Publishing in refereed journals has long been a requirement for Extension specialists with university faculty status. Because several states also have granted Extension agents faculty status, the requirement for refereed publications as evidence of scholarly activity is now becoming more common for field agents as well. O'Neill (1990) described 10 tips for Extension agents on getting published in a refereed journal. The first tip was to write about what you know. Agriculture Extension agents know agriculture and frequently conduct field trials that, with the appropriate data collection techniques, experiment controls, and replication, can lead to a refereed journal publication.

Loveridge (1998) noted that Extension field personnel can be at a disadvantage when conducting research because of the distance from a university campus and lack of infrastructure (equipment) and monetary support. A major limitation for field personnel conducting agricultural research is obtaining adequate quantitative data for statistical analysis.

A recent literature search reveals an abundance of simple and relatively inexpensive methods for gathering quantitative data from agriculture experiments. This article briefly summarizes and cites various methods to make agents aware of these field data collection opportunities. This list is not meant to be exhaustive, but rather to provide field agents with ideas for data collection methods that may be used in field studies.

Validity of Data Collection Methods

Prior to adopting any new methodology, one has to ask whether the method will be valid in the context in which it will be used. We recommend that researchers return to the original references cited in this paper and critically evaluate whether a method is appropriate for their intended use. Some critical evaluation has already occurred if the method was published in a refereed journal. However, additional research may be necessary before determining whether the method is appropriate for the situation in which it will be used.

Data Collection Methods

On-Farm Trials

On-farm trials, whether with demonstration plots or replicated treatments, have long been the primary vehicle for applied research in Extension (Kittrell, 1974). The advantages of on-farm trials include:

• Equipment used for field work is frequently owned by the farmer, eliminating the need for the agent to purchase equipment or borrow from campus sources;
• On-farm trial plots sizes are commonly large because equipment is farm scale; and
• Research is done on a producer's farm, which can lend additional credibility to the data and facilitate the adoption of new technology by other producers (Rzewnicki, 1991).

In many situations, on-farm trials minimize the need for Extension agent equipment resources and are an established and efficient way to conduct publishable research.

Various guides have been produced to aid in designing valid on-farm field trials (Miller, Adams, Peterson, & Karow, 1992). Recent variations of on-farm trials include using demonstration plots and single farms as replications for, among other practices, evaluating hybrid performance and fertilizer responses across a county, state, or region (Posner & Crawford, 1992; Devlin, Christian, & Fjell, 1994). These variations provide an alternative to conducting a replicated trial at each location, and data may still be analyzed using traditional statistical procedures (Nafziger, 1984).

Yield Measurements

Yield is the most frequent parameter measured in agricultural field trials. Direct harvest is the most accurate method of measuring yield. However, unless plots are large enough to use farmer equipment, an agent must have the equipment for harvesting and weighing, or use indirect methods to estimate yield.

Yield from small plots or subsampled yield from larger plots can be determined by directly harvesting plant material from a known area. A known area can be harvested within an inexpensive frame made of PVC or wood, or along a measured linear distance for row crops. A sickle mower or rechargeable or manual clippers can be used to harvest plant material from small plots. The tissue can then be weighed and yield calculated from the weight and harvest area. Grain plots also can be harvested by hand and a representative sample of heads or ears shelled by hand. The total cost of equipment to measure yield from small plots can be under $1,000.

Various indirect methods for measuring forage yield have been developed and successfully tested against direct harvest measurements. Some success with simple visual techniques has been reported (Laca, Demment, Winckel, & Kie, 1989); however, visual estimates of yield have not gained widespread acceptance in published research.

The rising plate meter is a simple tool utilizing a graduated shaft with a sliding plate to measure forage production and utilization (Scrivner, Center, & Jones, 1986). One end of the shaft is placed on the ground, and the plate is allowed to fall from a fixed height. The height and density of the forage prevents the plate from falling to the ground, and a measurement of plate height taken from the graduated shaft is related to yield via a calibration curve. The rising plate meter can be calibrated for specific situations (Gourley & McGowan, 1991), or one may use pre-established calibration curves if appropriate (Earle & McGowan, 1979).

Canopy height and leaf area index measurements have also been correlated to direct harvest yield measurements for various forages (Harmoney, Moore, George, Brummer, & Russell, 1997). Whenever indirect measurements are used, the method and actual measurements collected should be reported, as well as the yield derived from the measurement.

One additional challenge in determining yield for direct harvested agricultural experiments is variations in tissue water content. For example, forages vary in water content among species and at different times of the season (Laca et al., 1989). Therefore, the assumption of average and constant moisture content may result in errors in dry matter yield estimates. Rapid (10 minute) sample drying using a microwave oven is comparable to drying in a forced air oven at 55 degrees C for 24 hours (Schuman & Rauzi, 1981). This method apparently does not affect the nitrogen and phosphorus content of forage samples; however, feed quality parameters may be affected by microwave drying (Carlier & van Hee, 1971).

Forage Quality Evaluation

Techniques for field evaluation of alfalfa quality parameters (primarily acid and neutral detergent fibers) based on the tallest stem and maturity of the most mature stem have been developed in several states (Owens, Albrecht, & Hintz, 1995; Sulc et al., 1997). These techniques have been used mainly for pre-harvest quality evaluations and in decisions regarding harvest timing. Widespread use of these techniques for alfalfa quality assessment in research settings has not been reported.

Weed Control Effectiveness

The effectiveness of various weed control methods has been evaluated by visual rating scales (e.g., percent control) and weed counts per unit area (Willard, 1958; Frans & Talbert, 1977; McDaniel, Hart, & Carrol, 1997). Both of these methods are routinely reported in weed control literature. In addition, both methods have been expanded to include ratings of crop herbicide injury (Steckel, Defelice, & Sims, 1990).

Plant Nutrient Status

Chlorophyll meters have been used to rapidly assess the green color of leaves of various plant species (Peryea & Kammereck, 1997; Varvel et al., 1997; Bullock & Anderson, 1998). Relationships between meter reading and nutritive status or yield have been developed for certain plants; however, universal calibration curves relating meter readings to tissue nutrient (e.g., nitrogen or iron) content have not been developed. Chlorophyll meter data may be useful for comparing treatments such as nitrogen or iron rates. Readings may also be related to yield to develop localized data for routine use of the meter during field monitoring.

