| FSP New |
|
THE FARMING SYSTEMS PROJECT The FSP. The USDA-ARS Farming Systems Project (FSP) at BARC is a long-term comparison of seven cropping systems established in 1993 to:
The farming systems, which were designed by a team of farmers, extension agents and scientists, represent a continuum of production strategies from conventional to organic methods. They were designed to take advantage of regional resources and markets, such as rural and municipal organic wastes, and local demand for organic food and feed grains. The seven cropping systems were laid out in replicated research plots in 1996 after a three-year site variability assessment. Agricultural Sustainability. Farming systems are complex. Soils, crops, livestock, pests, weather, farm managers, the off-farm environment, economics, social issues and other factors interact in complicated ways to influence agricultural sustainability. Widespread adoption of sustainable farming systems will therefore require that we better understand and address the ecology of farming systems, the socioeconomic constraints to farming systems management, and how to overcome barriers to the development and adoption of sustainable farming systems.  Objectives.
Organic SystemsThe FSP also has a special emphasis on organic farming systems. Our current understanding of farming systems relies heavily on reductionistic research conducted within a conventional farming context. While we have made great progress using this approach, it is inherently biased toward an industrial approach to farming. On the other hand, there is increasing evidence that organic farms may be fundamentally different than conventional farms. For example, soil microbial communities and activities, nematode communities, and crop attractiveness to insects have been shown to differ between organic and conventional farms. Additionally, there are numerous but umsubstantiated accounts of differences in weed populations and dynamics between organic and conventional farms. A basic understanding of the ecological interactions likely responsible for such differences will allow us to better address the needs of organic farmers. Interdisciplinary research, therefore, is crucial to the success of the FSP. A list of current collaborators follows. We welcome inquiries from other researchers, farmers or others interested in collaborating on DFSP research.
CollaboratorsNutrient Management and Soil Quality: Soil Microbial Biodiversity Mycorrhizae and Glomalin Crop Modeling Weed Ecology Farming Systems Project Design Beltsville Farming Systems Project (FSP) N 1.1. Project Summary Conventional field cropping systems have been criticized as being unsustainable because they contribute to environmental degradation (on-farm and off-farm) and are often economically tenuous. Organic farming has been proposed as a means of increasing environmental and economic sustainability of cropping systems. However, we have very little information about the sustainability of organic cropping systems on which to base such an assessment. This project was established at the
Objectives Objective 1: Evaluate crop performance, soil fertility, soil quality, weed population dynamics and other measures of agronomic performance among the five FSP cropping systems. Objective 2: Determine and understand mechanisms controllingcarbon (C), nitrogen (N), and phosphorus (P) dynamics, losses, and retention among the five FSP cropping systems. Objective 3: Understand the processes controlling soil biological activity and community structure among the five FSP cropping systems. Objective 4: Predict the long-term sustainability of FSP cropping systems for economic viability and environmental protection under current and future environmental and economic scenarios. Personnel SYsMichel Cavigelli, Soil Scientist, Project Lead Scientist (1.0 FTE) Yao-chi Lu, Economist (0.7 FTE) Ben Coffman, Agronomist (0.25 FTE) John Teasdale, Plant Physiologist (Weed Science) (0.25 FTE) PostdocsSteven Green, Soil Scientist (1.0 FTE), position terminates 9/7/06 Beth Hima, Economist (0.7 FTE), position terminates 7/27/06 Support Staff Anne Conklin (0.5 FTE; data management and plant sampling) Mark Davis (0.5 FTE; outreach and crop management) Linda Jawson (0.5 FTE; greenhouse gas flux), resigning 5/31/06 Ruth Mangum (0.25 FTE; weed research) 2 Students, Cavigelli crew (0.4 FTE each; plant, soil, greenhouse gas sampling) 4 Students, Mangum crew (0.1 FTE each; weed plant, soil sampling) 13 high school interns since fall 2002 (10 hours per week each during school year; greenhouse gas flux) Current Collaborators, SASLJeff Buyer, Research Chemist (soil microbial community structure) Sara Wright, Soil Scientist (soil glomalin and soil quality) Current Collaborators, BARC other than SASLSteve Britz, Plant Physiologist, Phytonutrients Lab, BHNRC (grain phytonutrients) Thanh Dao, Soil Scientist, EMBUL (soil phosphorus chemistry) Ray Hunt, Research Physical Scientist, HRSL (remote sensing) Greg McCarty, Soil Scientist, HRSL (greenhouse gas and soil analyses) Jack Meisinger, Soil Scientist, EMBUL (soil nitrogen dynamics) Jim Reeves, Research Chemist, EMBUL (soil carbon) Larry Sikora, Soil Scientist, EMBUL, retired (soil CO2 flux) Bryan Vinyard, Statistician, Biometrical Consulting Service (statistics) Current Collaborators, other than BARC
