The state of Montana is dominated by agriculture with 59.7 million acres either farmed or ranched, ranking Montana second in the nation. Agricultural cash receipts for 1997 were $2.4 billion, dominating other industries such as mining, gas and oil, travel and wood and paper production. In 1997, 52% of the agricultural cash receipts were due to crops with wheat, barley, hay, sugar beets and potatoes the top five ranking commodities for cash receipts.
Pest management is central to economical and sustainable crop and livestock production, maintenance of Montana's natural resources, and individual home, garden and health issues. Issues such as food safety, crop and livestock productivity, farm and ranch economic well being, human health and environmental concerns are important to a responsive Integrated Pest Management Program.
In Montana, the Integrated Pest Management Program (IPM) funds both the Insect and Disease Diagnostic Laboratories that identify insect and disease pests and provide biological and management information, free of charge to Montana clientele. Demonstrations and workshops are developed and delivered through a Mini-Grants Program that supports County-based IPM and Sustainable Agriculture projects. Information is delivered through the support of the Montana Crop Health Report, a bimonthly newsletter that delivers timely pest situations, issues, and recommendations. Intensive Crop Pest Management Schools occur each January specialized for audiences or topics such as row crops, Certified Crop Advisors, County Agent Training, forages and small grains.
Other specialized programs such as IPM in the Schools, Museum IPM, and urban IPM issues continue to be addressed. Focus projects such as Wild Oat, Wheat Curl Mite and Wheat Streak Mosaic Interactions on Spring Wheat', Replacing Summer Fallow with Legume Cover Crops: Integrated Pest Management', Pest Recommendation Delivery to Remote Users', Regional Cutworm Monitoring and Survey Program', Biological Control of the Wheat Stem Sawfly' and Monitoring and IPM Assessment Strategies for High Plains Alfalfa Weevil' have been funded through the USDA, CSREES, Western Regional IPM Grants Program during recent years. The disciplinary diversity reflects the commitment of MSU faculty in working together to achieve competitive grants funds for IPM research and education.
1. To optimize grower profitability through the use of appropriate pest management techniques.
2. Develop sustainable IPM programs for Montana citizens that consider environmental issues and risks.
3. Demonstrate IPM techniques through on-farm trials and educational programs.
4. Encourage implementation of IPM strategies.
Insect Diagnostic Laboratory: Identification of insect pests and provide biological and management information
Plant Disease Diagnostic Laboratory: Identification of plant diseases, provide biological and management information
Pest Recommendation Network: Provides weed, insect, and plant disease situations and recommendations delivered through IPM Web site. Project funded in part by WRIPM
Montana Crop Health Report: Bimonthly newsletter produced April - October.
Crop Pest Management School: Discussion of crop pest management, hands-on laboratory experience, problem-solving focusing on pest issues and up-to-date technology is delivered.
IPM/SARE Mini Grants Program: Grant funds are competitively awarded to Extension personnel to support field demonstrations, workshops, and other educational events in cooperation with County Extension personnel.
Internet Resources: WWW page that details the MSU-ES-IPM program, discussion of specific pest issues, archive of Montana Crop Health Report, and linkages to other IPM sites. http://scarab.montana.edu/ipm/
Monitoring and IPM Assessment Strategies for High Plains Alfalfa Weevil. 1998-2000. M. J. Brewer, E. J. Morrison, S. Blodgett. $65,064.
Project Summary: Productivity of alfalfa in the High Plains of the western United States, and Wyoming and Montana in particular, is limited by a short production window and by a univolitine insect pest, the alfalfa weevil, Hypera postica (Gyllenhal). Alfalfa weevil's life cycle is well synchronized to damage the first cutting crop and the regrowth of the second cutting alfalfa, thereby threatening approximately two-thirds of the production capacity of alfalfa. Alfalfa weevil can decrease production of the first two cuttings by up to 25%, and associated losses to the honeybee industry (principally honey bee kill due to insecticide use to control alfalfa weevil) are documented. Reduction of alfalfa and honey bee losses can occur by use of judicious well-timed insecticide used based on standardized monitoring and use of economic thresholds, use of alternative controls such as early first cutting and raking, and appreciation / recognition of impact of classical biocontrol agents established in the region.
Objectives:
1. Demonstrate utility of monitoring / IPM assessment strategies for alfalfa weevil and provide recommendations on the appropriate scale of application of tactics.
2. Extend information to alfalfa-producing counties in our states and package information on monitoring / IPM assessment strategies for neighboring production areas in the intermountain region of the western U.S., which share similar challenges in alfalfa production and pest management.
Regional Cutworm Monitoring Program. 1999-2002. S. Blodgett, G. D. Johnson, W. Lanier. $49,331.
Project Summary: Several species of cutworms cause serious but sporadic damage to alfalfa, sugar beets, corn and small grains in the Great Plains (Burton et al. 1980, Byers & Stuble 1987). Damage to cereal grain crops, alfalfa, and sugarbeets includes loss of stand and in several cases replanting and/or insecticide treatment for damaging larval populations. Cutworms are costly and time consuming to monitor for, involving soil sieving and inspection for small, cryptically colored worms early in the season. Activity of adult army and pale western cutworm moths can be monitored using pheromone traps to indicate relative activity of each species in an area and provide a prediction of cutworm larvae and damage the following spring. Thresholds have been developed for pale western cutworm and army cutworm, based on pheromone trap adult catches but thresholds are based on small grain and do not work well for alfalfa, sugarbeets, other crops that these cutworm species damage. Using pheromones to monitor adult populations can be used to forecast the potential risk of an outbreak of the damaging larval stage. The potential for an outbreak is great when cutworm populations are high and weather conditions are favorable for survival. By combining critical weather data for each species, a forecast would be developed to improve our ability to provide risk forecast for pale western and army cutworms. The proposed project will regionalize the cutworm monitoring project to the Northern Great Plains, incorporate critical environmental data into a risk forecast, and deliver adult cutworm activity and environmental information to County Agents, consultants, and producers throughout the Northern Great Plains.