A simple visual rating scale (1=yellow through 9=green) has been used extensively to monitor turfgrass color and response to nitrogen or iron treatments (Wehner & Haley, 1990). A similar four-point scale also has been adapted to evaluate tree leaf color in response to iron treatments (Messenger, 1984). Color index scales may be improved by using standardized colors from sources such as the Munsell color chart for plant tissues (Wilde & Voigt 1952; Harrell, Pierce, Mooter, & Webster, 1984).

Rapid analysis of plant sap using portable meters or test strips (Prasad & Spiers, 1984) has been related to traditional colorimetric methods with some success. Use of quick test methods should be preceded by further research into the method to determine whether it has been successfully used for the specific situation.

Other Measures of Plant Performance

Many other simple and inexpensive measures of plant performance are routinely used in agricultural field research. Measured plant height may be a useful tool to evaluate different varieties or treatment effects on plant growth. Stand counts can be used to evaluate effects of treatments or other variables on seed germination and plant population. Yield component analysis, including tillers/area, ear or head number/plant, and seed counts, has also been used to evaluate performance among varieties or treatments. In addition, seed samples brought to local elevators can be tested for moisture and test weight using available equipment, often at no charge. Finally, rating scales or estimates of percent lodging and disease occurrence also are simple methods for gaining quantitative data from field experiments.

References

Bullock, D.G. & Anderson, D.S. (1998). Evaluation of the Minolta SPAD-502 chlorophyll meter for nitrogen management in corn. J. Plant Nutrit., 21, 741-755.

Carlier, L.A. & van Hee, L.P. (1971). Microwave drying of lucerne and grass samples. J. Sci. Fd Agric., 22, 306-307.

Devlin, D.L., Christian, M.L., & Fjell, D.L. (1994). Developing an on-farm testing and demonstration program for grain sorghum hybrids. J. Nat. Resour. Life Sci. Educ., 23, 59-60.

Earle, D.F. & McGowan A.A. (1979). Evaluation and calibration of an automated rising plate meter for estimating dry matter yield of pasture. Aust. J. of Exp. Agr. and Anim. Husb., 19, 337-343.

Frans, R.E. & Talbert, R.E. (1977). Design of field experiments and the measurement and analysis of plant responses. In B. Truelove (Ed) research methods in weed science (2nd ed.). Southern Weed Science Society.

Gourley, C.J.P., & McGowan, A.A. (1991). Assessing differences in pasture mass with an automated rising plate meter and a direct harvesting technique. Aust. J. of Exp. Agric., 31, 337-339.

Harmoney, K.R., Moore, K.J., George, J.R., Brummer, E.C. & Russell, J.R. (1997). Determination of pasture biomass using four indirect methods. Agron. J., 89, 665-672.

Harrell, M.O., Pierce, P.A., Mooter, D.P., & B.L. Webster. (1984). A comparison of treatments for chlorosis of pin oak and silver maple. J. Arboric., 10, 246-249.

Kittrell, B.U. (1974). Result demonstration technique--history, philosophy, and contemporary nature. J. Agron. Educ., 3, 90-94.

Laca, E.A., Demment, M.W., Winckel, J., & Kie, J.G. (1989). Comparison of weight estimate and rising plate meter methods to measure herbage mass of a mountain meadow. J. Range Manage., 42, 71-74.

Loveridge, S. (1998). Publishing research in extension. Journal of Extension [On-line], 36(3). Available: http://www.joe.org/joe/1998june/tt2.html.

Messenger, S. (1984). Treatment of chlorotic oaks and red maples by soil acidification. J. Arboric., 10, 122-128.

McDaniel, K.C., Hart, C.R., & Carrol, D.B. (1997). Broom snakeweed control with fire on New Mexico blue grama rangeland. J. Range Manage., 50, 652-659.

Miller, B., E. Adams, P. Peterson, & R. Karow. (1992). On-farm testing A grower's guide. Extension bulletin EB1706, Washington State University, Pullman.

Nafziger, E.D. (1984). Use of demonstration plots as extension tools. J. Agron. Educ., 13, 47-49.

O'Neill, B. (1990). How to get published in a professional journal. Journal of Extension [On-line], 28(3). Available: http://www.joe.org/joe/1990fall/tt2.html

Owens, V.N., Albrecht, K.A., & R. W. Hintz. (1995). A rapid method for predicting alfalfa quality in the field. J. Prod. Agric., 8, 491-495.

Peryea, F.J. & Kammereck, R. (1997). Use of Minolta SPAD-502 chlorophyll meter to quantify the effectiveness of mid-summer trunk injection of iron on chlorotic pear trees. J. Plant Nutrit., 20, 1457-1463.

Posner, J.L. & Crawford, E.W. (1992). Improving fertilizer recommendations for subsistance farmers in West Africa: The use of agro-economic analysis of on-farm trials. Fert. Res., 32, 333-342.

Prasad, M. & Spiers, T.M. (1984). Evaluation of a rapid method for plant sap nitrate analysis. Comm. Soil Sci. Plant Anal., 15, 673-679.

Rzewnicki, P. (1991). Farmers' perceptions of experiment station research, demonstrations, and on-farm research in agronomy. J. Agron. Educ., 20, 31-36.

Schuman, G.E. & Rauzi, F. (1981). Microwave drying of rangeland forage samples. J. Range Manage., 34, 426-428.

Scrivner, J.H., Center, D.M., & Jones, M.B. (1986). A rising plate meter for estimating production and utilization. J. Range Manage., 39, 475-477.

Steckel, L.E., Defelice, M.S., & Sims, B.D. (1990). Integrating reduced rates of post-emergence herbicides and cultivation for broadleaf weed control in soybeans (Glycine max). Weed Sci., 38, 541-545.

Sulc, R.M., Albrecht, K.A., Cherney, J.H., M.H. Hall, Mueller, S.C., & Orloff, S.B. (1997). Field testing a rapid method for estimating alfalfa quality. Agron. J., 89, 952-957.

Varvel, G.E., Schepers, J.S., & Francis, D.D. (1997). Ability for in-season correction of nitrogen deficiency in corn using chlorophyll meters. Soil Sci. Soc. Am. J. 61, 1233-1239.

Wehner, D.J., & J.E. Haley. (1990). Iron Fertilization of kentucky bluegrass. Comm. Soil Sci. Plant Anal., 21, 629-637.

Wilde, S.A. & Voigt, G.K. (1952). The determination of color of plant tissues by the use of standard charts. Agron. J. 44:499-500.

Willard, C.J. (1958). Rating scales for weed control experiments. Weeds, 6, 327-328.

