Check list for planning on-station
Agroforestry experiments
Richard Coe
ICRAF, Nairobi
14 April, 1993
This checklist is designed to remind researchers of the many points to consider when
planning on-station agroforestry experiments. It is arranged in the same order and
under the same headings as the document 'Writing Research Protocols 1. On station
experiments', which in turn coincides with the layout of ICRAF's software for recording
details of experiments.
Experiment Details
Code

Does the experiment need a unique code number?
Original Title

Is the title accurate?

Is the title descriptive?

Does it distinguish this trial from others at the site?
Activity type

Are you sure the objectives can be best met with an experiment?
Research type

Are you sure the objectives are best met by doing the research
on station?

Are the results useful without any farmer's assessments?
Experiment identification details
English title.
 

Can you give an accurate translation of the original title?
1
Location

Are the climate and soil type representative?

Has previous management of the site left it in a suitable state for
your purposes?

Has the site been fully characterised?

Is there a long-term climatic record for the site?

Is the site large enough?

Is the site suitable for the experiment?
Principle Investigator

Does one person have overall responsibility for the trial, even
though it is a multi-disciplinary effort?
Collaborators

Do you have access to all the expertise needed for this
experiment?

Have you taken advice from
agronomists, economists,....?
soil
scientists,
foresters,
Start and end dates

Have you chosen a realistic start date?

Do you have time to obtain seed, prepare the site, carry out
nursery work, obtain equipment...?

Have you chosen a realistic end date by which time the objectives
can have been met?
Background and Justification
Justification

Have you done a thorough literature review of the problem?

Do you know how the results of the trial will be used?
2


Have you done an ex-ante analysis to show the value of the
results?
Are you sure no one has done this research before?

Do you know enough about the problem to completely plan the
experiment?

Do you understand the behaviour of the tree, crop and animal
species well enough to design the experiment?

Do you know who else is doing research in similar areas?

Have you sought advice from them?

Have you looked at the designs used by others to investigate
similar problems, even in other ecozones?

Are you convinced you have done enough background work to
justify starting the experiment?
Objectives

Have you specified clear and concise objectives?

Are the objectives stated as a numbered list of hypothesis to test
or quantities to estimate?

Are all the objectives justified by the background?

Can all the objectives be met by the proposed design?

Have all the useful objectives that could be met with this trial been
included?

Do you know that the tree species proposed are suitable for the
environment?

Do you know that the proposed management is suitable for those
species?
Do you have a documented source of seed for the trees?
Materials
Trees

3
Crops, Animals, Other

Are the varieties (breeds) selected suitable for the environment
and proposed management?

Are the varieties representative of those used by farmers?

Are the varieties recommended and available for use by farmers?
Methods
Treatments

Are all the treatments a consequence of the objectives?

Is every treatment necessary to meet the objectives?

Have you included appropriate controls in the list of treatments?

Can the treatments be expressed as combinations of two or more
levels of two or more factors?

If so, are all factorial combinations realistic and distinct from each
other?

Is the number of levels of any quantitative factor restricted to 2 or
3?

If not, is there any real advantage in using more levels?

Are the treatments well enough defined to be applied in the field?
Field Layout

Is the design of individual plots representative of the system with
which you want to experiment?

Are you sure the plots will not interfere with each other above
ground (e.g. shading, windbreak effects), on the ground (e.g. runoff and run-on) or below ground (roots)?

If not, can potential problems be avoided by leaving larger border
or guard areas?

Are all plots the same size?
4

If not, are you aware of the problems that can occur in layout,
management and analysis?

Can you avoid leaving gaps between the plots?

If not, will the gaps be planted up with trees or crops, to provide
as uniform an environment as possible?

Has the site been surveyed, so that unrepresentative areas
(termite hills, drainage gulleys etc) can be avoided?
Statistical Design

Has the site been surveyed to identify homogenous areas that
can constitute blocks?

Is the size of these blocks sufficiently large to contain at least one
plot of each treatment and controls?

