Performance of agroforestry

systems under future climate:hypotheses and

methods Amber Kerr

Energy and Resources Group

February 26, 2008

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Talk outline

• Recap: Dissertation topic and goals

Why and how am I going to carry out my...

• Field work– Hypotheses and questions– Logistics, data, materials

• Simulation modeling • Meta-analysis

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I will test the overall hypothesis:

Under future climate, agroforestry systems will continue to outperform maize monoculture, but their yield advantage will be diminished due to belowground competition for water.

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If possible, I will also ask:

WHY does performance change (or not)?

• Is transpirational demand different between the systems?

• Are there differences in soil moisture?• Do rooting zones largely overlap,

implying competition for belowground resources?

• Do nutrient limitations arise as a result of water limitations?

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Five clarifications needed...

Under future climate, agroforestry systems will continue to outperform maize monoculture, but their yield advantage will be diminished due to belowground competition for water.

What aspects of climate will be manipulated? How?

What types of agroforestry systems will be compared?

How will “performance” will be measured? What about

minima and variances?How will the existence of competition be deduced?

What is the appropriate control?

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1. Future climate

• I believe that rainfall manipulations are the most practical and most interesting approach to simulating future climate.

• They have two major advantages:– Novelty (never before done on an

agroforestry system);– Direct testing of competition

hypothesis (otherwise must be answered indirectly).

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Encouragement from ICRAF

“I think rainfall manipulations are particularly valuable, particularly in Southern Africa. You should be able to build relatively inexpensive exclusions out of local materials. We’re not talking about something on the order of what Dan Nepstad did in the Amazon; I think if you aim for a few areas of 10 x 10 m, you’ll be fine.”

~ Louis Verchot, ICRAF Principal Scientist(e-mail 2/25/08)

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Low-tech, complete exclusion

• Without a major grant, I won’t be able to build the sturdy adjustable rainout shelters used by Dawson and colleagues.

• Instead, I will build simple structures to exclude all precipitation, and remove them intermittently.

D. Nepstad’s Amazon experiment

(photo: WHRC)

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Magnitude of manipulation

• To ensure I see a treatment effect, and to lessen the risk of one or two very wet years, I will aim for a level of rainfall exclusion that is more severe than expected under average future climate.

• I could also aim to alter the timing of precipitation (harsher curtailment early in the growing season).

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Rainfall: unresolved questions

• On what time schedule should I put the rainout shelters in place?– 50% of the time?– Every other storm?– More than one different type of

manipulation?

• What if the shelters don’t work?– Water addition?– Look at interannual variability?– Examine different spatial arrangements?

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2. Agroforestry systems

In an ideal world, I would consider• Multiple systems:

– Hedgerow intercropping– Relay intercropping– Improved fallows

• Multiple agroforestry speciesBut budget is unlikely to permit

this, so...

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Agroforestry systems, continued

...I will consider only one type of agroforestry system, either

• Relay intercropping, or• Hedgerow intercropping(depending on whether I have

access to established plots).Unfortunately this will mean I

cannot compare different types of agroforestry.

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3. Controls

• In an ideal world, I would include multiple controls to test different mechanistic hypotheses:– Monoculture maize

• Fertilized• Unfertilized

– Monoculture tree– Annual legume intercrop

• Due to resource constraints, probably only one control will be possible (monoculture maize).

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Plot design

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90 cmwithinrows

RidgeFurrow

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M = maizeT = tree(absent incontrols)

90 cmbetween

rows

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Whole plot:9 x 9 grid,

(7.2 m)2,81 indivs

per species

Sampledsubplot:

5 x 6 grid,(4 m)2,

30 indivsper species

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Planting density of controls

• Depending on the question you wish to test, the appropriate monoculture comparison could either be planted at– The same total density as the intercrop; or– The same conspecific density as the

intercrop.

• Since I wish to test the options actually faced by farmers, I will choose the latter configuration.

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The problem of combinatorics

• (3 treatments) + (3 controls)• 3 levels of precipitation• 2 levels of nitrogen• 6 replicates per treatment

... 6 * 3 * 2 * 6 = 216 plots! More realistic:

• (1 treatment) + (1 control)• 2 levels of precipitation• 4 replicates per treatment

... 2 * 2 * 4 = 16 plots.

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4. Metrics of performance

• The single most important variable to measure is maize yield. This is the bottom line for farmers.

• Also useful (but optional) would be:– Total maize biomass, including stover– Total tree biomass, separated into leafy

and woody components (ideally roots too!)

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Yield variability

• Farmers need to worry not only about average yield, but also minimum yield (and, in general, yield variability).

• I will not be able to test this with two years of field data.

• Instead, I will attempt to address this issue indirectly through meta-analysis and simulation modeling.

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5. Measuring competition

• The advantage of the rainfall exclusion is that it will allow me to say:If reduced precipitation has a greater negative effect on maize yield when maize is intercropped rather than grown as a monoculture, then the maize must be competing for water in the intercrop.

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Measuring competition, cont.

• Comparing yields should be adequate to determine the existence of competition, it would be better to also have data on– Root distribution– Soil moisture– Total water use– (perhaps) Water use efficiency

...to explain why competition was (or wasn’t) present in the agroforestry plots.

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Simulation modeling• Simulation modeling will allow me to:

Examine more aspects of climate change (including temperature) on a wider range of systems over longer time scales.

• Simulating actual yields is not a goal.• Improving /creating a model may be a

goal.• Progress: Am learning how to use

WaNuLCAS and corresponding with its creators; also considering different models.

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Meta-analysis

Three goals for my review of existing data:

1. Refine the questions and methods for my fieldwork.

2. Complement (and provide a reality check for) simulation model output.

3. Write a review article on the use of agroforestry for adaptation to climate change.

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What do you think?

• Will it still be useful to look at only at one type of agroforestry system?

• Beyond yield, which measurements should I prioritize? (Which mechanisms are potentially most interesting and important?)

• Is the scope of this work manageable? Have I provided a realistic budget?

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Thank you very much!In addition to everyone who helped me prepare for my qualifying exam, I would like to thank:

• Margaret Torn, for frequent conversations• Lou Verchot, for big-picture advice• Paxie Chirwa and Colin Black, for sharing

data from Makoka Research Station• Ni’matul Khasanah, for troubleshooting help

with WaNuLCAS• John Harte, Alex Farrell, Sintana Vergara,

Derek Lemoine, Mike Kiparsky, Kevin Fingerman, and Adam Smith, for feedback on an earlier talk