In the past two years, two Internet inservice trainings have been offered to county Extension agents in various states of the Southeast. For each training, a questionnaire was used on-line, and responses were tallied and reported in Lippert, Plank, Camberato, and Chastain (1998) and Lippert and Plank (1999). The questionnaires included questions that focused on previous computer and Internet experience, assessment of the material presented, and acceptance of using the Internet to learn the material. The agent responses were overall positive and very receptive to this form of inservice training.

Subsequently, a 3-week Internet training was offered to over 150 county Extension agents from six states (Alabama, Georgia, South Carolina, North Carolina, Florida, and Virginia) for a regional training titled "Soil Acidity and Liming." Nine specialists representing these states participated in the Web development and Internet discussions. In addition to questions selected from the previously used questionnaires, a pretest and posttest were given on-line. The intent was to move beyond personal perceptions regarding the effectiveness of this form of training and use a more empirical tool for assessing the utility of Internet instruction for knowledge acquisition.

Training Objectives

Objective 1: To determine if the Internet could be successfully used for distance instruction of Extension agents with a topic covering significant theoretical concepts in addition to many practical applications.

Objective 2: To use an appropriate instrument to assess the amount of actual knowledge gain as a result of the Internet training.

Training Content and Delivery

Prior to the Internet training, several agents were randomly surveyed via e-mail and asked to suggest topics of interest as well as the preferred time of year for the training. The title "Soil Acidity and Liming" was selected in response to this informal survey. The 3-week training was held from March 22 to April 16, 1999, (with a 1-week break because many specialists were traveling that week). Even though the training was scheduled for several weeks, the actual "hands-on" learning time was intended to be about 5 hours, equivalent to a day of traditional classroom-style training.

Training material was obtained from lecture notes and Extension information available from the participating states. The material was organized into a comprehensive text for instruction. The first week's topics were "Origin and Forms of Acidity," "The Effect of Soil Acidity and Liming on Crop Growth," and "The Effect of Lime Materials on the Neutralization of Aluminum." The second week's topics were "Conventional Lime Sources and Lime Quality" and "Alternative Liming Materials." The menu page for each week's training contained learning guidelines that listed the information the agents should know by the end of that section.

The Web page was created by a graduate student programmer who incorporated text, photos, and graphics under the direction of the senior training coordinator. Labor costs for the programmer were the only appreciable expenses encumbered for the course. When the Web page was near completion, the senior training coordinator subscribed registered agents to the Listserv by using their e-mail usernames.

The training was approved for four Certified Crop Advisor (CCA) credits in soil fertility. The CCA program was established to give agricultural professionals a standardized certification of competency in various areas. Members must take CCA approved training each year to retain certification. Instructions regarding how to access the Website and to use the Listserv were sent to the agents by e-mail. The Listserv is a means of electronic communication similar to an e-mail distribution list. All specialists and county agents were subscribed to the Listserv by the senior training coordinator. An e-mail message sent to the Listserv username (in our case acidity-l@clemson.edu) went to all participants who were subscribed to this address. A reply to the Listserv likewise went back to all subscribers. The Listserv serves as a "slow motion" conversation or as an electronic "bulletin board." Access to the Listserv software was provided by the university computer center.

The URL (Web address) for the training can be found at http://hubcap.clemson.edu/~blpprt/acidity.html

During a 2-week period prior to the training, the agents were urged at four different times to take a 25-question multiple-choice pretest (Figure 1). It was developed so they could submit their answers on-line. The questions were created to cover the key points presented on the Web. The questions were reviewed by the two specialists involved with the Web page development and two specialists not involved with the training to ensure the quality of the questions. We received 121 pretest responses.

At the end of training, two Listserv appeals were made for posttest and questionnaire responses. A week later county agents were e-mailed individually to ask them to take the posttest. One final Listserv appeal for agents to take the posttest was made 10 days after the training was completed. We received 93 posttest and questionnaire responses. The questionnaire questions included: previous training completed through the Internet, extent of Web material read, extent of Listserv correspondence read, and the number of questions the respondent asked on the Listserv. At the end of the questionnaire were four open-ended questions.

Figure 1. Questions Used for the Pretest and Posttest

1. Rainfall in excess of evaporation removes primarily ____ from the soil.
2. In general, when comparing dicots to monocots, the pounds per ton of crop removal of soil calcium is:
3. Sources of acidic hydrogen in the soil do not include:
4. Which of the following creates the most soil acidity per pound of N?
5. Active acidity refers to:
6. The two main effects of acidity on plant growth are:
7. The single most important factor affecting Ca and Mg availability in acid soils is:
8. Mechanisms of phosphorus deficiency in acid soils do not include:
9. All the following micronutrients become less plant available as the soil pH increases except:
10. In acid soils, legumes often show N deficiency symptoms because:
11. Nitrification is optimal in the pH range of:
12. The main benefit of lime on crop growth is:
13. The buffer solution that was developed to determine the lime requirement for soils containing primarily kaolinitic clays having a low CEC is:
14. The material used as the standard by which the acid neutralizing capability of all other liming materials is measured is:
15. The two principal factors which influence aglime quality is its acid neutralizing capacity and:
16. The acid neutralizing capacity of lime is usually measured as the:
17. Among the following materials, which has the highest CCE?
18. A liming material has a CCE greater than 120. It probably has an appreciable amount of:
19. The particle size of ground agricultural limestone is measured by:
20. Hydrated lime is all of the following except:
21. Boiler ash ...(various properties given as possible responses to complete the sentence):
22. Flue dust ...(various properties given as possible responses to complete the sentence):
23. Paper mill lime is not commonly used for agricultural purposes because of its:
24. The most abundant element in wood ash is:
25. The major constraints to land application of wood ash do not include:

Results

Pretest and Posttest

The pretest and posttest scores are shown in Table 1. The table also indicates the number and percent of correct and incorrect responses for each of the 25 questions (grouped by subject categories), percent gain in knowledge scores from pretest to posttest, and significance levels for differences in pretest and posttest knowledge scores as determined by the Chi-square test. Paired participant and unpaired participant data were compared, and we found no differences between paired and unpaired data. Therefore, we used unpaired data because of the larger representation of participants.

Table 1
Pretest and Posttest Scores for Internet Inservice Training

For ease of reporting, the knowledge gain percentages between pretest and posttest were categorized into: 1) Substantial gain (30% and above); 2) Moderate gain (20-29%); 3) Little gain (10-19%); and 4) Negligible or no gain (0-9%). As shown in Table 1, knowledge scores for all the 25 questions increased from pretest to posttest. Of the 25 questions, seven showed substantial gains (over 30%) in knowledge scores from pretest to posttest; four questions showed moderate gain (20-29%), nine showed little gain (10-19%), and five questions showed negligible or no gain (0-9%) in scores from pretest to posttest. The five questions that showed negligible or no gain were not statistically significant at the .05 level. Overall, the knowledge score gain from pretest to posttest ranged from a low of +1% (question 25) to a high of +43% (question 22).