Sean Clark, Insect Ecologist, Csada Csuzdi, Biologist, Dennis Flanagan, Agricultural Engineer, ARS National Soil Erosion Research Laboratory, Foster Purrington, Entomologist, Kathy Szlavecz, Soil Ecologist, Past Collaborators Wayne Dulaney, Remote Sensing Specialist, Hydrology and Remote Sensing Laboratory, Beltsville (spatial variability) Deborah Fravel, Research Leader, ARS Vegetable Laboratory, Beltsville (soil bacteria and fungi) Peter Groffman, Microbial Ecologist, Zafar Handoo, Microbiologist, ARS Nematology Laboratory, Beltsville (soil nematodes) Laura Lengnick, Pat Millner, Microbiologist, ARS Sustainable Agricultural Systems Laboratory, Beltsville (soil arbuscular mycorrhizae) Martin Rabenhorst, Soil Taxonomist, Eric Venteris, GIS Specialist, Environmental Quality Laboratory, Beltsville (spatial variability) Long-term agricultural research projects (LTARPs) provide the only means of collecting empirical data on changes in agricultural systems that occur slowly, that have a small signal to noise ratio, and that respond to episodic events such as rainfall (Janzen, 1995). Total soil C levels, for example, change slowly. At the world's longest running LTARP in Rothamsted, England, total soil C levels continue to increase slowly toward an asymptotic maximum in soils more than 150 years after annual farmyard manure applications were initiated (Johnston, 1997). Other variables, such as biogenic greenhouse gas flux from soils, exhibit enormous temporal variability and short-term measurements may not accurately represent treatment effects (Robertson et al., 2000). LTARPs have been essential sources of robust data on cropping system sustainability (Rasmussen et al., 1998), soil C sequestration and dynamics (Paul et al., 1997), soil N retention (Drinkwater et al., 1998), global warming potential (Robertson et al., 2000), economic performance (Hanson et al., 1997; Clark et al., 1998a), response of agricultural systems to a changing climate and environment (Rasmussen et al., 1998), population dynamics of (some) pest and beneficial species (Menalled et al., 2001; Colunga-Garcia et al., 1997), and on some aspects of soil quality (Doran and Jones, 1996). LTARPs also provide essential data resources for developing and validating crop growth and ecosystem models (Parton et al., 1988; Janzen, 1995; Rasmussen et al., 1998; Grant et al., 2001). In LTARPs may be designed as factorial or systems-level experiments. In systems-level experiments, treatments differ by more than one factor. Systems-level experiments are designed to understand how complex systems function as a whole and to understand how the structure (abiotic and biotic components) of the system affects its function (Drinkwater, 2002). Systems-level research is particularly suited to understanding how organic cropping systems function because many of the management practices used in organic farming are multifunctional (Drinkwater, 2002). For example, cover crops may add biologically-fixed N, decrease N losses (Staver and Brinsfield, 1998), increase soil P availability (Cavigelli and Thien, 2003), decrease soil erosion (Macrae and Mehuys, 1985), suppress weeds (Teasdale, 1998), and provide habitat for beneficial organisms (Altieri, 1994; Lewis et al., 1997). Since incorporating cover crops into a cropping system can affect other aspects of the system, such as planting date and crop rotation, systems level research can provide information not gained using conventional factorial experiments (Drinkwater, 2002). A systems-level experiment can also help identify important ecological characteristics and weaknesses of alternative production systems. The limitation of systems-level research, of course, is that effects cannot be attributed to individual factors. But, systems-level experiments are often used to identify possible causative factors and to develop hypotheses that can be tested in more traditional factorial experiments. The Beltsville FSP is a systems-level experiment. 1.6. Relevance to ARS National Program Action Plan ARS research projects are organized into National Programs. This project is in National Program 207: Integrated Agricultural Systems (IAS). The foundation of the IAS NP is using a systems approach in developing sustainable agricultural systems. This project addresses sustainability using a systems-level long-term cropping systems project that emphasizes multidisciplinary agroecological research on a diverse range of cropping systems (no till, chisel till, and organic). The project was designed using input from farmers, extension agents, researchers and agribusiness professionals. The project continues to receive annual input from a focus group of such stakeholders. Most soil and plant samples collected are archived, which facilitates cross-site comparisons and allows questions to be addressed that were not anticipated when samples were originally collected. 