Management [On-line]. 25. Available at: http://www.asfsa.org/childnutrition/jcnm/02spring/

Gregoire, M. B., Strohbehn, C., Huss, J., Huber, G., Karp, R., & Klien, S. (2000). Local food connections: From farms to schools. (Pamplet #: PM1853A). Ames, IA: Iowa State University Extension. Available at: http://www.extension.iastate.edu/Publications/PM1853A.pdf

Institute of Agriculture and Natural Resources. (2003). Approaching foodservice establishments with locally grown products. Lincoln, NE: Food Processing Center, University of Nebraska. Available at: http://www.foodmap.unl.edu

Iowa Department of Agriculture. (2002). Fruit and vegetable growers directory. Available at: http://www.agriculture.state.ia.us/fruitvegetable.asp

Iowa Department of Agriculture. (2002). Iowa family farm meats directory. Available at: http://www.agriculture.state.ia.us/meatdirectory1.htm

Lichtkoppler, F. R., & Passewitz, G. R. (1992). Starting new producer organizations. Journal of Extension [On-line], 30(1). Available at: http://www.joe.org/joe/1992spring/iw4.html

Norusis, M. J. (2001). Statistical package for the social sciences: version 11.0. Upper Saddle River, NJ: Prentice Hall.

Starr, A., Card, A., Benepe, C., Auld, G., Lamm, D., Smith, K., & Wilken, K. (2002). Barriers and opportunities to local agricultural purchasing by restaurants and institutional food buyers. Colorado State University.

Strohbehn, C. H., & Gregoire, M. (2003). Case studies of local food purchasing by central Iowa restaurants and institutions. Foodservice Research International, 14, 53-64.

Strohbehn, C. H., & Gregoire, M. (2002). Institutional and commercial food service buyer's perceptions of benefits and obstacles to purchase of locally grown and processed foods, Final Report. Ames, Iowa: Iowa State University, Leopold Center for Sustainable Agriculture. Available at: http://www.extension.iastate.edu/hrim/localfoods/

Strohbehn, C. H., & Gregoire, M. (2001). Innovations in school food purchasing: Connecting to local food. Journal of Child Nutrition. and Management, 25, 62-65.

Tubene, S., & Hanson, J. (2002). The wholesale produce auction: An

alternative marketing strategy for small farms. American Journal of Alternative Agriculture, 17(1), 18-23.

United States Department of Agriculture. (2001). Alternative enterprises-for higher profits, healthier land. Food Processing Center, University of Nebraska, Lincoln. Available at: http://www.nrcs.usda.gov/technical/RESS/altenterprise/

Will Tennessee Soybean Producers Support a Biodiesel Cooperative?

Burton C. English
Professor
benglish@utk.edu

Kim Jensen
Professor
kjensen@utk.edu

Jamey Menard
Research Associate
rmenard@utk.edu

The University of Tennessee Agricultural Economics Department
Knoxville, Tennessee

Introduction

Tennessee produces about 35.7 million bushels of soybeans each year. A growing market for soybeans is as a feedstock for biodiesel. Biodiesel can be made from soybeans, as well as other feedstocks, and can be blended with conventional diesel (B20 is 20% biodiesel) and used in engines with no modifications. Substituting petroleum diesel with biodiesel could decrease air emissions, reduce reliance on foreign oil, and help expand markets for U.S. farmers.

A recent study, funded in part by the Tennessee Soybean Promotion Board, Tennessee Department of Agriculture, USDA ë Rural Development, Tennessee Farm Bureau, and Tennessee Valley Authority, evaluated the economic feasibility of biodiesel production in Tennessee (English, Jensen, & Menard, 2002). As part of this study, it was determined that at the current time the most economically efficient sized plant is a 13-million-gallon biodiesel plant that would use 9 million bushels of soybeans.

While the results from this study were suggestive that a biodiesel facility would be economically feasible in Tennessee given sufficient soybean production, the question of producer interest in selling soybeans to a biodiesel facility was not addressed. The study reported here examines Tennessee soybean growers' views on biodiesel, their interest and capability to supply sufficient production to a biodiesel plant, and their interest in formation of a cooperative to produce biodiesel.

Survey and Analysis Methods

In February of 2003, a mail survey was sent to 2,452 producers in Tennessee. A listing of soybean producers was provided by the Tennessee Agricultural Statistics Service (TASS). All soybean producers farming soybeans on at least 100 acres were surveyed. Among those producing on less than 100 acres, 20% were randomly selected and surveyed. About 2 weeks after the initial mailing, a follow-up mailing was conducted. In this mailing, a second copy of the survey was sent to all producers who did not respond to the first mailing. Of the 2,452 producer addresses, 40 were undeliverable. A total of 561 usable responses were provided, giving a response rate of 23.3%. The results are summarized with means (for continuous responses, such as age) and with frequency counts (for categorical responses, such as "yes" or "no").

The survey was comprised of three sections. The first section contained questions regarding soybean producers' views on biodiesel markets, including their views on growth potential for biodiesel markets and whether they would be willing to sell soybeans to a biodiesel processing facility. The second section focused on cooperative processing of soybeans into biodiesel. This section included questions about purchasing delivery shares in a cooperative and desired rates of return on investment in a cooperative to produce biodiesel. The third section of the survey included questions regarding characteristics of the soybean farm and the soybean producers' characteristics, including size of farm and experience of the farm operator.

Summary measures include means for continuous variables (for example, age in years) and frequency tables for discrete variables (such as "Yes/No"). Throughout this document "N" represents the number of responses to the question. The frequency of responses versus non-responses was compared by county. No significant association between county and response was found. Age and farm size were also examined to determine if non-response bias existed. The statewide average age of the operator was 55.4, while the survey respondents averaged 52.4. When small (<100 acres) versus larger farms (100+ acres) were compared, the larger farms had a response rate of 23.8%, while the smaller farms had a response rate of 11.2%.