Objectives:
1 Establish intensive monitoring sites for adult pale western and army cutworm moths in Montana, Nebraska, and Wyoming.
2 Determine the relationship between pale western and army cutworm larvae and adult pheromone trap catches.
3 Develop a simple forecast for pale western and army cutworms that incorporates adult activity (from pheromone monitoring) and critical weather data.
4 Deliver the pale western and army cutworm risk forecast, regionally.
Biological Control of the Wheat Stem Sawfly 1998-2001. W. Morrill and D. Weaver.
$62,961
Project Summary: This project will identify wheat production practices that can be used to enhance populations of native parasitoids that attack the wheat stem sawfly, Cephus cinctus Norton (Hymenoptera: Cephidae). Production practices that will be compared are chemical fallow vs. conventional tillage, solid-stemmed vs. hollow stemmed cultivars, and block vs. strip fields. The goal is to increase levels of parasitism, reduce incidence of sawfly infestations, and minimize crop losses.
The wheat stem sawfly is currently the most destructive insect pest of wheat in the northern Great Plains. Infestations cause reduced yield, lower grain quality, and difficulties during harvest. Estimated annual losses in Montana exceed $50 million.
Sawfly-resistant winter wheat cultivars are not widely grown because producers feel that they have lower yields and higher winter mortality. Tillage and insecticides are not effective control practices. There is potential for enhancing populations of two native
parasitoid species, Bracon cephi (Gahan) and B. lissogaster Muesebeck (Hymenoptera: Braconidae) to reduce the severity of crop damage caused by sawflies. These parasitoids currently effectively suppress sawfly infestations in some northwestern Montana fields. In other regions with similar production practices, comparable climate, and heavy sawfly damage, parasitoid activity is low. Factors that affect the wheat/sawfly/parasitoid interaction are not known.
Pest Recommendation Delivery to Remote Users. 1997-1998. G. D. Johnson, S. Blodgett, W. Lanier. $29,594
Project Summary: Pesticide education program in Montana are designed to provide farm applicator training in the proper selection, use, and handling of pesticides. Approximately 8,000 private applicators are licensed and 500 to 700 applicators become new licensees each year. Pesticide applicators know that the decision to apply a pesticide requires information other than pest presence of absence. MSU IPM Pest diagnostic lab submissions are entered into a database, which currently contains over three years of insect and plant disease recommendations. The information required for specific pest control decision-making is determined daily by the Diagnostic lab staff and Extension specialists and entered into a database. Currently, pesticide education sessions use traditional delivery methods such as demonstrations, slide-illustrated talks, and use of videotapes. We propose to enhance traditional methods through use of telecommunications to allow applicators to interact with the IPM Diagnostic database and bring alive a valuable and novel resource. Support will be needed to reformat, organize and implement the exiting MSU PRD infrastructure for delivery via a MSU Pest Recommendation Network integrated with the World Wide Web.
Objectives:
1. Incorporate the recommendations made by Extension specialists and staff currently contained in the Pest Recommendation Database (PRD) into a format suitable for case-based reasoning software. Using a test group evaluate the format of the case-based reasoning recommendations and adjust the case-based reasoning software according to recommendations of this test group.
2. Adjust the PRD and cased-based reasoning software for delivery through the WWW as the Pest Recommendation Network (PRN). Using a test group evaluate the ease of obtaining recommendations using the WWW and adjust the PRN according to recommendations of this test group.
3. Deploy the PRN developed in objective 2 on the WWW allowing it to be used by pesticide applicators, producers, Extension agents, specialists and staff.
4. Determine how lack of hardware, software, and/or high telephones line charges incurred by distant participants, or prospective users influence if a participant uses the PRN?
5. Determine how training in the use of the PRN software influences if a participant uses the PRN?
Wild Oat, Wheat Curl Mite and Wheat Streak Mosaic Interactions on Spring Wheat. 1996-1998. S. Blodgett, A. W. Lenssen, W. Grey, B. Maxwell. $60,081.
Project Summary: Mechanical tillage and chemical fallow are used for weed control in summer fallow because weeds deplete the limited soil water reserves that otherwise are available for crop production. Tillage buries crop residues decreasing residue cover and certain crop pests, but tillage can deleteriously affect soil structure thus increasing soil erosion by wind and water. Where tillage operations have been greatly reduced or eliminated, as in low-till, no-till, or conservation-till systems, herbicide use has increased. Several weed species commonly found in Montana cereal grain production areas, including wild oat, kochia, and Russian thistle, are exhibiting resistance to herbicides.
Research conducted in Montana has developed a viable cropping system that supplants summer fallow with cover crops incorporated as green manure in cereal grains cropping systems. Replacing fallow with a cover crop provides producers with other alternate enterprise options, including utilization as pasture, conserved for forage, or production of a seed crop, depending on moisture availability. Flexibility in management of cover corps in a wheat production system allows producers to adapt to environmental conditions, diversify enterprises, and increase revenues by marketing forage and/or legumes seed while conserving soil and water resources. Cropping systems that offer more diversity would allow producers greater economic choices in enterprise selection and alternative pest management options. Tillage operations for incorporation of green manure and seedbed preparation, as well as the competition with weeds offered by the green manure crop. All offer weed, insect, and disease control.