If so, will you use a randomised block design?

If the blocks are not large enough to contain at least one plot of
each treatment and controls, do you know how to design the
experiment so that the important comparisons are estimated with
the greatest precision?

If the treatment comparisons are not orthogonal, do you know
how the data can be analyzed, and will that analysis answer the
questions the experiment is designed to pose?

Are there any regular trends across the experimental site or
material? If so, are these trends in one or both directions?

Have you considered the use of row and column designs to
remove the effects of one or two-way trends?

Is there likely to be any advantage in the use of a split plot
design?

If so, are the treatments applied to the sub-plots the ones for
which the greatest precision is required?


Will confounding of treatment factors or interactions with block
differences improve the efficiency of the design?
Have you planned to use the blocks of the experiment to absorb
as much as possible of the extraneous variation in the execution
and conduct of the experiment?

Is it possible that plots may be lost through accidents or mishaps?
5

If so, does your choice of experimental layout allow for a
meaningful interpretation of the results?

Have the treatments and controls been allocated to the plots of
the experiment by an explicit randomizing procedure?

Was a separate randomization carried out for each block or row
of the experiment?

Were the constraints on the randomization correctly applied?

Were you tempted to re-randomize any part of the allocation of
treatments and controls to plots because of apparently
unfortunate coincidences?

If so, do you have some knowledge of variation in the site or
experimental material which has not been incorporated into the
design of the experiment?

Does a plan exist, showing the allocation of the treatments and
controls to the individual plots?
Number of replications

Do you have any preliminary estimates of the precision likely to
be achieved by the experiment (expressed as a coefficient of
variation, for example)?

Is it possible to conduct a pilot experiment to determine the
coefficient of variation likely to be encountered, and to test the
experimental procedures?

Have you determined the size of the difference between
treatment means which you would regard as of practical
importance, if such a difference were to exist?

Have you calculated the number of replications that would be
necessary to match the size of the differences likely to be
detected as significant with the size of differences you regard as
of practical importance?

If there is insufficient land or experimental material for the number
of replications required to give significant differences of practical
importance, is it worth doing the experimental at all?

Do the controls need to be replicated more or less frequently than
the other treatments, in order to place greater emphasis on
particular comparisons?
6
Plot size

Will the proposed plot size enable all necessary measurements to
be made, including those which are destructive or otherwise
disturb the plot?

Will the proposed plot size enable samples large enough for
sufficient accuracy to be taken?

Is the proposed plot size sufficient for all treatments to be
properly applied?

Is the plot size the smallest that is consistent with other
constraints?
Analysis method

Do you know how all the data will be analyzed?

Have you completed a skeleton analysis of variance showing
degrees of freedom?
Management
Soil

Have you specified all soil management that will be undertaken
before the experiment?

Have you specified all soil management that will be undertaken
during the experiment?

Have you specified all crop management, including density and
spacing, weeding, use of fertilizer and pesticides and residue
management?

Have you specified all tree management, including nursery and
establishment methods, gaping, weeding, use of fertilizer and
pesticides, pruning and management of products?
Crop
Trees
Animals
7

Have you specified all aspects of animal management?
Observations and assessments

Have you defined the variables or assessments that will be
measured on each plot?

Do you have the necessary measuring instruments and observers
trained in their use?

Have all instruments been suitably calibrated and accuracy of
measurements checked?

Have you defined the time intervals at which assessments will be
made?

Have observation times been chosen to be sufficiently far apart
for important differences from the previous measurement to have
developed?

Have observation times been chosen to be close enough
together not to miss important changes?

Will any of the measurements be made on a sample, rather than
the whole plot?

If so have you determined the sample size needed?

Have you determined a suitable sampling scheme to use?

Are you aware of advantages and disadvantages of both random
and systematic sampling schemes?

Have you developed a method of recording the data, entering it
into a computer and maintaining good computer records?

If you are in doubt about the purpose of any of these questions,
should you not be consulting a statistician with experience in your
area of research?
Finally
8