A breakdown of the responses, sample, and population is shown in Table 1. Due to the lower response rate on the part of smaller firms, care should be taken in extending the results to the full sample or the population.

Survey Results

Section I. Biodiesel Markets

On average, producers felt optimistic about the growth prospects for biodiesel markets in the next decade (Table 2), strongly agreed or agreed that biodiesel production will provide an important national market for soybeans in the next 10 years, and were interested in using biodiesel from soybeans in a 20% blend on their farming operation if it were competitively priced with conventional diesel.

As shown in Table 3, nearly 96% of producers believed that biodiesel could be profitability produced in West Tennessee. About 97% indicated they would be willing to sell some or their entire crop to a biodiesel processing plant.

When asked about the type of buyer producers would like to sell to, 6.21% indicated they would prefer to sell to a privately owned buyer, 35.73% to a cooperatively owned buyer, and 58.06% had no preference for type of buyer (Table 4).

The respondents were also asked about whether they would rather sell on a contract or spot basis. As shown in Table 5, of those wishing to sell to a privately owned buyer, the respondents would sell 278,000 bushels through marketing contracts and 90,500 bushels on a spot basis. Among those wishing to sell to a cooperative or with no preference, 4,05,0349 bushels would be sold through contracts and 2,256,889 bushels on a spot basis.

From the respondents, a total of 6,675,738 bushels would be available for use in some type of plant. Accounting for farm size differences, a projection of the bushels available across the sample is 28,087,804 and across the population is 30,031,547 bushels. The adjustment was made by multiplying the average bushels for sale by small farmers (<100 acres) and the average bushels for sale by large farmers (100+acres) by the number of farms in the sample in the two categories. These two values were then summed to get a total across small and large farms. The adjustment for the population estimate was calculated in the same way using the number of farms in the population in each size category. Because the total number of bushels is 35.7 million, this represents about 84% of the state's production.

Section II. Cooperative Production of Biodiesel

The percent indicating they would be interested in participating in a new generation cooperative to produce biodiesel was 75.66%, or 314 producers (N=415). The desired average minimum percent per year on any investment made in a biodiesel facility was 9.58% (N=269). Among those interested in investing in a new generation cooperative, at this rate of return, 88.51% indicated they would be willing to make a minimum purchase of 2,500 shares ($5,625 at $2.25 per bushel) (N=261). This represents about 577,500 bushels or $1,299,375 total investment. In addition, another 13 producers indicated they would buy the minimum amount for a total of 32,500 bushels or $73,125 investment, but did not indicate a desired rate of return. This gives a total of 610,000 bushels or 1,372,500 in investment.

If adjustments are made for the farm size differences, then the projections for the sample are 2,622,674 bushels and for the population are 4,688,627. This is an investment of $5,901,016 for the sample and $10,549,412 for the population. Recalling that the shares and investment needed are 9 million bushels and $18.5 million in producer investment, the population estimates represent about 52.1% of the bushels needed and 58.6% of the producer investment required would be available for operating the cooperative. However, these are state estimates, and members of a cooperative will likely be more regionally oriented.

Section III. Farming Operation and Producer Characteristics

Of the respondents, 70.52% indicated they were members of agricultural cooperatives (N=536). The respondents who produced soybeans in 2001 harvested an average of about 665.14 (N=524), or 348,533.4 acres in total. Distributed across the state, a total of 33% or more of the acres planted as reported by the National Agricultural Statistics Service (NASS) are represented by the survey (Figure 1).

Figure 1.
Proportion of Acres Represented by Survey Responders

Using an average of 30 bushels per acre, this would represent about 10,456,002 bushels of soybeans. About 31.54% (N=539) had no on-farm storage. Among those with on-farm storage, average storage capacity was about 23,819 bushels of soybeans on-farm (N=369). The total amount of storage indicated was 8,789,211 bushels. On average, the respondents stated they typically sold about 33.65% through contracts (N=525).

On average the respondents were 52.39 years old and had been farming for 33.99 years (Table 6).

Shown in Figure 2, about 44.71% of the farmers were full owners of their farms, while 25.73% were partners in the farm. About 9.67% were renters. The majority of the rest, 19.89%, were owner/renters.

Figure 2.
Farm Ownership

The net farm income from farming most commonly cited was $35,000-$49,999, at 15.45% (Table 7). The majority (54.27%) of producers had net incomes from farming between $15,000 and $75,000 per year.

As displayed in Table 8, nearly 35% had no farm debt. The majority, 53.71%, had less than $5 financed with debt per $100 of assets.

On average, about 35.95% of the respondents' household income came from off farm sources in 2001 (N=507). Shown in Table 9, most of the producers were either high school graduates, had attended some college, or held a college degree.

Soybean Draw Area

A biodiesel facility located in Northwest Tennessee could be served by local soybeans trucked from the surrounding area or by soybeans delivered by barge from upriver. Counties in Tennessee lying within a 50-mile radius of Cates Landing, Tennessee include Dyer, Obion, Gibson, Weakley, and Lake. Responses from these counties indicate that a total of 2,634,155 bushels would be available for sale from the responding farmers. Projecting this amount to the five-county area, the total bushels available would be about 10,631,831 bushels. This suggests that area farmers could adequately supply a facility in Northwest Tennessee.

Implications for Extension

Rural development is critical for agriculture to survive. Striving for ways to not only create jobs but also add value to what is produced in agriculture is one means to achieve development. The biodiesel enterprise featured in this article has the potential of increasing the number of local jobs, increasing the value of commodity soybeans, and increasing income in rural areas through vertical integration--the producer owning processing facilities and thus capturing more of the profits available from selling the biodiesel. Extension needs to be in a position to provide advice on the formation of cooperatives and how this might affect the farmer's bottom line. Extension agents will need to work with producers as they struggle in analyzing the financial impacts to their respective operation.