1.7. Project History Origins This project was initiated in response to a need to develop more research on sustainable agriculture at BARC. The project was modeled on the Rodale Farming Systems Trial in 1993-1995: Planning and Site variability assessment From 1993 to 1995, following eight years of alfalfa, no till corn was grown on the entire site, receiving inputs consistent with local management practices. These three years were used to assess spatial variability of the site. A 25 m x 25 m grid of sampling points was established and plant and soil samples were taken annually to assess uniformity, in large part to aid in selecting areas with reasonable homogeneity in which to establish research blocks. These data have also been used to quantify underlying soil spatial variability. 1996-2005: Cropping systems plots Seven cropping systems were established in 1996 in accordance with input from a focus group composed of farmers, extension agents, and researchers. Sixty-eight plots (9.1 x 111 m) were established in four separate blocks with all rotation entry points present each year. Plots are large enough to be farmed with full sized farming equipment. Dr. Laura Lengnick (1993-1997) was the lead scientist and Bob Hoover (1996-1997) was the farm manager during the initial years of the project. Laura and Bob both left ARS at the end of 1997. During 1998 and most of 1999, there was no lead scientist assigned to the project and the project was managed by John Teasdale and Ben Coffman. Since August 1999 Michel Cavigelli has been lead scientist of the project.
2. Cropping Systems Cropping systems relevant to the mid-Atlantic region were selected with the goal of comparing a conventional no till system to a series of low input and organic alternative treatments. The seven cropping systems that were established are described in brief in the table on p. 8. Changes that have occurred in plot management in later years are also highlighted in the table and described below. 1999-2002: Reduced till organic During this period, the organic systems were managed using reduced tillage. Instead of chisel-plowing and disking the ground to prepare a seedbed and rotary hoeing and cultivating to control weeds, the existing cover crops were rolled (hairy vetch prior to corn) or mowed (rye prior to soybean) after no till planting, with the intention that the resulting mulch would suppress weed emergence and high-residue cultivation would control weeds that did emerge. This system was effective some years but became less effective with time. Due to a particularly heavy ryegrass infestation in corn, reduced till was abandoned after 2002. 2003-2005: Traditional organic tillage The organic systems were returned to traditional moldboard plow systems after minimum till proved inconsistently effective in the organic systems. Emerged weeds are now controlled by rotary hoeing and between-row cultivation. A new front-mounted cultivator that permits precision cultivation close to the crop row is used for early cultivations. 2000: Crop rotations improved In 2000, in consultation with a new focus group, FSP scientists made a number of changes to the cropping systems in accordance with evolving best management practices. 1) Systems 3 and 4 were discontinued since they depended heavily on poultry litter and composted poultry litter to supply N to crops. At the application rates necessary to achieve competitive crop yields, P applications in these systems were much higher than those recommended by the new Maryland P site index. The plots that were previously used for systems 3 and 4 were incorporated into expanded rotations in the NT, CT, and Org4 treatments as follows. 2) Wheat following corn in the NT system was prone to disease so that rotation was expanded to a corn-soybean-wheat/soybean rotation. To maintain the NT and CT systems as direct comparisons, the CT system rotation was expanded to this same 3-year rotation. 3) In the 4-year organic system, establishing a red clover-orchardgrass (RC+OG) hay crop by underseeding in wheat proved challenging. Also, the clover was often outcompeted by the orchardgrass, leaving a poor source of nitrogen for the succeeding corn crop. Therefore, the RC+OG was replaced with alfalfa, expanding the 4-year rotation to a 6-year rotation. These three changes resulted in five cropping systems that used all of the original 68 plots to account for all rotation entry points.