Pest management strategies often are developed for single pests, but agricultural producers must manage multiple pest species. We propose to investigate the multiple interactions of cover crop, wild oat, and wheat curl mite, vector of wheat streak mosaic virus, on spring wheat yield and quality. Observations strongly suggest that cropping system, wild oat, and wheat curl mite interactions may impact spring wheat differently than do these factors singularly. Additionally, we will quantify abundance and temporal distribution of the weed arthropod, and disease pests of spring wheat as influenced by interactions of cover crop, wild oat, and wheat curl mite.
Linkages between the proposed research project are through personnel with Extension appointments and by inclusion in two regional IPM Implementation Projects, one funded nationally (Pest management strategies for dryland wheat systems in the northern great plains and mountain farm regional: Development, implementation and evaluation, G. Johnson PD) and one through Western Regional IPM program (Ecologically-based IPM in dryland cropping systems. T. Holtzer, PD). Pest management strategies or insights that result from this proposed project will be implemented through a variety of county, state, regional, and national forums, including Cooperative Extension meetings, society meetings, and extension and journal publications.
Objectives:
1. Quantify interactions of pea cover crop, wild oat and wheat curl mite on spring wheat
2. Quantify abundance and temporal distribution of other weed, arthropod and disease pests in spring wheat as influenced by interactions of pea cover crop, wild oat, and wheat curl mite
Habitat Associations of Flea Beetles in the Aphthona Complex: Developing Tactics to Improve Their Rates of Establishment and Impact on Leafy Spurge. 1996. R. M. Nowerski and R. Hansen. $55,420.
Project Summary: The habitat associations of five flea beetle species will be characterized for leafy spurge infestations occurring from dry to very moist sites in the U.S. Their relationships with particular chemical and/or physical properties of the soil, chemical properties of the spurge roots/foliage, levels of plant productivity and other factors will be determined from multivariate analysis of information that largely exists in an APHIS-PPQ data base. This information will help guide the release of flea beetle species in the appropriate types of habitats in the future, and thus improve their chances for establishment and impact on leafy spurge in the U.S.
Objectives:
Microbial ecology of green manure residues as related to plant disease. 1994. N. W. Callan and D. E. Mathre.
Project Summary: Green manuring is a valuable agronomic practice and an important component of sustainable agriculture in a whole-farm system. Benefits include nitrogen fixation by legumes, increased phosphorus availability by Brassicas, improved soil tilth, and a general increase in microbiological activity. If species rotation is practiced with green manuring, further benefits accrue. While green manuring tends to reduce plant disease problems in the long term, the results obtained are often inconsistent. It is not generally known or appreciated that soil incorporation of raw plant residue may stimulate a rapid increase of fungal pathogens such as Pythium ultimum, a widespread and common cause of seed rot, damping-off, and reduced plant vigor.
Recommendations for green manure management have traditionally addressed soil fertility, but for the maximum benefit to be realized, the impact on soil microbiology must also be considered. Soil moisture, soil temperature, and the condition of the plant residue may influence the extent and diversity of colonization by microorganisms. Manipulation of the timing of both residue incorporation and irrigation could alter the microbial population of the residue and influence disease in the following crop.
This project examines the colonization of soil-incorporated green manure residues as related to disease caused by P. ultimum. We will examine the effects of soil conditions such as moisture and temperature on the interrelationships between P. ultimum and other saprophytic microorganisms which colonize dead or dying plant materials. An understanding of the microbial ecology of soil-incorporated plant residues will enable us to develop cultural guidelines for green manures and crop debris, so that farmers can derive the maximum benefit from increasing soil organic matter.
Objectives:
1. To determine the ecological succession of colonization of soil-incorporated green manure residue by Pythium ultimum and other microbial saprophytes.
2. To identify interactions between saprophytic microorganisms on soil-incorporated green manure residue.
3. To examine the effects of soil temperature and moisture on the saprophytic increase of Pythium ultimum on soil-incorporated green manure residue.
Integrated Control of Seedborne Fungal Pathogens and Damping-off of Sweet Corn. 1991. N. Callan and D. E. Mathre, Montana State University and S. K. Mohan and D. O. Wilson, University of Idaho.
Project Summary: Seedborne fungi, particularly Penicillium oxalicum and Fusarium spp., are responsible for significant stand losses in sweet corn through pre- and postemergence damping-off and seedling blight. The supersweet (sh-2) sweet corn cultivars are particularly susceptible to these diseases. Because 90% of the sweet corn seed produced in the U. S. is grown in southwest Idaho, seedborne pathogens are dispersed to a wide range of locales in the U. S. and the world.
In many locations, additional stand loss is caused by soilborne Pythium spp., particularly Pythium ultimum. The bio-priming seed treatment for sh-2 sweet corn, developed by us at Montana State University with the aid of WR-IPM funding, provides effective and reliable biocontrol of preemergence damping-off caused by this pathogen. Bio-priming, which involves hydrating seeds coated with Pseudomonas fluorescens AB254, should be an efficient method of addressing seedborne pathogens with the addition of biocontrol agents which control these fungi, or when used in conjunction with reduced rates of effective fungicides.