This study provides Tennessee Extension agents a means to evaluate farmers' perceptions of the development of a "new generation" cooperative. In Tennessee, there have been few success stories involving value-added cooperatives, especially those requiring large capital investment. However, the analysis indicates that while some producers are willing to provide some funding and are willing to purchase shares in a cooperative, many more are looking for new innovative ways to market their product.

Summary and Conclusions

The results from the survey reported here suggest considerable interest on the part of soybean farmers in selling their soybeans to a biodiesel production facility. Producers were less certain about formation of a new generation cooperative to produce biodiesel. If 9 million bushels are required to provide sufficient feedstock for a biodiesel production plant, there does appear to be sufficient interest and ability to supply soybeans on the part of producers.

As part of the economic feasibility study conducted during 2002, financial viability of a 13 million gallon (9 million bushel) facility at an investment of $18.5 million from producers and $18.5 million from outside investors was examined. From the survey responses, it appears that producers would be willing to purchase shares in a new generation cooperative in the amount to supply and finance about half the needs of a biodiesel plant. For the other half, additional sources of funding would be required.

References

English, B., K. Jensen, and J. Menard. (2002). Economic feasibility of producing biodiesel in Tennessee. Department of Agricultural Economics at the University of Tennessee. Available at: http://web.utk.edu/~aimag/pubmkt.html

Tennessee Agricultural Statistics Service. (2002). Tennessee Agriculture, 2002. Bulletin No. 37. Available at: http://www.nass.usda.gov/tn/tnbull00.htm

United States Department of Agriculture. (1997). National Agricultural Statistics Service. Census of Agriculture. Tennessee State and County Data. Vol. 1, Geographic Area Series, Part 42. Available at: http://www.nass.usda.gov/census/census97/volume1/vol1pubs.htm

County-Level Extension Programming: Continuity and Change in the Alabama Cooperative Extension System

Laura Robinson
Research Associate
School of Forestry and Wildlife Sciences
robinl2@auburn.edu

Mark Dubois
Extension Specialist/Associate Professor
School of Forestry and Wildlife Sciences
duboimr@auburn.edu

Conner Bailey
Professor
Department of Agricultural Economics and Rural Sociology
bailelc@auburn.edu

Auburn University
Auburn, Alabama

Introduction

The United States Cooperative Extension Service (Extension) was created in 1914 to "aid in diffusing . . . useful and practical information on subjects relating to agriculture and home economics" (Rasmussen, 1989:153). The declining farm and rural population has created a dilemma for Extension. Some clients, agents, and stakeholders argue Extension should maintain its focus on farms and rural America. Most clients, agents, and stakeholders agree that for Extension to survive it must change with the times and broaden its mission (Black, Howe, Howell, & Bedker, 1992; Conone, 1991; Adelaine & Foster, 1990; Johnsrud & Rauschkolb, 1989; Meier, 1989; Hildreth & Armbruster, 1981; Boone & Kincaid, 1966).

Extension programs are deeply rooted in agriculture and are, therefore, difficult to change. Extension programs, staff, and volunteers have strong ties to production agriculture, contributing to a slow rate of change.

Alabama has a long agrarian history marked by a steady decline since 1950 in number of farms and farmed acres. Much of the farmland has reverted to natural forest or has been planted in pines. Alabama forest acres grew by 1 million acres to 22.9 million acres between 1990 and 2000 (Hartsell & Brown, 2002). This compares with 9 million acres of farmland in 2000 (Alabama Agricultural Statistics Service, 2002). Over 80% of all commercial timber land in Alabama is controlled by 445,500 non-industrial private forest owners (NIPF) (USDA Forest Service 2001). The vast majority of these are individuals who own small parcels and may have needs for the type of expertise that the Alabama Cooperative Extension System (ACES) could provide (Bliss, Sisock & Birch, 1998; Zhang, Warren & Bailey, 1998).

Given the growing importance of forestry as an industry and some evidence that residents-clients were concerned about natural resource and environmental quality (Bliss, Nepal, Brooks, & Larson, 1994), we wanted to see if these concerns were being transmitted to county Extension offices and, if so, how this affected local Extension programming. Our research was motivated by recognition that staffing within ACES did not reflect the declining importance of agriculture or the increasing importance of forestry and natural resources, including the needs of NIPF owners.

Methods

Both primary and secondary data were used in our study. Secondary data included reports of County Advisory Boards and Program Advisory Committees and the allocation of time by county agents. Annually, each of Alabama's 67 counties is to have a County Advisory Board that is asked to identify issues of widespread concern for Extension to address. In contrast, Program Advisory Committees are focused on particular "base" program areas. We requested data on County Advisory Boards and Program Advisory Committees from all county Extension offices. We received usable data from 42 counties (63%) on County Advisory Boards and from 39 counties (58%) on Program Advisory Committees. Both County Advisory Boards and Program Advisory Committees represent citizen input, but their make-up and focus differ.

The allocation of effort by county agents is documented through self-reporting at the beginning of each year. Data for this study are from 2000 and were obtained from ACES. ACES personnel estimate, with approval of County Coordinator and District Supervisor, what portion of time in the coming year they expect to devote to various activities listed under Extension Team Projects. Data reflect both intended and approved allocation of time on the part of county agents and therefore the relative priority of program areas.

These secondary data were used to select four representative counties for more detailed investigations. Two of the four counties selected appeared to have a disconnect between what was identified by the County Advisory Board as a major issue of concern and the programs that were being implemented based on Extension Team Project data. In the two remaining counties, County Advisory Board priorities and county Extension programs had substantial overlap.