Cropping Systems, 1996-2005, highlighting changes made during this period.
C=corn; S=soybean; W=wheat; RC+OG=red clover + orchardgrass hay; A=alfalfa; r=rye cover crop; v=hairy vetch (or crimson clover in early years) cover crop.
2.1 Focus Group Farmers, extension agents, agribusiness professionals and other researchers were actively involved in designing the FSP treatments in 1995. A new focus group composed of similar individuals met annually from 2000 to 2003 to discuss management protocols and research direction. Beginning in 2004 we began two separate focus groups, one for the two conventional systems and one for the organic systems. Members of the conventional management team include, from the University of Maryland, Drs. Bob Kratochvil (cropping systems specialist), Ron Ritter (weed science specialist), and Les Vough (alfalfa management) and, from the BARC farm management team, Dan Shirley. Members of the organic management team include Mark Davis (former organic grain farmer) and Ed Fry ( 3. Annual Data Collection Activities Feb-Dec Weekly (April-Oct) or less frequent (Feb, March, Nov, Dec) greenhouse gas sampling March/April Weed seedbank sampling April/May Cover crop biomass sampling May Hay harvest sampling - 1st cutting June Wheat biomass sampling at soft dough stage June PSNT soil sampling in corn June-Sept Corn phenological stages June-Sept Corn and soybean LAI June Hay harvest sampling - 2nd cutting July Wheat harvest sampling August Soybean (full-season) biomass sampling August Hay harvest sampling - 3rd cutting September Weed cover ratings, biomass September Corn/soybean grain yield in weedy/weed-free subplots September Corn population count, biomass sampling September Soybean (double-crop) biomass sampling October Full-season soybean grain yield October Corn grain yield October Hay harvest sampling - 4th cutting Oct-Dec Soil fertility sampling November Double-crop soybean grain yield Outreach and Impact FSP research has been highlighted in several news releases or educational materials: •• FSP research included in "Organic Grows on •• FSP research highlighted in "An Agricultural Time Machine," Delmarva Farmer. 2002, April 2, p. 15. •• "Tilling takes toll on soil's tiny creatures, student finds" The Johns Hopkins University Gazette, 2003, 32:5. •• FSP farming techniques included in "Opportunities in Agriculture: Transitioning to Organic Production" Sustainable Agriculture Network, 2003. 30pp. •• "Navigating new waters: PURA grants launch 41 undergraduates into sea of research projects," The Johns Hopkins University Gazette, 2004, 33:11-12. •• "Longer crop rotations help organic farmers" in Research Highlights section of CSA News, October, 2004. •• "Weed seedbank dynamics in three organic farming rotations" in USDA-Organic Interest Group Recent Organic News Items, Dec., 2004. •• "Organic farming is a winner for sustainability," ARS press release about FSP research, published extensively, including in Food Industry Environmental Network (11/27/04); STAT Communication's AgReport (11/26/04); SeedQuest (11/26/04); CABI's Organic Update Newsletter (Nov. 2004); USDA-OIG's Recent Organic News Items (Dec. 2004); The New Farm (12/4/04) and USDA Radio. •• "Weed seedbank dynamics in three organic farming rotations" AgProfessional, 2005, April:56-58. •• Alex Avery, Hudson Institute, cited FSP organic research in letter to the editor of BioScience 55:820, referring in phone conversation to FSP scientists as "the most objective source for organic farming research", 2005. •• FSP research included in "Banking on BARC," The New Farm, July, 2005. •• FSP research highlighted in "From the Editor," Journal of Sustainable Agriculture 2005. 26:1-2. •• FSP scientists interviewed by Dr. Rhonda Janke, •• FSP scientists interviewed by Camille Barchers, Southern SARE Agricultural Systems Research Project Leaders, for upcoming Systems Research Handbook, June, 2005. Outreach publications •• "Another Way: Organic Grain Production," video and educational materials produced in collaboration with extension personnel from •• "Small Farm Success: Profiles of Sustainable Farming Systems," Future Harvest-Chesapeake •• "Characteristics of Sustainable Farmers: Success in the Mid-Atlantic," Future Harvest-CASA, •• Book review of "Agriculture and the nitrogen cycle: assessing the impacts of fertilizer use on food production and the environment" Ecology 2005. Professional Advisory Groups on which FSP Scientists and Staff serve •• SARE Technical Committee, 2001-2004. •• •• Northeast Region Sustainable Agriculture Research and Education (SARE) Professional Development Program (PDP) winter and summer m.eetings, 2001-2005. •• Consultation with organic farming methods with the Chesapeake Farms Sustainable Agriculture Project, Chestertown, MD, 2003. •• Co-leader of national effort to develop ARS NP 207 long-term agricultural research projects network, 2003-present. •• Chair, SARE PDP Curriculum Committee, 2004-2005. 