Our proposal involves cooperative and complementary research to be performed at Montana State University and the University of Idaho. Research at MSU will involve isolating and identifying biocontrol agents, primarily bacteria, which will control P. oxalicum and Fusarium spp. when used in the bio-priming seed treatment. Interaction of these biocontrol isolates and of chemical fungicides with bio-priming using P. fluorescens AB254 will be examined. Evaluation will take place in Montana and in Idaho. We will also determine whether P. ultimum influences the severity of diseases caused by seedborne fungi.
University of Idaho personnel will apply biocontrol agents isolated in Montana and elsewhere, as well as chemical fungicides, to harvested corn ears to eliminate or reduce the incidence and severity of fungal seed infection. Seed treated in Idaho in this manner will also be evaluated in Montana and used there in further bio-priming research.
Objectives:
1. To isolate and evaluate biocontrol agents which will suppress seedborne fungal pathogens and which are compatible with P. fluorescens AB254 when used in bio-priming. (MSU - WARC and Bozeman).
2. To integrate biological and chemical control of sweet corn pathogens by using reduced rates of chemical fungicides in conjunction with bio-priming. (MSU-Bozeman).
3. To determine whether the presence of P. ultimum in the soil influences the severity of diseases caused by seedborne Penicillium and Fusarium spp., and whether biological control of P. ultimum interacts with that of seedborne pathogens. (MSU-WARC and Bozeman).
4. To eliminate or reduce postharvest infection of sh-2 sweet corn seed by Penicillium and Fusarium spp. by applying chemical and biological agents to harvested ears. (U of I)
Summary of WRIPM grants funded in Montana 1990-1998.
| Year | No. Montana grants funded | Total number of grants funded in region |
| 1999 | 1 | |
| 1998 | 1 | 11 |
| 1997 | 1 | 8 |
| 1996 | 2 | 11 |
| 1995 | 0 | 7 |
| 1994 | 1 | 6 |
| 1993 | 0 | 8 |
| 1992 | 0 | 4 |
| 1991 | 1 | 8 |
| 1990 | 0 | 7 |
High Plains Integrated Pest Management Guide for Colorado, Western Nebraska, Montana and Wyoming (Bulletin No. 564A) provides the most recent regional recommendations for insect pest control including cultural, biological and chemical methods, guidelines for monitoring, and life cycle. This guide is updated yearly and is currently being developed for the WWW.
School IPM introduces middle school science teachers to IPM concepts and application in the school environment. IPM for Schools (ENTO 580) was offered as a 1 credit hour, distance delivery course through Burns Telecommunication Center to middle school teachers in spring 1999 by W. Lanier.
Stored Grain Adviser was developed by Kansas State University and is being distributed in cooperation with Kansas State University, Iowa State University, and Montana State University. The software program allows users to evaluate stored grain pest management needs and outcomes by inputting storage conditions.
Museum IPM provides pest identification, monitoring and control strategies specific for Montana museums.
State Programs:
Pest interactions in small grains cropping systems. Weed science, entomology, plant pathology and research station researchers are cooperating to evaluate interactions of wild oats, wheat streak mosaic virus and common root rot in Montana spring wheat fields. GIS/GPS technology is being used to map pests and yield to determine how specific pests interact in the field and how interactions should be incorporated into decision-making guidelines.
Pest Recommendation Network. xxxx
AgEnto, is an electronic information listserver initiated in 1999 to deliver responses to questions to County Extension faculty. Plans are to convert this to an interactive listserver that will allow County Extension faculty to individualize pest management recommendations.