Findings from this training indicate that participants had some previous knowledge of the subject matter topics. Based on the percent gain in knowledge scores between the pretest and posttest, however, it was possible to increase participant knowledge in four topic areas via the Internet training.

Nature of the Listserv Discussions

There is much discussion in the literature regarding the use of the Listserv in classroom situations and how the students adapt to it. Velayo (1994) and Collins (1998) present excellent reviews of this aspect of the Listserv. They discuss various strengths of Listserv use, such as being able to collect data, reaching a large number of diverse people easily, conversations not influenced by physical responses from others, and the ability to reflect and compose a comment at the student's own pace and convenience. Both authors support this form of electronic communication as a viable learning tool.

Typically, the literature refers to classroom situations that cannot be transferred to the inservice training approach we are presenting. For example, Williams and Merideth (1996) document student use of a Listserv to supplement class discussion, but the Master's level students initially met for 32 hours the first week. The second week, they met for 19 hours, and during the last four weeks, all discussion was restricted to the Internet. Thompson et al. (1997) pointed out that for a graduate level class, where all discussion was confined to the Internet, about 15 weeks was required for the students to overcome Listserv phobia. An inservice training for professional adults that lasts only 2 or 3 weeks has considerations that are not addressed by studies of a semester-long Internet class for university students where there may or may not be face-to-face interaction.

Thirty-one agents participated in the Listserv discussions, some of them sending more than one e-mail. A previous training covering cotton fertility had a total of 59 e-mails sent through the Listserv. During this training, there were 168 e-mails posted on the Listserv, reflecting nearly a three-fold increase. The increase was likely due to the inclusion of agents from two additional states in the training (Virginia and Florida) and the use of a topic with wider appeal.

The e-mails from the agents mostly consisted of questions addressed to the specialists. A few agents initially sent e-mails addressed directly to one of the lead coordinators, who subsequently forwarded them through the Listserv. Perhaps this was due to some slight initial Listserv phobia. Only towards the end of the training did a few agents express personal views that went beyond simply asking questions. These e-mails in particular were quite lengthy.

Piburn and Middleton (1997) used a Listserv as a way of allowing the students to share their thoughts for a course preparing them for a career in middle school teaching. They noted that "Just as in spoken conversation, some people are quiet and others loquacious. The most talkative person posted 51 messages with [a total of] 790 lines. Another posted only one message consisting of one line of text. Some of the differences in verbosity were due to familiarity with the computer medium." This is likely applicable with the county agents as we observed later in the training. A comment by an agent, though, sums up the reluctance to communicate on the Listserv. "We are hesitant to ask dumb questions after hearing Ph.D.'s talk to one another." Perhaps students are more likely to ask questions on a Listserv than county agents who are already expected to be knowledgeable in many aspects of crop production. Romiszowski and de Haas (1989) also point out that "There are people who don't trust their thoughts in print. There will be an amount of people only reading messages and never responding."

Questionnaire Response Summary

The questionnaire provided space for open-ended written responses to four specific questions. When asked "What advantages do you see with Internet inservice training?" 59 agents replied that they could do the training at their own pace and when convenient. Some agents replied not having to travel (14) and low expense (16). Twenty-six agents reported that the regional approach to the training was a benefit for them because, through the Listserv discussions, they could learn about agent experiences in nearby states and have access to information from many knowledgeable specialists. Seventeen agents pointed out that they were very glad the material would remain accessible on the Web indefinitely for future reference.

Responses to the question "What disadvantages do you see with Internet inservice training?" included:

• the ease of procrastination (18),
• problems with office distractions (6),
• lack of personal contact (12),
• problems with Internet access due to computer shortages or very slow modem connections (6),
• lack of immediate feedback to Listserv questions (4),
• the possibility of a more detailed discussion to questions in a face-to-face situation (5),
• excessive e-mails (8), and
• the need for other means of agent and specialist interaction so the training won't be so passive (3).

To the question, "Regarding information delivery, what changes would you like to see when the next inservice training is offered on the Internet?" nine agents pointed out that the training would have been more convenient if scheduled in January or February, when they are not so busy. Three agents suggested some way of organizing the Listserv questions and answers by topic so the discussion wouldn't seem so disjointed. Thirty-six agents volunteered such comments as "Excellent, well thought out, great format, good text and visuals, and material organization was outstanding."

The responses to the question "What was the most important thing you learned as a result of this training?" were very consistent. Eleven agents responded "good review," eight agents responded "the economic advantages of using lime," 16 agents responded "The causes of soil acidity," and 20 agents indicated that they most benefited from the section on types and properties of alternative liming materials.

The question, "The use of the Internet can provide a learning experience as effective as a face-to-face class" received the following responses:

• strongly disagree (2%),
• disagree (17%),
• neither agree or disagree (26%),
• agree (44%), and
• strongly agree (11%).

Conclusions

The pretest and posttest results clearly show the effectiveness of the Internet for actual knowledge acquisition of theoretical and applied agricultural topics. As also found in with previous Internet trainings, there is a general acceptance of this style of learning. A majority of the agents (55%) thought that a training offered through the Internet can be as effective as a face-to-face learning environment.

A future training will incorporate a learning style test, in addition to a pretest and posttest, to see if there is a correlation between the agents' personal style of learning and their ability to learn with an Internet training. We will also study the relationship between their test performance and various demographics, such as age, level of education, sex, etc. Future training sessions will also utilize more interactive tools, such as video clips and intermittent self-grading mini-tests so the agents can monitor their own progress as they read through the material.

References

Collins, M. (1998). The use of e-mail and electronic bulletin boards in college-level biology. Journal of Computers in Mathematics and Science Teaching, 17(1), 75-94.

Lippert, R.M. & Plank, C.O. (1999). Responses to a first time use of Internet inservice training by agricultural Extension agents. Journal of Natural Resources and Life Sciences Education (in press).

Lippert, R.M., Plank, C., Camberato, J., & Chastain, J. (1998). Regional Extension in-service training via the Internet. Journal of Extension [On-line], 36(1). Available: http://www.joe.org/joe/1998february/a3.html.