5. Accomplishments--Summary Research conducted on the FSP has shown that: FSP Objective 1: Agronomic performance-crops •• Organic corn yields over ten years are almost always lower than conventional corn yields, likely due to various combinations of higher weed pressure, later planting date, and challenges with cover crop management in organic compared to conventional corn. •• Corn yields tend to increase with increasing rotation length in organic cropping systems, likely due in part to better weed control and enhanced fertility with increasing rotation length. •• Organic soybean yields over ten years are lower or equal to conventional soybean yields. Lower yields are likely due to greater weed pressure and later planting date in organic compared to conventional systems. •• Organic wheat yields are generally similar to conventional wheat yields. •• Soybean seed a-tocopherol as a proportion of total tocopherols was greater in 3-year organic rotations than in 2-year organic rotations and was greater in no till than in chisel till systems, but this effect was not consistent among years. Results may reflect different levels of plant stress in the different systems. •• Corn and soybean biomass were linearly correlated to a normalized green-red difference index measured using a remote-controlled model aircraft for biomass values between 0 and 120 g m-2. FSP Objective 1: Agronomic performance-weeds •• When weather and other factors allow for timely weed control in organic systems, weed control effectiveness increases with crop rotation length such that weed control in organic rotations that include a hay crop is comparable to weed control in conventional systems. •• Weed communities in organic cropping systems are dominated by pigweed and lambsquarters while grasses and perennial species are dominant in no till systems. •• Weed seedbank size is negatively related to crop rotation length among organic cropping systems. •• Weed seedbank size can be reduced by about 50% in one year with good weed control, regardless of organic crop rotation length. •• Crop loss to weeds is greatest in dry years and least in years with adequate rainfall; this effect is similar in all FSP cropping systems. FSP Objective 2: Soils and environmental quality •• Among systems with three-year crop rotations, no till cropping has the lowest and chisel till has the highest soil and nutrient erosion potential. Organic cropping systems show intermediate soil and nutrient erosion potential. Although soil quality is similar in organic and chisel till systems, organic systems have lower erosion potentials due to having plant cover during a greater proportion of the year than do chisel till systems. •• Bioactive phosphorus increases over time in soil aggregates, suggesting that P release by eroded sediments might increase with time. Dynamics of P release seem to be biologically controlled and rates seem to differ with aggregate size class. •• Soybean nitrogen fixation is lower in 6-year organic rotations than in shorter organic rotations and conventional systems, likely due to higher soil nitrogen levels in the 6-year organic system soils. •• Cumulative soil CO2 flux is greater in organic than in no till or chisel till systems (corn phase in 3-year rotations) due mostly to large CO2 fluxes in the organic system following vetch plow down and manure addition (2004), but not due to rotary hoeing and cultivation. Carbon inputs are also greater in organic than in no till and chisel till systems. •• Maximum CO2 flux occurred at lower soil moisture content in the organic system than in the no till system [20.0% vs. 27.6% soil volumetric water content (VWC), respectively]. CO2 flux was greater in the organic system than in the no till system below 29% VWC but greater in the no till system than in the organic system at soil VWC greater than 40%. These differences are likely due to higher dissolved organic carbon and lower porosity in the organic soil than in the no till soil. FSP Objective 3: Soil biological communities •• Ground beetle assemblages