Primary data were collected using semi-structured interviews with members of County Advisory Boards, Program Advisory Committees, and Extension personnel. Interviews were conducted with 13 ACES staff, 10 county level and 3 state level. County Extension Coordinators in each county provided names and phone numbers for members of the County Advisory Boards. A total of 33 interviews were conducted (64% of all County Advisory Board members in these four counties). Face-to-face interviews ranged from 20 to 120 minutes. A set of common open-ended questions was used for these interviews, allowing for respondents to expand on their answers, an approach that often yielded valuable information. These primary data were useful in understanding local dynamics of Extension programming, but also helped us understand the limits of available secondary data.

Secondary Data

Figure 1 presents a normative (expected) model of how Extension programming at the county level should take place (Robinson, 2001). Figure 2 presents a summary of the purpose, members, and meetings of the County Advisory Board, Program Advisory Committee, and Extension Team Projects.

Figure 1.
Expected Relationship Between County Advisory Boards, Program Advisory Committees, Extension Team Projects, and Extension Agents in County-level Programming

According to the County Advisory Board Handbook (ACES, 1999a, p. 2), the mission of the County Advisory Boards is to aid local Extension staff by identifying issues of widespread public concern within the county and helping local staff decide which of these issues should be addressed through Extension programs.

Members of the County Advisory Board should include both formal and informal leaders of the community and represent a cross-section of race, ethnic, gender, economic strata, and occupations. In general, the County Advisory Board is to meet three to six times a year (ACES, 1999a). Their primary responsibility is to identify "critical issues and problems that affect the economic, physical, and social well-being of the county residents" (ACES, 1999a, p. 2). A review of available County Advisory Board reports (42 of 67 Alabama counties) indicates that family issues (83%), natural resources (71%), and agriculture (50%) were the concerns most often expressed (Robinson, 2001).

Program Advisory Committees are "organized groups of individuals with a common interest in a specific issue of widespread, local concern that Extension has committed to address" (ACES, 1999b, p. 2). County-level Extension staff determine how many Program Advisory Committees are needed, the number of people to serve on specific Program Advisory Committees, how often they meet, and their structure. County agents rely on Program Advisory Committees to ensure that "base" programs stay relevant and meet needs of their clientele. Program Advisory Committee members help county agents obtain resources--facilities, equipment, program-specific donations--needed to carry out programs. Also, Program Advisory Committee members assist agents in implementing and evaluating certain educational programs (ACES, 1999b).

Members should be community leaders who have a general knowledge of the program area within which they have volunteered. Like County Advisory Boards, Program Advisory Committee members must represent a cross-section of race, age, sex, economic strata, skills, and knowledge levels. Secondary data were available on Program Advisory Committees for 39 counties. All but two counties (95%) had Program Advisory Committees related to agriculture, compared to 69% for family issues and 38% for natural resource issues (Robinson, 2001).

Extension Team Projects were created in 1997 to replace individual plans of work and to better facilitate organized teamwork within ACES. An Extension Team Project is defined as "a series of related activities which take place over a specified period of time (usually several years), and which involve several Extension-funded employees working together to accomplish specific objectives" (ACES, 1997, p. 2). Extension Team Projects are not committees or groups that meet, but rather are program areas that individual county agents and specialists identify as important to their assignments.

County agents are required to allocate a minimum of 50% (116 days) of their time to one or more Extension Team Projects. The remaining days should be allocated to "non-project work." For this project, the amount of time dedicated to specific Extension Team Projects was defined as the amount of time spent working in that program area and focus of county-level Extension programming. Family issues were the largest (45%) single program area as defined by Extension Team Projects, followed by agriculture and 4-H (38.5% combined), and natural resources (6.2%) (Robinson, 2001). The emphasis on family issues is explained by federal funding tied strictly to such programs as the Expanded Food and Nutrition Education Program.

Analysis of secondary data suggests that there is a disconnect between (1) the major issues of concern identified by County Advisory Boards and (2) where county-level Extension personnel devote their time and energy (as measured by involvement in various Extension Team Projects). In particular, these data indicate that the continuing emphasis on traditional agriculture and 4-H programs and the far more limited attention devoted to natural resource issues is at some variance to recommendations by County Advisory Boards across the state.

Primary Data

Primary data from interviews with County Advisory Board members and Extension personnel from the four study counties suggest that the disconnect may not be as sharply defined as the secondary data indicate. County Advisory Board members interviewed expressed no dissatisfaction with Extension programming. To the contrary, they expressed the view that certain major issues of concern are "timeless" in nature and not easily resolved (e.g., unemployment, poor parenting skills, and such youth issues as drugs, alcohol, and teen pregnancy). They indicated that their role was not to be directly involved in program definition and development but rather with broad-brush scoping of challenges facing their particular county.

This is at some variance to the official position on this matter (ACES, 1999a). The County Advisory Board handbook states that the County Advisory Board's primary mission is to identify issues of widespread public concern in the county and help the local staff determine which issues should be addressed through Extension programs (ACES, 1999a). Both primary and secondary data indicate that County Advisory Boards are not instrumental in shaping county-level Extension programming.

Interview data indicated that county Extension staff rely primarily on Program Advisory Committees to identify program needs. By definition, Program Advisory Committees are linked to certain "base" program areas, historically defined as 4-H and production agriculture. Local members of Program Advisory Committees are likely to be associated with various agricultural commodity groups or other influential organizations with a clear interest in ACES continuing to serve the needs of agricultural interests. Nine county-level Extension staff interviewed had degrees either from Auburn University or Alabama A&M University, both land-grant universities. Eight had degrees in traditional Extension areas of agriculture or home economics. This pattern of staffing is consistent nationally (Terry, 1995).

Interviews with Extension personnel at the county level indicated that Extension Team Projects may not represent an accurate reflection of the work they do. County agents respond to needs of residents, and predicting what those needs will be involves more art than science. Extension Team Projects were designed to encourage interaction among Extension personnel (e.g., between university-based specialists and county agents) to address common problems.