Piburn, M.D. & Middleton, J.A. (1997). Listserv as journal: computer-based reflection in a program for pre-service mathematics and science teachers. Paper presented at the International Conference on Science, Mathematics and Technology Education. Hanoi, Vietnam

Romiszowski, A.J & de Haas, J.A. (1989). Computer mediated communication for instruction: using e-mail as a seminar. Educational Technology, 7-14.

Thompson, J.C., Malm, L.D., Malone, B.G., Nay, F.W., Oliver, B.E. & Saunders, N.G. (1997). Enhancing classroom interaction in distance education utilizing the world wide web. Paper presented at the annual meeting of the Mid-Western Educational Research Association. Chicago, Illinois.

Velayo, R.S. (1994). Supplementary classroom instruction via computer conferencing. Educational Technology, May-June, 20-26.

Williams, H.L. & Merideth, E.M. (1996). On-line communication patterns of novice Internet users. Computers in the Schools, 12(3), 21-31.

Bringing a group of diverse agencies together to address a common concern can challenge even the best of Extension workers. While partnerships are not always easily formed, successful partnerships can provide greater results and benefits to clientele than might otherwise be obtained.

Goal 3 of the Cooperative State Research, Education and Extension Service (CSREES) Strategic Plan is "A Healthy, Well-Nourished Population" (United States Department of Agriculture, 1997). The second objective of this goal is "to promote health, safety, and access to quality health care." Extension workers are encouraged to work with partners and cooperators to improve individual and family health status through non-formal health education and promotion programs, and to improve safety levels that could result from accidents in the home and worksites.

Community partnerships can work to address health issues by either creating an awareness of needs or creating an environment that facilitates changes (Butterfoss, Goodman, & Wandersman, 1993; Harris, Richter, Paine-Andrews, Lewis, Johnston, James, Henke, & Fawcett, 1997). When diverse groups come together to achieve a common purpose, the outcome is often more efficient and effective for the targeted audience (Hastad & Tymeson, 1997). This is especially important as we try to reach both underserved and high-risk populations in better ways (Poole & Hook, 1997). In the future, there is likely to be increasing pressure to forge new partnerships between public and private sectors to achieve these goals (KPMG Peat Marwick, 1997).

Collaborative partnerships must be mutually beneficial. Such partnerships can result in cost-savings, mutual community service, better opportunities for obtaining external funds, and educational support (Hastad & Tymeson, 1997). When colleges and universities are involved, partnership activity may become a practical training ground for students as well as an opportunity to return benefit to the community that supports them (Deutsch, 1997).

Partnerships begin with the identification of a perceived community need (Bazzoli, Stein, Alexander, Conrad, Sofaer, & Shortell, 1997; Hastad & Tymeson, 1997). Next steps include identification of those in the community who have the willingness and ability to serve in a partner relationship. Partners will take on shared responsibilities and risks as well as rewards.

In that context, this article describes the development, activities, and outcomes of a rural community health partnership. The partnership was formed to promote health and safety among a potentially underserved rural population and to encourage clientele access to existing health services.

Rural Partnership Development

The Nebraska panhandle is a large rural area (15,000 square miles) with a population density of approximately 6.25 persons per square mile. Of the 11 panhandle counties, 6 are federally designated primary care health professional shortage areas (HPSA). Three counties are federally designated medically underserved areas, and 2 other counties have populations medically underserved (Office of Rural Health, Nebraska Health & Human Services System, personal communication, August 1997).

In 1995, representatives for health service agencies and educational institutions met to discuss the health and safety needs of ranch and farm families within the region. Institutions or agencies that were represented included a regional medical center, medical foundation, university Extension service, university learning center (distance education), and the western division of a university medical center nursing college.

Early in the planning process the partners identified the four leading causes of unintentional work-related deaths for U.S. farmers to be agricultural machinery, motor vehicles, falling objects, and electricity. Agricultural machinery is also a leading cause of non-fatal injuries among farmers. Livestock-related accidents and respiratory disorders among hog and cattle confinement operators also are concerns for this population. Heart disease and cancer were identified as leading causes of death for adults in rural Nebraska, as they are in the rest of the United States population (Nebraska Department of Health, 1996).

These morbidity and mortality figures for farmers and ranchers indicated a need for a programming effort to address prevention steps. It was decided that a special event that would include a combination of health screening, educational seminars, and opportunities for immunizations would be useful.

Rural Health Partnership Activities

A 1-day educational event preceded by prearranged opportunities for health screening was organized. Opportunities for health screening were deemed essential in assisting families into the health care system. The educational seminars included topics such as:

• prevention of work-related accidents,
• working with livestock,
• tractor/power safety,
• safe use of pesticides,
• ways to prevent respiratory disorders,
• diet and heart disease,
• cancer risk reduction, and
• improving family communication.

Written screening panels provided an analysis of diet, stress, exercise, cardiac, and cancer risk factors. Physical screening for blood pressure, blood cholesterol levels, and colorectal cancer was also completed. A PAP smear and/or mammogram were available to eligible women as part of the screening package. Additional screening tests offered but not required included hearing, blood glucose, and pulmonary function tests.

The screening and assessments were scheduled to be completed prior to the conference so that results could be shared with each conference participant by registered nurses on the day of the conference. Guidance and referral were provided when necessary or indicated. To remove one of the barriers in access to quality health care, payment for the screening and tests came from subsidies from the medical foundation, when necessary.

To further meet the needs of entire farm and ranch families, an educational program for children was included. Children aged 5-to-11 attended sessions on avoiding common accidents, playing safely, and how to do a "Safety Walkabout." They attended sessions or exhibits on electrical accidents and vehicle/train accidents.

For these events the planning partners assumed various responsibilities. Cooperative Extension provided contacts with potential clientele and some of the educational programs. Personnel at the partner medical center managed screening schedules. The university learning center handled registration and marketing. Faculty and students of the college of nursing provided screening assistance, gave immunizations, and managed the children's program. Numerous volunteer nurses presented the screening results to all participants. Other speakers for the educational sessions came from the health community within the region and state.

Although the first planned educational and screening event was met with enthusiasm, some problems emerged. Schedules for some of the pre-arranged screening exams were overloaded and caused confusion among the participants. At the day-long educational activity, insufficient time was allotted with the professional nurses for the personal summary and referral of screening and assessment results. In some cases, both men and women expressed high levels of stress and confided they felt the need for help but didn't have the time, money, or confidence to seek counseling. These issues were discussed by the planning partners and helped to establish some of the changes for continuing efforts to reach this audience.