were distinct in organic systems compared to those in the two conventional systems. Carabid biomass is highest in organic systems, likely due to greater ground cover in organic systems than in conventional systems. •• Isopod+diplopod assemblages were often distinct in organic systems compared to those in the two conventional systems. •• Isopod and earthworm biomass are greatest in no till, lowest in chisel till and intermediate in organic systems. Differences are likely due to the detrimental effects of tillage on these soil invertebrates and to the positive effects of increased ground cover in the organic systems compared to the chisel till system. •• Tillage has a greater effect on soil hydraulic conductivity than do earthworms. Areas with earthworm burrows, however, have much higher ponded water infiltration rates than do areas with no burrows. •• Soil survey-defined soil types can be used as an initial predictor of some soil microbiological properties at the landscape level, but soil sampling probably needs to be conducted at a finer scale to adequately predict most soil microbiological properties. FSP Objective 4: Economic performance •• During the initial transition years, conventional no till cropping systems consistently show greatest economic returns among FSP cropping systems. The 3- and 4-year organic cropping systems had higher returns than conventional no till in some years and some crops. These results do not include organic premiums that can provide substantially higher revenue in some years. Research results are presented in more detail in the Research Summary section. Accomplishments have been published and presented in the following venues. Publications
•• Green, V.S., M.A. Cavigelli, T.H. Dao, and D.C. Flanagan. 2005. Soil physical properties and aggregate-associated C, N, and P distributions in organic and conventional cropping systems. Soil Sci. 170:xx-xx (in press).
Manuscripts in preparation
•• Hima, B.L., M.A. Cavigelli, Y-C. Lu , and J. Teasdale. A comparative economic analysis of the Beltsville Farming Systems Project. Journal of Sustainable Agriculture. To be submitted December 2005.
Presentations (in addition to presentations listed above under Outreach and Impacts)
•• Green, V.S., M.A. Cavigelli, T.H. Dao, and D.C. Flanagan. 2003. Cropping system effect on distribution of C, N, and P among aggregate size classes. ASA, CSSA, SSSA, annual Meeting Abstracts (CD-ROM),
•• Pitz, S.L., K. Szlavecz, and M.A. Cavigelli. 2004. Hydrology and earthworms in agroecosystems. ESA Mid-Atlantic Ecology Conference,
•• Hima, B. L., M. A. Cavigelli, Y.Lu, and J. Teasdale. 2005. A comparative economic analysis of the Farming Systems Project,
6. Challenges There are at least three factors that pose significant challenges to conducting research at the FSP site: 1) Underlying soil spatial variability, 2) Changes and inconsistencies in cropping systems management and performance during the first ten years of the project, and 3) Limited funding and personnel. These issues are discussed in some detail here and will be the focus of presentations and discussion during the afternoon of the review session, November 17. The goals of these discussions will be to determine the extent to which these challenges are barriers to meeting the four objectives of the FSP project plan, to explore avenues for surmounting these barriers, and to determine how to proceed with FSP research in light of these challenges. 6.1 Spatial variability All field projects have underlying spatial variability. The question is: how much variability is acceptable in order to conduct publishable research in a randomized complete block design, i.e. to be able to see treatment effects. And, how much underlying variability exists at FSP? While a lot of data has been collected to characterize spatial variability at FSP and a fair amount of SY time has been spent to analyze these data, there are not currently qualified personnel to fully take advantage of this rich data set. Soil wetness index at FSP site shown relative to plot locations As a result, data collected on soil quality, weed-crop competition and other parameters show high within treatment variability and, at times, strong treatment by block interactions. Examples of soil texture variability within and between blocks at FSP site Example of soil texture variability along length of one FSP plot In addition, we have a digital elevation map of the site that together with soil texture data can be used to more fully characterize