Adaptive nutrient management
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Adaptive Nutrient Management . Tom Morris, Associate Professor University of Connecticut [email protected] 860-486-0637 VTC Conference Call NRCS Adaptive Nutrient Management Work Team October 24, 2011. Adaptive management.

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Adaptive Nutrient Management

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Adaptive nutrient management

Adaptive Nutrient Management

Tom Morris, Associate Professor

University of Connecticut

[email protected]

860-486-0637

VTC Conference Call

NRCS Adaptive Nutrient

Management Work Team

October 24, 2011


Adaptive nutrient management

Adaptive management

Adaptive management is a process to better manage our natural resourcesConcept developed by ecologists starting in mid-1970s and is ongoingNot commonly used in agriculture, but has great benefit and value for ag


Two short definitions of adaptive management

Two short definitions of adaptive management

  • Process of dealing with uncertaintyin the management of renewable resources(Adapted from Walters, 1986)

  • An approach to natural resource policy that states: “policies are experiments; learn from them” (Lee, 1993)


Adaptive nutrient management

Adaptive Management in Agriculture

Plan

Implement

Adjust (Adoption)

Learn

Evaluate

Best results when process involves farmer from the beginning and time for learning is build in to the process


Adaptive nutrient management

Draft definition for agriculture developed by scientists from the Multistate Coordinating Committee: “Adaptive Management for Improved NutrientManagement” (NEERA 1002 and ASA Adaptive Nutrient Management Community)

An on-going process of developing improved management practices for efficient production and resource conservation by use of participatory learning through continuous systematic assessment. Participants include producers, agricultural service providers, policy makers, regulators, scientists, and other interested stakeholders.


Learning is one of the key processes

Learning is one of the key processes

Without learning policies (better practices) have low adoption rates (NMPs)

Adaptive Management greatly enhances learning and hence greatly enhances adoption of better practices


Adaptive nutrient management

  • Adaptive Nutrient Management (ANM) and Nutrient Management Plans (NMPs)

ANM enhances NMPs by adding a learning process to the plans

ANM also adds a process to document improvements in nutrient management using results fromobjective evaluations of nutrient practices at the field level


Four key principles in adult learning that led to improved practices

Four key principles in adult learning that led to improved practices

Adults are more likely to adopt new practices when:

  • They are involved in the planning and evaluation of their instruction (Farmer developed NMPs vs NMPs developed by a TSP)

  • Their learning is based on experience (including mistakes) (Evaluations provide a new experience to learn from that includes finding mistakes)


Adaptive nutrient management

Four key principles in adult learning that led to improved practices

Adults are more likely to adopt new practices when:

3. The topics are about subjects that have immediate relevance to their job or personal life (NMPs are part of their farm operations)

4. Discussions about improving a practice are problem-centered and not content-oriented (Content-oriented lectures aren’t nearly as effective as problem-centered discussions at allowing farmers to integrate new information into their existing experiences and to make improvements in practices


Why adaptive nutrient management needed

Why adaptive nutrient management needed?

Good example is nitrogen management

Much uncertainty in what rate of nitrogen to apply to corn

Uncertainty has economic and environmental consequences

Adaptive nutrient management provides additional information to reduce uncertainty


N response trials in corn belt

N response trials in Corn Belt

Scientists in Corn Belt pooled their N fertilizer response trials for corn; Created large data base of N fertilizer response trials

Calculated economic optimum N rate for trials

Created interactive web site using economic optimum N rates for trials

Data from 7 states, IA, IL, IN, MI, MN, WI, OH

1366 N response trials in data base


Adaptive nutrient management

On average the N rate calculator provides a reasonable value for N rate

Based on 188 N fertilizer response trials for corn after beans in Central Illinois:

Economic N rate 176 lbs N/acre

Range: 163-189 lbs N/acre


Adaptive nutrient management

Frequency distribution of N rates makes it difficult for farmer to chose what rate to apply

188 trials in Central Illinois

Economic N rate

176 lbs N/acre

Range: 163-189

Percent of sites in optimum

range: ~20%

No manure history


N recommendations from land grant universities using yield goal probably less accurate