A second educational and screening event was planned for farm/ranch families. Collaborating partners were added to the planning group, including other hospitals that could serve as additional screening sites. Educational sessions for adults included farm/ranch stress, emergency first aid, arthritis/back pain, nutrition, respiratory disorders, and cancer risk reduction. A children's program was again included.

A dermatologist to conduct full body screening for skin cancer was added to the screening and assessment package. More time for summary and referral was allotted for each participant by recruiting more volunteer nurses.

Programming Outcomes

Approximately 1 year after the first two health and safety education and screening events, participants were surveyed regarding their health practices. Questions from the original health screening assessment tool were included in the survey so they could be compared to original responses. These questions centered on medical history and health habits related to food, exercise, smoking, and recommended medical screening. One hundred eighty persons were contacted, and 82 surveys were returned (46% response rate).

These planned events were found to be most helpful in improving the breast and cervical cancer screening practices of the female participants. At initial assessment, 57% of the women reported having a mammogram within the previous year, compared to 91% at the final assessment. Similarly, 60% of the women at the initial assessment reported having a clinical breast exam within the previous year, compared to 79% at the final assessment. There were also trends toward improved cervical cancer screening (62% versus 77%).

Through the continuing years of the partnership, one woman discovered a malignant breast tumor at a very early stage and sought treatment; several farmers had suspicious skin lesions removed; more than 75 people were immunized against flu, pneumonia and tetanus; and nearly 300 farmers/ranchers and their spouses have participated in educational sessions to learn ways to maintain their health and prevent disability.

The rural health partnership was formed to address a key objective of improved health and safety for this targeted audience. The planned events emphasized the importance of having regular and recommended health screening, and they were successful in assisting persons in scheduling them. Whether individuals will schedule their own screening without the reminder and support from the event organizers is yet to be determined.

Continuing Partnership

The rural health partnership has continued working together to reach the intended audience. More health professionals have volunteered to assist with immunizations, registration, on-site screening, and results and referral. Medical facilities from six communities participate in screening activities prior to educational events, which is helping to improve the access to health care for this rural population. Nursing students have been able to apply public health and community health principles as they planned the children's program, administered immunizations, and answered questions about health. Cooperative Extension has been able to expand its health and safety education outreach.

This partnership for health for farm and ranch families was established out of a common desire to develop a healthier community among those who live and work in rural Nebraska. The planning and implementation processes taught the partnership members more efficient ways to screen this sparsely dispersed and underserved population while providing educational sessions. A model has been established that could be applied in similar rural areas.

References

Bazzoli, G.J., Stein, R., Alexander, J.A., Conrad, D.A., Sofaer, S., & Shortell, S.M. (1997). Public-private collaboration in health and human service delivery: Evidence from community partnerships. The Milbank Quarterly, 75(4), 533-563.

Butterfoss, F.D., Goodman, R.M., & Wandersman, A. (1993). Community coalitions for prevention and health promotion. Health Education Research, 8, 315-319.

Deutsch, C. (1997, May-June). Mutual benefit, mutual respect. World Health, 50(3), 14-16.

Harris, K.J., Richter, K.P., Paine-Andrews, A., Lewis, R.K., Johnston, J. A., James, V., Henke, L., & Fawcett, S.B. (1997). Community partnerships: Review of selected models and evaluations of two case studies. Journal of Nutrition Education, 29(4), 189-195.

Hastad, D.N., & Tymeson, G. (1997). Demonstrating visionary leadership through community partnerships. Journal of Physical Education, Recreation & Dance, 68(5), 47-51.

KPMG Peat Marwick LLP. (1997). Organizations serving the public: Transformation to the 21st century. New York.

Nebraska Department of Health, Data Collection Section. (1996). 1996 Vital Statistics Report. Lincoln, NE.

Poole, D.L. & Hook, M.V. (1997, February). Retooling for community health partnerships in primary care and prevention [Editorial]. Health and Social Work 22(1), 2-4. Available: http://www.reeusda.gov/part/gpra/stratpl.htm

United States Department of Agriculture. (1997). Cooperative State Research, Education, and Extension Service Strategic Plan [On-line].

There is a critical need for information on the relative effectiveness of measures taken to restore or rehabilitate riparian and aquatic habitats and associated upland watersheds. In California, alone, millions of dollars are spent every year for implementing restoration projects. However, in the rush to implement restoration, few dollars have been expended on evaluation of the effectiveness of restoration projects or techniques for achieving specified objectives. Many restoration projects have been undertaken without clearly defined objectives or provisions for intermediate to long-term monitoring. If done at all, monitoring is typically limited to the implementation (i.e., construction) phase.

Restoration is often undertaken under the direction of local watershed organizations and Resource Conservation Districts. Working with such stakeholder groups is a key opportunity for Extension professionals.

In the Feather River watershed of northeastern California there has been an extremely active restoration program for the past 15 years. The Feather River Coordinated Resource Management group (CRM), a consortium of 21 local, state, and federal agencies and private landowners has implemented over 30 different stream and riparian restoration projects since 1985. Some of these involve rather extensive modifications to stream channels; others involve changing land use practices (exclusion or management of grazing) or simple revegetation.

The stated goal of the CRM is: "to maintain in perpetuity the stability, vitality, and diversity of the Feather River watershed and its communities." In general, the CRM's restoration projects have been undertaken in an opportunistic manner, responsive to cooperative landowners and availability of funding. Monitoring, however, has been short-term and limited.

In 1996, with the intention of stimulating local interest, the University of California Cooperative Extension (UCCE) held a technical workshop on ecological and environmental monitoring in the Feather River watershed. It was well attended and generated much local discussion on the need for monitoring restoration activities. Later in the year, with the support of the CRM, UCCE obtained funding for beginning the process to establish a "demonstration monitoring watershed" wherein the focus would be evaluating the effectiveness of restoration in "improving water quality and quantity" because that has been the principal aim of past restoration projects. Our objective was to designate a watershed and obtain the commitment of the Feather River CRM agencies to implement a long-term monitoring program.

In this article, we report on the methods and results of that effort. What we found working with an existing group for the purposes of establishing a monitoring program may be helpful to other Extension workers.

The Process in Theory

Our past work with the Feather River CRM had led us to conclude that its overall monitoring goal was to assess the effectiveness of both riparian and upland restoration practices. Some typical CRM riparian restoration activities include installation of check dams, stream channel realignment, streambank stabilization, and revegetation. Upland activities include road rehabilitation and forest thinning. In our proposal for funding to select a demonstration watershed we stated our assumed goal as follows:

"The goal of the Feather River Demonstration Watershed will be to provide scientific monitoring of the efficacy of watershed restoration efforts in terms of water quality as well as yield and timing and other attributes as identified."

