Systems Research: Challenges and Oppurtunities
Managing complexity in systems research
i. Managing multiple perspectives
ii. Identify windows of interest rather than boundaries
iii. Changing systems to maintain multiple perspectives
iv. Mechanistic tools may not fit
Balancing Farming Integrity and Research Needs in Simulated Cropping Systems
i. Address both ecological and economic problems/ concerns
ii. Reward structure should balance quick success with long-term benefits
iii. Perform treatments on farm-relevant scales
iv. Communicate cross disciplinary approaches with example applications
v. Embrace a dynamic research model (e.g. crop sequences)
Keeping the Research Components Integrated During the Implementation Phase
i. Need a vision keeper, group capacity builder
ii. Publish process as well as research
iii. Pursue adaptive management research
iv. Need to share common vision, or commitment to solve a problem
v. Forge shared hypothesis, detailed objectives
Including Farmers as Equal Collaborators While Also Being Efficient in Using Their Time
i. Offer fair compensation for farmer’s time
ii. Clearly outline goals, objectives, and expectations
iii. Develop a project so farmers have vested interest
iv. Develop mutual respect and honor farmer knowledge
v. Respect farmer time constraints during the growing season.
Reducing the time required for meetings in interdisciplinary research
i. Use visual tools such as concept mapping
ii. Use highly qualified and motivated research staff
iii. Invest in human capacity, such as a good facilitator
iv. find the right time for collaborators
v. empower farmer and students to take responsibility for the agenda
Melding disciplines within a systems level research project
i. Encourage more merging of disciplines in school so that new faculty are accustomed to this process
ii. Since you need multiple perspectives to understand whole systems each discipline should take the time to appreciate the strengths of all the other disciplines.
Leaving Behind the Factorial Mentality in Designing Systems Experiments
i. Don’t forget factorials but use them wisely. Consider starting with systems then working backwards. Pulling out the smaller questions to use in factorials
ii. Need new sources of funding. Current examples include SARE and NRCS Innovation Grants
iii. Need alternate publications to support systems research
iv. Appreciate the synergy of systems/ narrative as science. There is still a need to use regular quantitative analysis.
Building Flexibility into Systems Level Research
i. Put a lot of time and focus into initial design and principles. If you stick to these principles, and they are strong, then fluidity will be accepted.
ii. Build on an idea of adaptive metrics (which tell us how well we are responding to the challenges presented to us by our environments.
7 comments:
Perform objective tests that evaluate the quality of organic food (i.e. is it more valuable or not) and publish these objective tests.
Produce a textbook on how to conduct systems research and present case studies that were successful !!!!
Comment on Managing Complexity in Systems Research
Use clear language [when communicating research concepts and experimental findings]. Don’t get bogged down by semantics.
Comment on “Including Farmers as Equal Collaborators While Also Being Efficient in Using Their Time”
Farmers are our audience, bringing them into the picture will increase the relevance of [our] research and allow for a better sense of what best management practices (BMPs) are economic viable.
Comment on "Reducing the time required for meetings in interdisciplinary research"
Include technical writers in funding requests. Set framework for publication based on a definition of areas of expertise
Comment on “Melding disciplines within a systems level research project”
Always ensure that your experiments have sufficient treatment levels to prove the primary hypothesis. Treatment replication (min. 3) and experimental repetition (min. 2) should always be used!!!! You should not abandon the factorial approach! It is essential to convey accurate and compelling statistics in order to ensure that time is not wasted repeating something that should have been done in the first place. Many regulatory authorities require this kind of information in order to fully support a product or endorse something.
Comment on “Building flexibility into systems level research”
If the treatment factor is a systems-level factor, then a systems experiment reduces (or can reduce) to a standard factional design then, present it that way.
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