the spatial variability of the site. The spatial variability at FSP can also be used to study the effect of, for example, terrain attributes (e.g. toeslope, midslope, etc) on soil characteristics, crop yields and other response variables. Compiling these complex data sets, however, requires resources and expertise not currently available among FSP staff or collaborators. Questions for discussion: •• What level of among block and within block variability is acceptable? •• How can we use the wealth of spatial variability data at the site to best account for variability in response variables? •• Is the spatial variability at the site too high or too complex to justify certain types of sampling, hypothesis testing? •• How can we take advantage of this variability to understand the impact of soil gradients on various ecosystem processes? •• Is the spatial variability at the site too high or too complex to justify continuing the project? 6.2. Changes and inconsistencies in cropping systems Various types of changes and inconsistencies have occurred in the first ten years of the FSP. 6.2.1. Changes in crop rotations in 2000 Specific changes are discussed in section 2. Cropping Systems. The implication of these changes is that not all FSP cropping systems are 10 years old. Thus, making some ten-year cropping systems comparisons is limited by these changes. In addition, plots that were taken from systems 3 and 4 and added to systems 1, 2 and 7 do not share the same number of years of management as the original plots in these systems. Questions for discussion: •• While such changes are perhaps common to LTARPs as managers learn to tweak original systems to reflect best management practices for their location, what are the implications of such changes for detecting treatment differences and for publishing research results? 6.2.2. Management changes within crop rotations Due to changes in personnel and weather, management within a cropping system has not always been consistent within the general guidelines used for a particular cropping system. For example, the changes in cover crop management and tillage in the three organic systems represent changes made in conjunction with personnel changes. Examples of a weather-related change in management within a cropping system include that wheat was not planted in the fall of 2002, 2003 and 2004 in the organic systems and in 2002 and 2003 in the conventional systems due to wet fall weather. Also, 2003 was so wet (2nd wettest year on record) that established alfalfa stands died in almost all BARC fields, including the FSP plots. These inconsistencies have resulted in incomplete yield records and in less-than-ideal performance of some cropping systems some years. While future weather is certainly beyond our control, the SYs have learned from early management decisions how best to manage the current five systems. An acceptable level of management and good growing conditions during 2004 and 2005 have provided the opportunity to obtain a relatively good assessment of the potential of the five systems in those years. Questions for discussion: •• While some of these program- and weather-related changes in management probably reflect farmer practices in the region, what are the implications for publishing research results? 6.2.3. Weather-related variability Since the FSP is not irrigated, crop yields can vary tremendously from year to year. For example, corn and soybean yields were severely reduced in all cropping systems in 4 of 10 years (1997, 1998, 1999, and 2002) due to severe droughts. In addition, the FSP site has many poorly drained areas leading to, at least, spotty areas of poor growth during wet periods and, at worst, complete crop failure (e.g. alfalfa in 2003) or inability to plant or manage crops in a timely manner (e.g. no wheat in some years or poor weed control because of inability to cultivate). With low corn yields in 2003 due to a very wet year (2nd wettest on record), half of the 10 years have had poor crop yields. In addition, site based measurements of soil parameters or soil populations of various species-especially weeds-can be influenced more by site differences in drainage than by system effects. Questions for discussion: •• What are the implications of low crop yields in half the years in a LTARP? •• What are the implications of the interactions between site drainage properties and weather on our ability to detect system differences for many soil physical, chemical, and biological parameters?
|