On the basis of this assumed goal, we designed a process by which a demonstration watershed could be selected and a monitoring plan prepared. Two committees, one comprised of CRM representatives and the other comprised of outside peer reviewers, would develop and prioritize criteria for watershed selection through a DELPHI process.

In DELPHI, an initial list of criteria is given to a group. Each member ranks the criteria according to priority on a scale of 1-5 and suggests deletions or additional criteria. The analyst averages scores to develop a second list representing the ordered criteria. This list is given to the group; each member re-ranks the criteria and returns it. The reiterative process repeats until the group reaches a final consensus on priority. The final criteria would then be applied to existing data for Feather River sub-basins (approximately 5-10,000 acres in size), and one or more of these would be selected for the establishment of a monitoring program. The final step in our project would be the preparation of an effectiveness-monitoring plan, including provisions for baseline data collection. We expected to complete this project in one year.

As is usual in DELPHI, we planned to do most of the work on criteria development by mailing ranked and re-ranked lists to participants. Peer review would be accomplished primarily through the media of electronic mail. We anticipated two to three meetings of the CRM panel over the course of the project and our funding included travel costs for panel members. We did not anticipate a need for any face-to-face meetings with the peer panel.

Results

Criteria Development and Goal Formulation

We met with the Feather River CRM Management Committee to present our proposed research agenda and solicit members for the policy panel. The CRM nominated a 29-member Technical Advisory Committee (TAC) that included representatives from most member agencies, local County supervisors, private landowners, and restoration project workers. We solicited membership on the scientific review panel from academic and agency researchers. Representatives of the University of California and University of Nevada, the USDA-Forest Service, and the California Department of Forestry and Fire Protection agreed to serve on the peer panel. Of the 29 nominated TAC members, as many as 20 attended one or more of the organized workshops.

An initial questionnaire was sent to the TAC. (Copies of questionnaire forms used in this project are available on request from the authors.) We suggested the following general criteria for consideration by TAC members and asked them to rank them in terms of their importance to selection of a monitoring watershed:

Accessibility: for public involvement and education.
Representativeness: to ensure transferability of results to other watersheds.
Reference conditions: at least some parts of the watershed represent target conditions for restoration.
Existing or proposed restoration projects: the watershed has or will have projects that will be available for effectiveness monitoring.
Detailed data are available: the watershed has been subject to detailed environmental studies in the past or is proposed for studies in the future.
Land cover proportions: vegetation types, water, urban uses. Geomorphology: watershed physical and hydrologic conditions.
Habitat: diversity of aquatic, riparian and terrestrial habitats.

TAC members ranked these criteria and suggested some others related to land ownership, restrictions on uses, and historical land use. After the results of the first questionnaire were obtained, we synthesized the ranking and returned a second questionnaire to the TAC for re-ranking.

When the second questionnaire was returned to us, several things became evident. First and most important, respondents indicated a lack of consensus on our assumed goal "to evaluate effectiveness of upland and riparian restoration." There seemed to be a split in the group between the desirability of effectiveness monitoring versus "demonstration" of restoration techniques. Given that, responses on other criteria were questionable. For example, criteria related to land ownership (preference for all-public, all-private, or mixed ownership) were all ranked similarly low, indicating no clear direction. Criteria that were ranked the highest were existence of multiple land and resource management problems, representativeness, accessibility, existence of historical data, and existence of varied habitat and environmental conditions. There was no clear emphasis on effectiveness monitoring in the selection and ranking of criteria. We determined that it was necessary to backtrack and develop consensus on the goals for establishing and conducting a monitoring program.

We met with the TAC twice to develop goals. The group eventually consented to the following two-part goal statement for the demonstration watershed-monitoring program:

1) Evaluate effectiveness of restoration in reducing erosion and sedimentation, while considering effects on water quantity and flow timing, wildlife, fisheries and forage at the project, reach, and small and large watershed scales, and 2) provide opportunities for education, training and technology transfer pertinent to monitoring.

This goal was formally adopted by the TAC and by the CRM Management Committee. The first part generally corresponded to our initial understanding. The second part reflected a lesser degree of interest in effectiveness monitoring on the part of some TAC members.

During the course of developing this goal statement, several issues arose. The question of the appropriate scale for monitoring became especially important and one on which we consulted extensively with our scientific review panel. If the aim was to monitor the effectiveness of restoration in reducing erosion and sedimentation while considering effects on other values, such as wildlife, fish, etc., then the literature and our scientific panel suggested that there are different possibilities at different scales.

At the large-watershed scale (>10,000 acres), it would be possible to conduct trend monitoring of water quantity, water quality (sediment yield, sedimentation rates in reservoirs), and land cover changes. There are no documented cases of restoration effectiveness monitoring at the large-watershed scale.

The literature and our peer review panel suggested that effectiveness monitoring would be feasible at the small-watershed scale (<1000 acres) at which most studies of watershed effects from land use treatments have been conducted. Possibilities include paired experiments in geomorphically similar basins to evaluate watershed-level restoration effects on stormflow sediment, stream temperature, channel pattern, bank stability, mass wasting, and wildlife/fish/invertebrate populations. At the project-site scale (1-5 acres), monitoring would focus on implementation (i.e., was the project done as planned?), longevity (did the project survive?), and site-specific effectiveness (was a site-specific problem solved?). This type of monitoring is already being done but tends to be short-duration (1-3 years).

The realization of the effects of scale on monitoring expectations was important to the Feather River CRM because much of its hope rests on large-scale watershed benefits. The literature suggests that the likelihood of demonstrating such cumulative benefits from many individual restoration projects is low, especially in the short-term because of natural variability and the relatively small proportion of a large watershed that may be economically feasible to restore.

Related to the scale issue was the suggestion by our peer panel that the monitoring program should be based on a conceptual model of restoration effectiveness. A search of the literature indicated that there were neither models of properly functioning Sierra Nevada watersheds nor models indicating how management might alter processes to restore functions in degraded systems. Model development has since become a major part of our ongoing research agenda.

Other issues that arose included the need for a vigorous outreach program to get private landowners to cooperate with a monitoring program. This issue underlay the ambiguity in preference for land ownership in a demonstration watershed. In view of uncertainty, the TAC concluded that it would be advantageous to confine the monitoring program to public lands (i.e., National Forests) while seeking ecological and environmental representation of private lands. Also, the manner in which restoration projects had been implemented in the past (opportunistically, subject to availability of funding and landowner willingness) was seen as an obstacle to effectiveness monitoring at the watershed scale. Finally, there was a feeling in the TAC that monitoring efforts should not substitute for on-the-ground restoration activities due to limited staff and funding.