From the perspective of ACES headquarters, a common planning framework for all employees makes sense in defining interests and coordinating activities. From the perspective of the county agent, however, Extension Team Projects may be seen simply as another form of reporting not unlike the annual work plans that the Extension Team Projects were designed to replace. In short, conclusions based on a strict interpretation of Extension Team Projects as reflective of county agent program activities need to be approached with caution.

These caveats aside, our research suggests that Extension programming at the county level emphasizes traditional programs in agriculture and 4-H. The question is why this emphasis instead of forestry, natural resources, and community development.

Discussion

There is a substantial literature on Extension's continued linkage to agriculture. To this literature we offer a modest contribution by focusing specifically at county-level Extension programming. Terry (1995) noted that most county agents in the U.S. studied agricultural disciplines at land-grant universities, a pattern reflected in the staffing of ACES as well.

As they began their careers, county agents found a ready clientele and well-organized support groups. In Alabama this support is institutionalized in the form of the Program Advisory Committees. County-level Extension personnel look to Program Advisory Committees for primary guidance in program development. Compared to the County Advisory Boards, whose guidance tends to be broad in scope, Program Advisory Committees have well defined goals and are focused on deliverable outcomes. The combination of organized support and program clarity is understandably attractive to county agents who depend on local funding for a portion of their operational budget.

Both primary and secondary data collected in this study reflect the continued dominance of agriculture in ACES programming at the county level. Normative description of County Advisory Boards and Extension Team Projects do not match how they are operationalized in practice. Interpretation of secondary data based on normative definitions is misleading. County Advisory Boards do not appear to play an effective role in Extension program development at the county level. As a result, ACES resources have the potential to be disproportionately devoted to traditional programs in agriculture and 4-H. The comparative strength of ACES programs related to family issues such as nutrition is directly related to federal funds earmarked for those purposes.

While these needs are being met, needs of citizens whose concerns involve natural resource and environmental protection or community development remain unmet. Well over 100 citizen groups in Alabama have been formed out of concern for natural resource and environmental issues <www.ag.auburn.edu/grassroots>, but few have any connection to ACES (Bailey, Walton, Merritt, & Dubois, 2000). Of the 445,500 non-industrial private forest landowners, many own small tracts of forestland and would benefit from ACES programming in the areas of timber management and marketing (USDA Forest Service, 2001).

Conclusion

Changing institutional direction is a slow process. Vested interests and institutional cultures represent conservative forces in the gradual transformation of Extension in the United States. In this article we have examined the dynamics of such change at the county level in Alabama. Federal funding to support programming in family well-being has led to substantial investment of effort into this new program area. In an era of budgetary constraints, expanding program efforts in new directions will have an immediate and negative impact on established programs. Resistance is to be expected. Yet if Extension is going to continue to meet the needs of citizens in the United States, some redirection of effort will be necessary. Our research suggests that such initiatives are unlikely to begin at the county level.

Acknowledgement

The research reported upon here was supported by the USDA's National Research Initiative Competitive Grants Program (Rural Development).

References

Adelaine, M. & Foster, R. (1990). Who really influences Extension direction? Journal of Extension [On-line], 28(4). Available at: http://www.joe.org/joe/1990winter/a1.html

Alabama Agricultural Statistics Service. (2002). Alabama agricultural statistics. Bulletin 44. Montgomery: Alabama Agricultural Statistics Service.

ACES (Alabama Cooperative Extension System). (1999a). Alabama Cooperative Extension System county advisory board handbook.

ACES. (1999b). Alabama Cooperative Extension System program advisory committee handbook.

ACES. (1997). Extension team projects. Retrieved October 11, 2000, from http://www.aces.edu/department/acesadm/plan/explan.htm

Bailey, C., Walton, B., Merritt, L., & Dubois, M. (2000). Green groups as clients; Opportunities for ACES. Action; Public Issue Information for Alabama Citizens. Spring 2000. Auburn: Alabama Cooperative Extension System.

Black, D. C., Howe, G. W., Howell, D. L., & Bedker, P. (1992). Selecting advisory council members. Journal of Extension [On-line], 30(1). Available at: http://www.joe.org/joe/1992spring/a4.html

Bliss, J. C., Sisock, M. L., & Birch, T. W. (1998). Ownership matters: Forestland concentration in rural Alabama. Society and Natural Resources, 11, 401-410.

Bliss, J. C., Nepal, S. K., Brooks, R. T., Jr. & Larson, M. D. (1994). Forestry community or grandfalloon?: Do forest owners share the public's views? Journal of Forestry, 92(9), 6-10.

Boone, E. J., & Kincaid, J., Jr. (1966). Historical perspective of the programming function. In H. C. Sanders (Ed.) The Cooperative Extension Service. (pp. 89-93) Englewood Cliffs, NJ: Prentice-Hall, Inc.

Conone, R. M. (1991). People listening to people. . .or are we really? Journal of Extension [On-line], 29(3). Available at: http://www.joe.org/joe/1991fall/f1.html

Hartsell, A. J., &. Brown, M. J. (2002). Forest statistics for Alabama, 2000. Resource Bulletin SRS-67. Ashville, N.C.: Southern Research Station, USDA Forest Service.

Hildreth, R. J. & Armbruster, W. J. (1981). Extension program delivery--Past, present, and future: An overview. American Journal of Agricultural Economics, 63, 853-858.

Johnsrud, M. D., & Rauschkolb, R. S. (1989). Extension in transition: Review and renewal. Journal of Extension [On-line], 27(1). Available at: http://www.joe.org/joe/1989spring/tp1.html

Meier, H. A. (1989). Extension trends and directions. Journal of Extension [On-line], 27(3). Available at: http://www.joe.org/joe/1989fall/a3.html

Rasmussen, W. D. (1989). Taking the University to the people--Seventy-five years of Cooperative Extension. Ames, Iowa: Iowa State University Press.

