Plot structure by 0L4UyZ65


									P L O T   S T R U C T U R E — L E C T U R E   N O T E

Plot structure
Plot structure—R. Coe

Even though the basic rules of experimental design remain the same,
agronomists, foresters and agroforesters face different problems when
designing a plot structure for an experiment. Agroforestry trials are often more
complex because of the presence of different components and their long-term

An agronomist will basically have to choose plot length and width and will use
standard agronomic practices for an agricultural experiment (e.g. variety
screening, fertilizer experiment). There is a lot of experience available in
standard agricultural experimental design and plot structure. The consequences
of getting it wrong are mostly limited since quite often these experiments only
last one growing season.

An agroforester will also have to choose plot length and plot width but in
addition to this will have to consider tree and crop numbers and position in an
agroforestry experiment. Being a relatively new approach to land use and a
rather complex field, there is much less experience available in agroforestry
experimental design and plot structure. Getting it wrong at the start of an
experiment can have far reaching consequences on its results and validity
because such experiments often last several years.

Plot design and types of experiments
Different types of trials may require different types of plot structure. For
example, screening trials of tree species and provenances can use a line or
a block plot structure.

                      
                                   Gross plot                        

                                                                  
                                     Net plot
                                                                  

                                      Tree                        

                                                                  

             Line plot                                      Block plot

It must be noted that only a limited number of characteristics of interest to
agroforestry can be measured in such plots.
P L O T   S T R U C T U R E — L E C T U R E   N O T E

In a process trial, the plot structure will be defined by the objective of the trial,
e.g. studying rooting depth, and such trials do not necessarily have to consider
farmer practices or particular agroforestry systems or technologies. Such trials
are implemented to address some very specific research questions.

In a systems trial, the experimental plots do have to consider existing farming
systems, practices and conditions. Experimental plots and treatments should
be designed and put together in such a way that the experiment resembles a
farmers field. In the following drawing, Plot A has hedgerows on the edges of
the plot. If new plots are added adjacent to this one, their hedgerows will be
too close too each other and the complete experiment will not resemble a field
planted under this technology. The ‘systems’ plot will reflect this much better.
             Hedge               Crop row

            Plot A                                      ‘Systems’ plot

Other examples of “systems” plots and experiments are those resembling
“trees in cropland” or “boundary planting”. In the case of a boundary planting
experiment, crops planted adjacent to the tree boundary should be grown on
an area that is sufficiently large to represent a real farming situation. Data taken
from plots with narrow crop areas do not adequately represent a farming

Plot design features
Size of plots:

In theory, larger plots give a higher precision for a fixed number of plots but a
lower precision for a fixed total area.

In practice, leaving border areas will modify theoretical considerations. Plots
must be large enough to apply the treatments and to collect the necessary
measurements. They should also be small enough to be cost effective, to
manage the experiment and to fit in the available land area.

Shape of plots:

Long thin plots are more precise than square plots of the same area but in
practice, the shape of the plots will be determined by the system under
consideration, management requirements and other practical considerations
regarding the available area.
P L O T   S T R U C T U R E — L E C T U R E   N O T E

Guard rows and border areas:

Theoretically, the measured area of a plot should behave as a whole field that
received a specific treatment and one plot should not influence another one in
any way.

Interference between plots is one of the largest sources of errors in
agroforestry experiments and will seriously affect the results and thus the
validity of the experiment. The following steps can be taken to avoid certain
types of interference:

    1.    leave large borders (costly since they will need to be managed and will
          not produce experimental data).

    2.    spatially separate the plots (requires more land and may decrease
          precision due to site heterogeneity).

    3.    physically prevent interference (root pruning, wire mesh barriers,...).
          This can be expensive and is not always effective.

The following table illustrates the types of interference one may experience in
an improved fallow experiment and ways of controlling this:

   Above ground                  At ground level                  Below ground
 light shading             water moves between            removal of water and
                             plots                           nutrients through tree root
 windbreak effect          litter moves between
 rain shadow
                                    Amelioration by:
 leaving a border          using small bunds              avoiding edges
 pruning                   replacing residues             root pruning
                            avoiding edge areas            barriers

The main problems with interference between plots are that:

    1.    the effects below ground are often not noticed in good time

    2.    the bias tends to be in favour of the “agroforestry” plot

    3.    the problems get worse with time as the trees grow and develop

    4.    remedial steps taken when the experiment is already established may
          not be effective since the problem may already have influenced the

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