Based on a 1998 survey conducted through MSU-Extension Service of County Extension faculty, estimates of the number of acres that utilize IPM practices was conducted. Specific questions were asked about number of acres within a county that use the following techniques for wheat and barley, alfalfa and sugar beets.
IPM Practices:
Scouting / Monitoring
Crop Rotation
Use of cultural control measures
Manipulating planting date
Resistant Varieties
Non-Chemical control practices
Use of Independent Crop Consultants
Use of all Crop Consultants
Use of at least 2 or more non-chemical pest control measures
Use of more than 4 non-chemical pest control measures
Number of clients trained in the use of IPM techniques
Results:
Table 1. Percentage of crop acres reporting the use of resistant cultivars as a pest management practice
| County | Wheat | Barley | Alfalfa | Sugarbeet |
| Lincoln | 5.7 | |||
| Lake | <1.0 | <1.0 | <1.0 | |
| Sanders | 41.0 | |||
| Powell | 35.7 | 11.4 | ||
| Silver Bow | 40.0 | |||
| Beaverhead | <1.0 | 100.0 | <1.0 | |
| Broadwater | 2.0 | |||
| Gallatin | 90.0 | 90.0 | 90.0 | |
| Park | 10.0 | 10.0 | 5.0 | |
| Cascade | 30.0 | 65.0 | 60.0 | |
| Teton | 30.0 | 80.0 | 15.0 | |
| Glacier | 85.0 | 75.0 | 5.0 | |
| Toole | 55.0 | 70.0 | 30.0 | |
| Carbon | 40.0 | 40.0 | 50.0 | 60.0 |
| Yellowstone | 40.0 | 40.0 | 25.0 | 100.0 |
| Big Horn County | 29.9 | 88.2 | ||
| Fergus | 30.0 | 20.0 | 20.0 | |
| Liberty | 30.0 | 10.0 | 2.0 | |
| Hill | 60.0 | 0.0 | ||
| Philips | 35.0 | 10.0 | 20.0 | |
| Valley | 3.0 | 9.0 | 26.4 | |
| Daniels | 50.0 | 5.0 | ||
| Sheridan | 20.0 | 10.0 | 100.0 | |
| Roosevelt | 34.8 | 85.1 | ||
| Richland | 25.0 | 25.0 | 0.0 | 40.0 |
| Dawson | 85.0 | 40.0 | 40.0 | 100.0 |
| McCone | 50.0 | 30.0 | 12.0 | |
| Garfield | 30.9 | |||
| Prairie | 60.0 | 50.0 | 50.0 | 75.0 |
| Fallon | 38.9 | 33.7 | 2.6 | |
| Powder River | 100.0 | 89.0 | 94.3 | |
| Custer | 90.0 | 80.0 | 90.0 | 90.0 |
| Flathead Res. | 90.0 | 90.0 | 80.0 | |
| Wibaux | 50.0 | 30.0 | 20.0 | |
| Chouteau | 50.0 | 2.0 | 2.0 |
Table 2. Percentage of crop acres reporting the use of field scouting or monitoring as a pest management practice
| County | Wheat | Barley | Alfalfa | Sugarbeet |
| Lincoln | <1.0 | 2.9 | ||
| Lake | <1.0 | <1.0 | <1.0 | |
| Sanders | 100.0 | 100.0 | 54.5 | |
| Mineral | 72.7 | <1.0 | <1.0 | |
| Ravalli | <1.0 | 26.3 | 1.4 | |
| Powell | 3.6 | 2.3 | ||
| Silver Bow | 100.0 | 40.0 | ||
| Beaverhead | 53.8 | 92.0 | <0.1 | |
| Lewis & Clark | <0.1 | <0.1 | <0.1 | |
| Broadwater | 47.6 | 68.9 | 54.2 | |
| Gallatin | 20.0 | 20.0 | 15.0 | |
| Park | 75.0 | 75.0 | 20.0 | |
| Cascade | 85.0 | 85.0 | 10.0 | |
| Teton | 30.0 | 60.0 | 30.0 | |
| Glacier | 5.0 | 5.0 | 5.0 | |
| Toole | 70.0 | 70.0 | 70.0 | |
| Carbon | 75.0 | 75.0 | 75.0 | 75.0 |
| Yellowstone | 80.0 | 80.0 | 70.0 | 100.0 |
| Big Horn County | ||||
| Sweet Grass | 38.5 | 29.6 | 7.9 | |
| Fergus | 42.5 | 42.5 | 30.0 | |
| Liberty | 60.0 | 60.0 | 60.0 | |
| Hill | 5.0 | 5.0 | ||
| Philips | 50.0 | 50.0 | 50.0 | |
| Valley | 4.2 | 71.8 | 33.3 | |
| Daniels | 20.0 | 5.0 | ||
| Sheridan | 20.0 | 30.0 | 100.0 | |
| Roosevelt | 16.5 | 100.0 | 4.3 | 100.0 |
| Richland | 40.0 | 40.0 | 0.0 | 100.0 |
| Dawson | 100.0 | 100.0 | 100.0 | 100.0 |
| McCone | 15.0 | 15.0 | 15.0 | |
| Garfield | 51.4 | 100.0 | ||
| Prairie | 60.0 | 40.0 | 70.0 | 75.0 |
| Wibaux | 35.0 | 35.0 | 25.0 | |
| Fallon | 36.4 | 35.0 | 10.5 | |
| Powder River | 24.1 | 25.7 | 52.8 | |
| Custer | 25.0 | 10.0 | 15.0 | 100.0 |
| Flathead Res. | 50.0 | 50.0 | 60.0 | |
| Chouteau | 10.0 | 7.0 |
Table 3. Percentage of crop acres reporting the use of crop rotation as a pest management practice
| County | Wheat | Barley | Alfalfa | Sugarbeet |
| Lake | <1.0 | <1.0 | >1.0 | |
| Mineral | 72.7 | 75.0 | 15.0 | |
| Ravalli | <1.0 | <1.0 | <1.0 | |
| Powell | 89.3 | <1.0 | ||