N Recommendations from Land Grant Universities using Yield Goal Probably Less Accurate

N recommendations from University of Connecticut Soil Test Lab are based on yield goal

Having my name on those recommendations makes me uneasy


Adaptive nutrient management process to manage uncertainty of n rate

Adaptive nutrient management process to manage uncertainty of N rate

Three main concepts:

1. Objective evaluation of N at field level

2. Use results in a participatory education program

3. Keep environmental community informed about process and changes in practices to garner support for process


Components of one anm program for improved nitrogen management at field level

Components of one ANM program for improved nitrogen management at field level

1. Corn stalk nitrate test to evaluate rate of current practice

2. Aerial images of corn fields to evaluate uniformity of N application and uniformity of N in field

3. Replicated strip trials to evaluate:

a. rate of current practice; b. alternative form, timing, placement of N; c. potential for spatial management

4. Process to collect, analyze, summarize and send to farmers important field management data and results of evaluations

5. Group meetings in winter to discuss individual farm, group, county, multi-county, and state results by practice


Adaptive nutrient management

Corn Stalk Nitrate Test

  • Postmortem assessment of N management

  • Procedure:

    • Sample between ¼ milkline and

    • 3 weeks after black layer

    • 8” piece of stalk 6” above the

    • ground

    • Optimum 700-2000 ppm NO3-N


Adaptive nutrient management

1. Evaluate Rate of Current Practice

What fert rate apply next year?

What manure rate next year?


Adaptive nutrient management

1. Rate evaluations 2007

One farm - 41 fields – Lancaster, PA

Manure 2/4 years

Stalk Nitrate (ppm)

Optimum range (700-2000)

No Manure

Poultry

Steer

Hog

Field Number


2 evaluate uniformity of application

2. Evaluate uniformity of application

Manure application


Adaptive nutrient management

2. Evaluate field

uniformity


Adaptive nutrient management

2. Evaluate field uniformity


Adaptive nutrient management

3. Replicated strip trials

80-acre field in Iowa

Numbers show sampling locations for corn stalk nitrate test

Yields collected by combine with yield monitor and GPS


Adaptive nutrient management

Strip Trial in PA in 30-acre field


Results from anm programs

Results from ANM Programs

Iowa: 80% of farmers improved N practices

Reduced N 36 kg ha-1

Chesapeake Bay: Net reduction of 31 kg N ha-1

Small % of fields N increased

Other On-Farm programs only 1-2 years old; requires 2-3 years for farmers to improve

90-95% attendance at winter meetings


Summary

Summary

Adaptive nutrient management programs will result in more efficient management of nutrients

Our task I think is to develop guidelines for integration of adaptive nutrient management into Nutrient Management Plans


References

References

Gunderson, L. H., C. S. Holling, and S. S. Light, editors. 1995. Barriers and Bridges to the Renewal of Ecosystems and Institutions. Columbia University Press, New York.

Holling, C.S., editor. 1978. Adaptive Environmental Assessment and Management. John Wiley & Sons., New York.

Lee, K. N. 1993. Compass and Gyroscope. Integrating science and politics for the environment. Island Press, Washington, D.C.

Lee, K. N. 1999. Appraising adaptive management. Conservation Ecology 3(2):3. http://www.consecol.org/vol3/iss2/art3/

Northwest Oregon State Forests Management Plan FINAL PLAN Jan. 2001. http://www.odf.state.or.us/DIVISIONS/management/state_forests/sfplan/nwfmp01-final/17-5-Implement.prn.pdf

Peterman, R.M. 1990. Statistical power analysis can improve fisheries research and management. Can J. Fish. Aquat. Sci. 47:2-15.

Salafsky, N., R. Margoluis, and K. H. Redford. 2001. Adaptive Management: A Tool for Conservation Practitioners. http://fosonline.org/resources/Publications/AdapManHTML/adman_1.html

Walters, C. 1986. Adaptive Management of Renewable Resources. Macmillan, New York.

Walters, C., and R. Green. 1997. Valuation of Experimental Management Options for Ecological Systems. Journal of Wildlife Management 61:987-1006.


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