Robinson, L. (2001). Examination of the Alabama Cooperative Extension System's county level programming. M.S. Thesis in Rural Sociology, Auburn University. December 2001.

Terry, L. D. (1995). Cooperative Extension's urban expansion: The default of leadership or responsiveness to changing times? Administration & Society, 27, 54-81.

United States Department of Agriculture Forest Service (2001). Alabama State and Private Forestry Fact Sheet. Site Accessed May, 24, 2004. http://www.fs.fed.us/spf/coop/states/al.pdf

Zhang, D., Warren S., & Bailey, C. (1998). The role of assistance foresters in nonindustrial private forest management: Alabama landowners' perspectives. Southern Journal of Applied Forestry, 22(2), 101-105.

Private Forest Landowners: What They Want in an Educational Program

Adam K. Downing
Extension Agent, Forestry and Natural Resources
Virginia Cooperative Extension
Madison, Virginia
Adowning@vt.edu

James C. Finley
Associate Professor of Forest Resources and Extension Forestry Specialist
Penn State School of Forest Resources
State College, Pennsylvania
JFinley@psu.edu

Introduction

As educators, we accept certain challenges that inherently come with a clientele with varying values, beliefs, attitudes, experiences, and knowledge levels. Nonetheless, we remain committed to the challenge of facilitating change--our basic yet most lofty goal. For most private forest landowners (PFLs), ideas of stewardship and management are only "occasionally relevant" (Sampson & DeCoster, 1997). Forested systems are ever changing, but change is often slower and more gradual than, for example, with agricultural crops. This, perhaps, frustrates the engagement of PFLs in using appropriate management practices.

One of the greatest challenges for the Extension educator is identifying programs relevant to the clientele's concerns (Seevers, Graham, Gamon & Conklin, 1997). The survey implemented in the study reported here assessed PFL educational needs and desires. If educators can provide private forest landowners with well-designed tailored programs, they may foster forest resources stewardship. "Programs" include educational events such as workshops, seminars, and demonstrations.

Background

Most (58%) of the forestland in the United States is privately owned. This fact alone lends credence to the importance of private forestland stewardship. Additionally, the bulk of the nation's wood (60% in 1997) comes increasingly from non-industrial private forestland (Haynes, 2001). What's more, PFLs value aesthetics and recreation most highly, and ownership reasons like timber production or land investment are seldom primary (Birch, 1996).

Private forestland ownership is changing. For example, Pennsylvania annually has about 40,000 new PFLs owning an increasingly smaller portion of the finite land-base. The new owners include more retirees, professionals, and white-collar workers (Birch, 1996). Pennsylvania is not unique in these challenges. PFL ownership nationwide is increasingly diverse and fluid (Sampson & DeCoster, 1997).

Shifting ownership patterns coupled with increased societal demands for forest products and amenity values have implications. It emphasizes the need to deliver relevant information and service to an ever increasing and changing forest owner population. As audience profiles' change, educational methods may likewise need to change to achieve increased clientele acceptance of forest stewardship activities (Seevers, Graham, Gamon & Conklin, 1997).

The logical implication is to design programs targeted to different audience segments. One-on-one assistance easily accommodates this need; but efficiency is low. Additionally, as ownership numbers increase, the prospect of reaching landowners with individual assistance is daunting. The viable alternative is to design educational programs targeted to specific audience groups.

Retail marketing provides a precedent for this approach. Customer surveys are used to more effectively market to diverse populations of consumers. Several studies have suggested landowner grouping or classification schemes (Mills, Hoover, Vasan, McNamara & Nagubadi, 1996; Sampson & DeCoster, 1997; Trokey & Kurtz, 1982; Webster & Stoltenberg, 1959). However, no recent examples specifically linking programs to PFL groups by using their shared needs and preferences were found.

Purpose and Objectives

The study reported here was designed to broadly address a set of questions:

• What do forest landowners want?

• Do they have preferences for meeting length, time of day, and subject matter, for example?

• Which preferences are most important when designing a program?

• Which preferences are important to various audience segments?

• Can we group people in a meaningful way, for example, that would enable educators to design programs to reach young professionals who own less than 100 forested acres?

The specific primary objectives were:

1. To identify educational approaches preferred by private forest landowners inclined to attend education programs about the care and management (i.e., forest stewardship) of their land(s).

2. To identify socio-demographic characteristics that relate to PFL preferences for receiving information about forest stewardship.

Methods

A mail survey was initially developed and reviewed for content and readability then pre-tested and modified before being mailed to 500 private forest landowners. These landowners were randomly selected from a list of 3,435 individuals who were initially contacted with an educational offering but who chose not to participate. The initial program was offered to individuals on "natural resources" related mailing lists in an eleven-county area in Northeast and Central Pennsylvania.

This sample represented those likely having an interest to learn about natural resources. Rogers' Adoption Diffusion model (1983) provides the logic for this sampling method. The study sample, because of prior self-selection, at least excludes laggards and probably emphasizes early adopters. By targeting innovators and the early adopters, educators can more efficiently affect learning. The response rate was 43% (n=212), but only 180 surveys were useable for statistical analysis. Thirty-two responses were not used for several reasons (i.e., the respondent did not own forest land, the respondent worked in a forestry related field [we were only interested in landowners], or returned unusable incomplete instruments). Non-response bias is considered negligible, again, because of the desired early adopter audience.

Results/Findings

PFLs: A Demographic Snapshot

The respondents more of less paralleled the "typical" private forest landowner in Pennsylvania (Birch and Dennis, 1980) and across the nation (Birch, 1996).