| Silver Bow | 100.0 | |||
| Beaverhead | 86.0 | <1.0 | <1.0 | |
| Lewis & Clark | <1.0 | <1.0 | 1.5 | |
| Broadwater | 28.6 | 19.7 | 62.5 | |
| Gallatin | 90.0 | 90.0 | 90.0 | |
| Park | 5.0 | 5.0 | 5.0 | |
| Cascade | 15.0 | 15.0 | 70.0 | |
| Teton | 40.0 | 35.0 | 80.0 | |
| Glacier | 40.0 | 40.0 | ||
| Toole | 60.0 | 60.0 | 100.0 | |
| Carbon | 65.0 | 65.0 | 50.0 | 75.0 |
| Yellowstone | 50.0 | 65.0 | 30.0 | 100.0 |
| Big Horn County | ||||
| Sweet Grass | 51.3 | 37.0 | ||
| Fergus | 55.0 | 55.0 | 55.0 | |
| Liberty | 40.0 | 40.0 | 7.1 | |
| Hill | 5.0 | 5.0 | ||
| Philips | 20.0 | 20.0 | 60.0 | |
| Valley | 2.0 | 0.0 | 1.3 | |
| Daniels | 5.0 | 2.0 | ||
| Sheridan | 10.0 | 70.0 | 100.0 | |
| Roosevelt | 56.1 | 100.0 | 100.0 | |
| Richland | 85.0 | 85.0 | 20.0 | 100.0 |
| Dawson | 100.0 | 100.0 | 100.0 | 100.0 |
| McCone | 65.0 | 65.0 | 10.0 | |
| Garfield | 61.7 | 100.0 | 1.2 | |
| Prairie | 30.0 | 50.0 | 50.0 | 90.0 |
| Wibaux | 25.0 | 25.0 | 25.0 | |
| Fallon | 40.0 | 50.0 | 1.6 | |
| Powder River | 12.1 | 85.7 | 10.5 | |
| Custer | 10.0 | 100.0 | 60.0 | 100.0 |
| Flathead Res. | 80.0 | 80.0 | 100.0 | |
| Chouteau | 70.0 | 70.0 |
Table 4. Percentage of crop acres reporting the use of planting date as a pest management practice
| County | Wheat | Barley | Alfalfa | Sugarbeet |
| Lake | <1.0 | <1.0 | ||
| Sanders | 85.0 | 81.3 | 8.1 | |
| Ravalli | 13.3 | 15.8 | <1.0 | |
| Beaverhead | <1.0 | 5.7 | ||
| Lewis & Clark | <1.0 | 6.3 | <1.0 | |
| Cascade | 55.0 | 15.0 | ||
| Teton | 70.0 | 45.0 | 20.0 | |
| Glacier | 25.0 | 25.0 | ||
| Toole | 50.0 | 50.0 | ||
| Carbon | 25.0 | 25.0 | 1.0 | 7.5 |
| Yellowstone | 40.0 | 40.0 | 10.0 | 0.0 |
| Fergus | 65.0 | 40.0 | 15.0 | |
| Liberty | 60.0 | 60.0 | ||
| Hill | 70.0 | 70.0 | ||
| Philips | 80.0 | 80.0 | ||
| Valley | 2.0 | 32.9 | ||
| Daniels | 8.0 | 1.0 | ||
| Sheridan | 50.0 | |||
| Roosevelt | 8.2 | |||
| Richland | 40.0 | 40.0 | 0.0 | |
| Dawson | 20.0 | 20.0 | 20.0 | 0.0 |
| McCone | 50.0 | 30.0 | ||
| Wibaux | 55.0 | 55.0 | ||
| Fallon | 30.0 | 30.6 | 2.1 | |
| Powder River | 12.1 | 10.0 | 0.0 | |
| Custer | 20.0 | 20.0 | 20.0 | |
| Flathead Res. | 75.0 | 75.0 | 30.0 | |
| Prairie | 70.0 | 40.0 | 30.0 | 50.0 |
| Chouteau | 60.0 | <1.0 | ||
| Park | 15.0 | 15.0 | ||
| Gallatin | 10.0 | 10.0 |
Table 5. Percentage of crop acres reporting the use of cultural controls such as swathing, tillage/summer fallowing for weed control, burning, early cutting as pest management practices.
| County | Wheat | Barley | Alfalfa | Sugarbeet |
| Lake | <1.0 | 21.2 | <1.0 | |
| Sanders | 82.5 | 81.3 | 40.9 | |
| Mineral | 27.3 | |||
| Ravalli | 13.3 | <1.0 | <1.0 | |
| Silver Bow | 100.0 | |||
| Beaverhead | 61.3 | 5.7 | 10.2 | |
| Lewis & Clark | 0.9 | 1.3 | <1.0 | |
| Broadwater | 6.0 | 4.2 | ||
| Gallatin | 90.0 | 90.0 | 60.0 | |
| Park | 20.0 | 0.0 | 20.0 | |
| Cascade | 80.0 | 80.0 | 5.0 | |
| Teton | 40.0 | 80.0 | 20.0 | |
| Glacier | 40.0 | 40.0 | 20.0 | |
| Toole | 80.0 | 80.0 | 30.0 | |
| Carbon | 15.0 | 15.0 | 50.0 | 35.0 |
| Yellowstone | 95.0 | 95.0 | 95.0 | 95.0 |
| Big Horn County | 100.0 | 100.0 | 2.5 | 0.2 |
| Fergus | 95.0 | 95.0 | 35.0 | |
| Liberty | 80.0 | 80.0 | 10.0 | |
| Hill | 70.0 | 70.0 | 3.8 | |
| Philips | 90.0 | 90.0 | 70.0 | |
| Valley | 40.0 | 45.0 | 35.0 | |
| Daniels | 80.0 | 5.0 | ||
| Sheridan | 10.0 | 10.0 | 70.0 | |
| Roosevelt | 46.2 | 70.4 | 6.5 | 100.0 |
| Richland | 60.0 | 60.0 | 82.5 | 12.2 |
| Dawson | 50.0 | 50.0 | 40.0 | 40.0 |
| McCone | 5.0 | 5.0 | 25.0 | |
| Garfield | 77.2 | 93.3 | 29.4 | |
| Prairie | 70.0 | 70.0 | 75.0 | 75.5 |
| Wibaux | 60.0 | 60.0 | 80.0 | |
| Fallon | 31.9 | 100.0 | 10.5 | |
| Powder River | 12.1 | 68.6 | 52.8 | |
| Custer | 100.0 | 100.0 | 100.0 | 100.0 |
| Flathead Res. | 25.0 | 35.0 | 20.0 | |
| Chouteau | 50.0 | 5.0 | 30.0 |
Table 6. Percentage of crop acres reporting the use of one non-chemical pest management practice.