Watershed Selection

When we began this project, some TAC members had definite ideas on which sub-basins within the greater Feather River watershed would be most suitable for demonstration monitoring. The goal that was acceptable reflects the division within the group between monitoring for purposes of assessing restoration project effectiveness and demonstration for educational purposes.

While engaged in our watershed selection process, two things happened that ultimately affected the outcome. One CRM agency representative (Regional Water Quality Control Board) developed a proposal to establish 22 stations for trend monitoring throughout the Feather River watershed. This proposal became one element of what was eventually to be a multi-scale monitoring concept, including trend, effectiveness, and implementation monitoring.

The second important development was the proposal by other CRM representatives (USDA-Forest Service, primarily) to focus future restoration efforts in the 90,000-acre Last Chance watershed, the easternmost watershed that still drains to the Sacramento River. The intent for Last Chance was to emphasize restoration of meadows and associated streams and groundwater aquifers to enhance water storage, restore wet meadow communities, reduce downstream flood peaks, and augment summertime baseflows. Anecdotal evidence has indicated that check dams, grazing and vehicular exclosures, revegetation, and streambank stabilization in combination may achieve most of these effects, at least at the local level.

After developing a final list of selection criteria, the TAC used the selection criteria to screen candidate watersheds. The Last Chance basin was chosen after comparative analysis with other basins (Table 1). It was assumed that effectiveness monitoring would primarily occur at the small-watershed scale using a paired basin approach. Results of the screening indicated that Last Chance did indeed meet many criteria that are pertinent to restoration effectiveness monitoring, but the remoteness of the basin made it relatively unsuitable for public education and technical training.

The TAC concluded at this point that two different watersheds were needed--Last Chance and another, which is more accessible. By consensus, it was decided that a decision on an educational demonstration monitoring watershed would be temporarily deferred. We also deferred choice of sub-basins for comparative effectiveness monitoring until such time as restoration projects are actually proposed. The TAC concluded that detailed watershed analysis would be needed to select sub-basins.

Table 1
Final Criteria for Selecting a Demonstration Monitoring Watershed and Results of Application to Last Chance Watershed

The products of this project included a clear statement of goals, an understanding of the effects of scale on monitoring, a final choice of an effectiveness-monitoring watershed, and a proposal (now funded) for watershed trend monitoring. Coincidentally, funding was obtained for establishing some reference monitoring sites within the Last Chance watershed. The project forever changed the understanding of and support for environmental monitoring among members of the Feather River CRM. Increased awareness has created a foundation for a continuing effort. Currently, we are seeking funding to do research on meadow hydrology in the Last Chance basin.

The forwarding of recommendations to the Feather River CRM Management Committee concluded the project. Below, we discuss how the process actually used in this project compares to the process we proposed at the outset. We feel that the differences between theory and reality are an important lesson for other Extension workers. We suggest a modified process based on our experiences.

Discussion

What actually happened in this project differs from what we had anticipated in three fundamental ways.

Our assumptions about the goal for monitoring were wrong, and we had to step back and spend considerable time developing an acceptable goal.

The differences in opinion among TAC members led to the determination that effectiveness monitoring and educational objectives could not be achieved within a single watershed.

The development of selection criteria and the application of those were modified from our expectations. Although we had anticipated applying the criteria to all possible sub-basins >10,000 acres within the Feather River watershed, local knowledge and professional judgment reduced the choices a priori. Ultimately, professional judgment of the TAC was much more important in selecting the watershed than the abstract criteria.

In view of these lessons, we propose a modified process for working with a local group to select a watershed for monitoring (Figure 1). The process outlined below could be adapted to any similar project with a local watershed organization, such as restoration project site prioritization and site selection or prioritization of watersheds for conservation and protection. In our view, this modified process presents greater potential for success.

Figure 1
Modified Process for Selecting a Demonstration Monitoring Watershed

Step 1: Problem Formulation/Project Initiation (3 months):
Procure start-up funding
Establish peer and local interest panels
Preliminary data gathering
Literature search
Step 2: Establish Project Goal(s) (1 month):
Define project area
Develop overall goal statement
Peer review
Step 3: Define Monitoring Scales and Issues/Objectives (2 months):
Peer review
Step 4: Develop Conceptual Model for Watershed (1 month):
Prepare flow/process diagram for watershed
Develop sub-models indicating relationships between issues/activities and processes/results
Identify key monitoring variables for each scale/issue
Peer review
Step 5: Assemble Data Base and Determine Selection Criteria for Candidate Basins (3 months):
Delineate candidate basins
Procure data for candidate basins
Create data management system
Develop and prioritize criteria for basin selection
Step 6: Data Analysis for Basin Selection (3 months):
Develop statistical profiles for each basin based on criteria
Step 7: Select Demonstration Basin (1 month):
It is assumed here that a 10-20,000 acre basin will be selected that is representative of processes at larger scales and wherein monitoring at other finer scales can be performed.
Present results of Step 6 to local panel
Conduct selection process
Peer review
Step 8: Conduct Issue-Related Watershed Analysis for Selected Basin (6 months):
Procure funding
Generally, the goal is to determine environmental and ecological conditions relative to important issues.
Step 9: Present Results of Watershed Analysis (1 month):
Local panel review
Peer review
Step 10: Design Monitoring Plan(s) for Selected Basin (3 months):
Develop specific methodologies for monitoring at relevant scales to answer key questions and address issues. This may include an overall basin-level monitoring approach and/or specific approaches to effectiveness monitoring at paired sub-basin, reach and project level. This will depend on whether or not projects are proposed for which monitoring plans can be prepared. If no projects are proposed, specific monitoring plans may be prepared in the future. But the overall plan will be prepared and will guide monitoring at other scales.
Local panel review
Peer review
Step 11: Pilot Monitoring Program (6 months):
Procure funding
Test monitoring protocols
Revise monitoring plan(s) as necessary
Local panel review
Peer review
Step 12: Implement Long Term Monitoring (multiple years):
Procure funding

Acknowledgments

This project was funded by the University of California, Division of Agriculture and Natural Resources Competitive Grant program. The authors sincerely appreciate the willingness and determination of the Feather River Coordinated Management Group.

This article is online at http://joe.org/joe/2000april/ent-a.html.

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