• Acreage owned:
  • 43 % owned < 50 acres
  • 84 % owned < 200 acres
    
    
• 87 % male
  
  
• Average age = 57 years
  
  
• Occupation:
  • Retirees = 33 %
  • Professional workers = 18 %
  • Farmers = 11 %
  • Laborers = 6 %

PFLs reported fairly high levels of education and moderate incomes. Over 50% had completed a two-year degree or more with nearly 20% completing a graduate degree. Over 40% had annual household incomes of $50,000 or greater.

Programming for PFLs

Developing and offering successful educational program often depends on:

• When is the target audience available?

• What are appropriate program subjects?

• How would participants most prefer to receive information?

When

More than half (52%) of the respondents believed that time of year was "somewhat" or "very important." Overall, winter is the favored season, followed by spring, for attending educational programs (Figure 1). An analysis of variance revealed a difference among occupational groups in terms of how strongly they preferred certain seasons (F = 3.53, p<0.05). Laborers and technicians were more concerned about the time of year than professional and retired PFLs.

Asked to rank their preference for day of the week, Saturday was the most favored day to have a meeting, with Monday ranked second, while the least favored was Friday (Figure 1). Nearly a third (31% of the respondents) had no time of day preference. Those who did have a preference preferred evening gatherings (34%) (Figure 1). An analysis of variance suggests another difference by occupation groups and preferred meeting times (F = 3.54, p <0.01). The greatest difference occurred between technicians, who prefer evenings, and retirees, who least prefer evenings.

Figure 1.
PFL Preferences for When* They Want to Attend an Educational Offering

What

PFLs placing high importance on learning specific natural resources information had achieved a higher level of formal education and were younger. More than 87% of the respondents believed that learning specific information was important. Knowles (1984), writing on andragogy, recognized the importance of learning specific information to adult learners. When asked to identify specific information they wanted, top subjects were forest and wildlife management (Figure 2).

Figure 2.
Information Most Desired by Forest Landowners

Over 50% of the respondents indicated that it is important to discuss environmental issues. Forest landowners with higher formal education and preferring more active learning methods viewed the discussion of environmental issues as more important (p <.01). Interestingly, gender is a significant consideration (p<.01). Although less than 10% of the respondents were female, they were more likely to desire discussion of environmental issues as a program component.

Forest landowners want to learn information they can apply to their personal situation, again mirroring Knowles' (1984) findings. On a Likert scale of one to four, the mean score for this question was 3.44, (Table 1) between "somewhat" and "very" important. Networking with resource professionals was also important, more important than networking with other forest landowners (Table 1).

How

Asked if it mattered who sponsored a program, nearly half indicated that it was not important. Similarly, 45% were not concerned with recognizing the speaker's name. PFLs for whom this was a concern tended to own more forested acreage and belong to a conservation- or a natural resources-oriented organization (p <.01).

Respondents reported a willingness to travel. Fifty-five percent indicated they would willingly travel 45 minutes or more to attend a program. The distance one was willing to travel related positively to formal level of education (p <.05).

Given that a program occurred during their favored time of year, respondents prefer a half-day program. An entire weekend was the least preferred (4%).

As expected, respondents varied in their preferred learning styles. Respondents were asked how well each of 12 different program methods "work for them" (Figure 3). Four of the top five most preferred methods were more active delivery styles. Workshops, demonstration areas, and skill demonstrations were considered "active" delivery. The remaining methods (slide, videos, newsletters, etc.) were considered "passive" delivery styles. A paired t-test showed that the means of these two groups were significantly different (p<.01).

Figure 3.
PFL Preference for Educational Delivery Methods (5-Point Likert Scale)

Discussion

Timing issues are important. Our findings suggest that PFLs differ, according to their occupation, in their preference for when programs are offered. Time commitment issues are also important to consider. PFLs are willing to drive considerable distances to attend a relevant program, and many are willing to commit half a day.

PFLs want to learn practical information about the management of their natural resources, and they prefer to learn these skills and information through active methods like workshops, demonstration areas, and field trips. PFLs also value the opportunity to network with others, especially natural resource professionals. When planning education events, educators should make a point of including program elements that encourage active involvement and allow for informal networking.

The landowners queried in this study (early adopters) do have preferred methods for receiving information about the care of their forest(s). Educational preferences often relate to easily measurable socio-demographic characteristics.

Conclusions

Seasoned Extension educators will find few, if any, surprises presented in the study reported here. Evening and weekend meetings are part of our normal workweek. We have long used hands-on teaching methods (such as workshops and demonstration areas) for teaching audiences typically comprised of "hands-on" people who work for a living.

Perhaps more interesting is the idea of looking more closely at our audience (consumer). Who are they, and what educational information (product) do they seek? Not only should we consider the content and preferred timing, but also delivery methods and various informal program components. The study revealed occupation as a key variable to consider when choosing a date and time for a program. Other variables such as education, gender, and age may warrant consideration for planning other components of an educational event.

Consideration of findings from this study will move Extension education beyond counting attendance. It will help Extension educators design and deliver meaningful programs to targeted clientele who have specific preferences in educational program design and delivery. Extension educators are more likely to achieve higher levels of impact if they plan for active involvement and have considered clientele preferences and needs.

Implications for Further Study

The study reported here provides a cursory investigation into levels of preferences. As PFL ownership patterns are changing, educators need to know how to adapt to and target audiences. A study that would group private forest landowners in "demographic clusters" and align them with specific program elements would be extremely valuable to Extension personnel as well as other natural resources educators. The study reported here purposively selected Rogers (1983) innovators and early adopters, but it would be useful to look across the entire adoption range.

References

Birch, T.W. (1996). Private forest-landowners of the United States, (1994.). USDA Forest Service, Northeastern Forest Experiment Station, Research Bulletin NE-134.