| County | Wheat | Barley | Alfalfa | Sugarbeet |
| Lincoln | <1.0 | |||
| Lake | <1.0 | 6.0 | <1.0 | |
| Sanders | <1.0 | |||
| Ravalli | 13.3 | <1.0 | <1.0 | |
| Silver Bow | <1.0 | <1.0 | ||
| Beaverhead | <1.0 | <1.0 | <1.0 | |
| Lewis & Clark | <1.0 | <1.0 | <1.0 | |
| Gallatin | 90.0 | 90.0 | 90.0 | |
| Park | 5.0 | 5.0 | 20.0 | |
| Cascade | 100.0 | 100.0 | 70.0 | |
| Teton | 65.0 | 80.0 | 30.0 | |
| Glacier | 90.0 | 90.0 | 75.0 | |
| Toole | 65.0 | 65.0 | 65.0 | |
| Carbon | 95.0 | 95.0 | 95.0 | 95.0 |
| Yellowstone | 75.0 | 75.0 | 60.0 | 100.0 |
| Big Horn County | <1.0 | |||
| Sweet Grass | <1.0 | <1.0 | <1.0 | |
| Fergus | 97.0 | 97.0 | 35.0 | |
| Liberty | 70.0 | 70.0 | 80.0 | |
| Hill | 70.0 | 70.0 | <1.0 | |
| Philips | 90.0 | 90.0 | 70.0 | |
| Valley | 5.0 | 5.0 | 5.0 | |
| Daniels | 60.0 | 20.0 | 100.0 | |
| Sheridan | >0.1 | 0.6 | ||
| Roosevelt | 3.3 | |||
| Richland | 90.0 | 90.0 | 90.0 | 100.0 |
| Dawson | 100.0 | 100.0 | 100.0 | 100.0 |
| Garfield | 25.7 | 13.3 | 5.9 | |
| Prairie | 60.0 | 50.0 | 40.0 | 60.0 |
| Fallon | 54.6 | 30.0 | 21.1 | |
| Powder River | 10.0 | 10.0 | 45.0 | |
| Custer | 100.0 | 100.0 | 100.0 | |
| Flathead Res. | 92.0 | 92.0 | 80.0 | |
| Wibaux | 60.0 | 60.0 | 80.0 | |
| Chouteau | 50.0 | <1.0 | 30.0 | |
| McCone | 50.0 | 50.0 | 68.0 |
Table 7. Percentage of crop acres reporting the use of 2-3 non-chemical pest management practices.
| County | Wheat | Barley | Alfalfa | Sugarbeet |
| Lake | 3.0 | 6.0 | <1.0 | |
| Sanders | 1.0 | 2.5 | <1.0 | |
| Silver Bow | 6.7 | 0.2 | ||
| Lewis & Clark | <1.0 | <1.0 | <1.0 | |
| Gallatin | 60.0 | 60.0 | 60.0 | |
| Park | <1.0 | |||
| Cascade | 55.0 | 55.0 | 5.0 | |
| Teton | 40.0 | 40.0 | 10.0 | |
| Toole | 35.0 | 35.0 | 35.0 | |
| Carbon | 60.0 | 60.0 | 60.0 | 65.0 |
| Yellowstone | 50.0 | 50.0 | 30.0 | 80.0 |
| Sweet Grass | <1.0 | <1.0 | <1.0 | |
| Fergus | 70.0 | 70.0 | 20.0 | |
| Liberty | 60.0 | 60.0 | 70.0 | |
| Hill | 70.0 | 70.0 | ||
| Philips | 5.0 | 5.0 | 5.0 | |
| Valley | 80.0 | 80.0 | 80.0 | |
| Daniels | 30.0 | 1.0 | ||
| Sheridan | 20.0 | 10.0 | 60.0 | |
| Richland | 45.0 | 45.0 | 25.0 | 80.0 |
| Dawson | 80.0 | 80.0 | 40.0 | 100.0 |
| Garfield | 10.3 | 6.7 | ||
| Prairie | 30.0 | 25.0 | 25.0 | 30.0 |
| Fallon | 9.1 | 7.5 | 3.2 | |
| Powder River | 2.0 | 2.0 | 2.0 | |
| Custer | 50.0 | 50.0 | 50.0 | 50.0 |
| Flathead Res. | 80.0 | 80.0 | 80.0 | |
| Wibaux | 40.0 | 40.0 | 20.0 | |
| Chouteau | 40.0 | <1.0 | <1.0 | |
| McCone | 30.0 | 30.0 | 50.0 | |
| Park | 3.0 | 3.0 | 3.0 | |
| Glacier | 50.0 | 50.0 | 10.0 |
Table 8. Percentage of crop acres reporting the use four or more pest management practices.
| County | Wheat | Barley | Alfalfa | Sugarbeet |
| Lake | <1.0 | |||
| Silver Bow | <1.0 | |||
| Lewis & Clark | <1.0 | >1.0 | <1.0 | |
| Cascade | 7.5 | 7.5 | ||
| Teton | 20.0 | 20.0 | 5.0 | |
| Toole | 5.0 | 5.0 | 5.0 | |
| Carbon | 12.5 | 12.5 | 12.5 | 12.5 |
| Yellowstone | 15.0 | 15.0 | 15.0 | 40.0 |
| Liberty | 5.0 | 5.0 | 5.0 | |
| Hill | 2.0 | 2.0 | 2.0 | |
| Philips | <1.0 | <1.0 | <1.0 | |
| Valley | 15.0 | 15.0 | 15.0 | |
| Sheridan | 10.0 | 0.0 | 40.0 | |
| Dawson | 20.0 | 20.0 | 20.0 | 40.0 |
| McCone | 12.0 | 12.0 | 5.0 | |
| Prairie | 12.5 | 12.5 | 10.0 | 15.0 |
| Fallon | 0.0 | 5.1 | 0.0 | |
| Powder River | <1.0 | <1.0 | <1.0 | |
| Custer | 7.5 | 7.5 | 7.5 | |
| Flathead Res. | 30.0 | 30.0 | 10.0 | |
| Wibaux | 0.0 | 0.0 | 0.0 | |
| Richland | 10.0 | 10.0 | 0.0 | |
| Daniels | 5.0 | 0.0 | ||
| Park | 0.0 | 0.0 | 0.0 | |
| Fergus | 15.0 | 15.0 | 0.0 | |
| Gallatin | 5.0 | 5.0 | 5.0 | |
| Glacier | 15.0 | 15.0 | 0.0 |
Table 9. Percentage of crop acres reporting the use of crop consultants
| County | Wheat | Barley | Alfalfa | Sugarbeet |
| Lake | ||||
| Mineral | ||||
| Ravalli | 20.0 | 26.3 | <1.0 | |
| Powell | 11.4 | |||
| Silver Bow | ||||
| Beaverhead | 14.0 | 17.2 | ||
| Lewis & Clark | <1.0 | <1.0 | 1.5 | |
| Broadwater | 4.3 | 16.4 | 4.2 | |
| Gallatin | 20.0 | 20.0 | 20.0 | |
| Park | 0.0 | 0.0 | 0.0 | |
| Cascade | 5.0 | 60.0 | 0.0 | |
| Teton | 10.0 | 70.0 | 10.0 | |
| Glacier | 30.0 | 30.0 | 40.0 | |
| Toole | 15.0 | 15.0 | 0.0 | |
| Carbon | 20.0 | 75.0 | 20.0 | 75.0 |
| Yellowstone | 25.0 | 60.0 | 20.0 | 100.0 |
| Big Horn County | 12.4 | 97.2 | <1.0 | 88.6 |
| Fergus | <5.0 | <5.0 | <2.0 | |
| Liberty | 30.0 | 30.0 | 10.0 | |
| Hill | 1.0 | 1.0 | 1.0 | |
| Philips | 70.0 | 70.0 | 50.0 | |
| Valley | 20.0 | 20.0 | 10.0 | |
| Daniels | 20.0 | 5.0 | ||
| Sheridan | 0.0 | 0.0 | ||
| Roosevelt | 100.0 | |||
| Richland | 20.0 | 20.0 | 0.0 | 100.0 |
| Dawson | 20.0 | 20.0 | 30.0 | 100.0 |
| McCone | 4.0 | 4.0 | 4.0 | |
| Prairie | 5.0 | 5.0 | 5.0 | 20.0 |
| Wibaux | 30.0 | 30.0 | 30.0 | |
| Fallon | 35.0 | 30.0 | 10.5 | |
| Powder River | 5.0 | 5.0 | 5.0 | |
| Custer | 15.0 | 15.0 | 10.0 | 100.0 |
| Flathead Res. | 25.0 | 25.0 | 20.0 | |
| Chouteau | 10.0 | 7.0 | <1.0 |
Table 10. Number of clients trained in improved pest management techniques
| County | Total number | Home gardeners | Consultants (independent & private) | Private pesticide applicators | Landscape professionals |
| Lincoln | 76 | 72 | 4 | ||
| Lake | 256 | 32 | 220 | 4 | |
| Sanders | 240 | 60 | 180 | ||
| Mineral | 84 | 37 | 47 | ||
| Ravalli | 138 | 100 | 35 | 3 | |
| Powell | 75 | 10 | 15 | ||
| Silver Bow | 144 | 58 | 78 | 8 | |
| Jefferson | 82 | 4 | 3 | 75 | |
| Beaverhead | 64 | 16 | 5 | 43 | |
| Lewis & Clark | 100 | 20 | 2 | 40 | 2 |
| Broadwater | 50 | 50 | |||
| Gallatin | 302 | 46 | 9 | 245 | 2 |
| Park | 243 | 17 | 0 | 225 | 1 |
| Cascade | 1660 | 1200 | 5 | 460 | 6 |
| Teton | 73 | 20 | 3 | 50 | 0 |
| Glacier | 72 | 15 | 2 | 55 | |
| Pondera | 200 | 30 | 2 | 50 | |
| Toole | 232 | 150 | 2 | 80 | |
| Carbon | 306 | 100 | 3 | 200 | 3 |
| Yellowstone | 537 | 2300 | 4 | 260 | 3 |
| Big Horn County | 221 | 25 | 196 | ||
| Sweet Grass | 28 | 4 | 24 | ||
| Fergus | 135 | 60 | 5 | 65 | 5 |
| Liberty | 125 | 20 | 4 | 100 | 1 |
| Hill | 405 | 100 | 300 | 5 | |
| Philips | 76 | 40 | 35 | 1 | |
| Valley | 170 | 70 | 3 | 95 | 2 |
| Daniels | 117 | 30 | 2 | 85 | 0 |
| Sheridan | 291 | 0 | 0 | 290 | 1 |
| Roosevelt | 250 | 1 | 180 | ||
| Richland | 150 | 40 | 10 | 35 | 2 |
| Dawson | 428 | 120 | 5 | 300 | 3 |
| McCone | 78 | 30 | 3 | 45 | 0 |
| Garfield | 75 | 30 | 16 | ||
| Prairie | 130 | 30 | 0 | 100 | 0 |
| Wibaux | 40 | 5 | 1 | 34 | |
| Fallon | 250 | 25 | 125 | ||
| Powder River | 120 | 35 | 85 | ||
| Custer | 212 | 100 | 10 | 100 | 2 |
| Flathead Res. | 15 | 8 | 15 | ||
| Chouteau | 472 | 83 | 4 | 15 | 2 |