Birch, T. W., & Dennis, D. F. (1980). The forest-land owners of Pennsylvania. USDA Forest Service, Northeastern Forest Experiment Station, Research Bulletin NE-66.

Haynes, R. W. (2001). The 2000 RPA timber assessment: An analysis of the timber situation in the United States, 1996 to 2050. USDA Forest Service, Pacific Northwest Research Station General Technical Report PNW-GTR-560.

Knowles, M. (1984). Andragogy in action: Applying modern principles of adult learning. San Francisco, CA: Jossey-Bass Publishers.

Mills, W., Hoover, W., Vasan, S., McNamara, T., & Nagubadi, V. (1996). Factors Influencing Participation in Public Management Assistance Programs. Symposium on non industrial private forests. Learning from the past, prospects for the future. February 18-20, 1996. Washington, DC.

Rogers, E. M. (1983). Diffusion of innovations, (3rd ed). New York, NY: The Free Press.

Sampson, N., & DeCoster, L. (1997). Public programs for private forestry, a reader on programs and options. Washington, DC: American Forests.

Seevers, B., Graham, D., Gamon, J., & Conklin, N. (1997). Education through Cooperative Extension. Albany, NY: Delmar.

Trokey, C. B., & Kurtz, W. B. (1982). Increasing timber management through a better understanding of nonindustrial private forest owner's motivation and objectives. Journal of the Association of Consulting Foresters, 27, 57-59.

Webster, H., & Stoltenberg, C. (1959). What ownership characteristics are useful in predicting response to forestry programs? Land Economics, 35, 292-295.

Assessment of Negative Economic Impacts from Deer in the Northeastern United States

David Drake
Extension Wildlife Specialist
Rutgers University
New Brunswick, New Jersey
drake@aesop.rutgers.edu

Joseph B. Paulin
Extension Program Associate
Rutgers University
New Brunswick, New Jersey
paulin@aesop.rutgers.edu

Paul D. Curtis
Extension Wildlife Specialist
Cornell University
Ithaca, New York
pdc1@cornell.edu

Daniel J. Decker
Director, Cornell AES
Cornell University
Ithaca, New York
djd6@cornell.edu

Gary J. San Julian
Extension Wildlife Specialist
Penn State University
University Park, Pennsylvania
gsjulian@psu.edu

Introduction

White-tailed deer (Odocoileus virginianus) are perhaps the most recognizable wildlife species in the United States. The economic benefits of hunting, viewing, and photographing deer are in the hundreds of millions of dollars annually (United States Fish and Wildlife Service, 2002). Deer provide numerous ecological benefits as well (Putman, 1988).

Evidence suggests that deer are also causing negative impacts. For example, Conover, Pitt, Kessler, DuBow, and Sandborn (1995) estimated that more than one million deer-vehicle collisions occur annually in the United States, costing over $1.1 billion in repair costs and resulting in 29,000 human injuries and 211 human fatalities. Nationwide, deer have been recognized to cause more damage to agricultural crops than any other vertebrate wildlife species (Conover & Decker, 1991), costing farmers more than an estimated $100 million each year (Conover, 1997; Conover, 1998).

It is critical that stakeholders experiencing unwanted deer interactions be included and involved in management decisions if deer management is to be successful (Messmer, Cornicelli, Decker, & Hewitt, 1997). Arming decision makers with factual information is also vital because many deer management decisions are made in the policy arena or are politically influenced (Curtis & Hauber, 1997).

Therefore, the objective of our study was to identify affected stakeholders and the extent of negative impacts resulting from unwanted deer-human interactions in the northeastern United States. Understanding affected groups and impacts will enable Extension and wildlife professionals to tailor outreach, research, and management options to better manage overabundant deer populations. Increased understanding of the stakeholders and impacts will also aid policy makers who need to evaluate the magnitude of issues as they weigh one constituency group against another.

Methods

During the fall of 2001 we gathered secondary data for 13 northeastern states: Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, Virginia, and West Virginia. We surveyed, via e-mail and telephone, Extension specialists, wildlife biologists at state wildlife agencies, and personnel at state Departments of Transportation. Our survey asked recipients for economic data on deer-vehicle collisions, deer damage to high-value agriculture (i.e., fruits and vegetables), grain crops, nursery stock, and commercial and residential landscaping. We had a 100% response rate because we contacted survey recipients until they either responded with data or informed us that no data existed. We also performed a literature review and gathered data from each state's agricultural statistic service to supplement data on impacts from the e-mail and phone surveys.

We reported straight loss figures for deer-vehicle collisions and residential/commercial landscape depredation. For example, we gathered data on the number of deer-vehicle collisions from each state of interest and multiplied number of collisions by a nation-wide average repair cost to arrive at a total estimated cost per state from deer-vehicle collisions. To determine the cost of deer depredation to high-value agriculture, grain, and nursery crops, we gathered data from each state of interest and calculated an average total production value for specific crops. For states where we had no basis for a loss estimate, we subtracted 1% from the average total production value. We chose a 1% loss estimate because it was as conservative a loss estimate (whole number) as possible but still allowed for nominal levels of depredation. A higher loss estimate was used for states where we either had published research or personal knowledge from wildlife professionals to support higher loss estimates.

Results

Deer-Vehicle Collisions

The total estimated annual vehicle damage from deer-vehicle collisions for the 13 states surveyed was $390,594,000, ranging from a low of $592,000 for Delaware to a high of $150,000,000 for Pennsylvania. All states except Connecticut, Vermont, and West Virginia reflect collision data for 2000. Due to availability, 1986 data were used for Connecticut, and 1991 data were used for Vermont and West Virginia. An average repair bill of $2,000 per collision was used to estimate the economic impact from deer-vehicle collisions, according to the Insurance Information Institute <http://www.iii.org/individuals/auto/lifesaving/deercar/>. The data do not include costs of human fatalities associate