(2A) Surveying Methods 1,
Surveying using quadrats
quadrat is defined as a frame, traditionally square, used
in ecology and geography to isolate a standard unit of area for study of
the distribution of an item over a large area.
You can measure how common an organism is in two
or more sampled areas of a habitat using a small quadrat and
comparing the distribution numbers of species of plants or animals in
each location in a much larger area.
For a plant in the same habitat (e.g. same field)
you might choose dry/damp areas or bright light/shaded areas or any
permutation of conditions (here 4 possibilities, yes?).
Suppose you are surveying a field, you can place
the 1 m2 quadrat in specific locations or choose some places
at random over a wide area.
The frame of the quadrat can be made of wood or
metal. Illustrated is 1 m x 1 m quadrat and wire strung across at 10 cm
intervals. In this case there 100 10x10 cm square possibilities for
sampling, each has x,y coordinates of 1-10,1-10. You do NOT count all 100
mini-squares, instead you can use a random number function on your
calculator to select e.g. 10 of them. The square with x,y co-ordinates
of 7,4 is shown on the quadrat diagram. This 'mesh' size is ok for very
small organisms e.g. tiny flowers.
I wrote myself a quick computer programme in BBC
basic (above left) to generate 10 random x,y coordinates (above
Link to the above programme
(it might work on Microsoft platforms after querying it, probably won't
work on other platforms?)
After placing the quadrat at selected locations
you e.g. count the flowers in each 10 x 10 cm2 square or the
total in the whole1 m2 of the quadrat - the whole quadrat is
1 m x 1m.
Here the yellow flowers are quite large and best
counted per 1 m2, giving you quantitative data e.g.
species of flower/m2.
To count the population using 10 x 10 cm squares
it needs to be a very small flower or insect.
Photos from the Cornfield wild flower project
Hutton-le-Hole - Ryedale Folk
Again, I've superimposed a 1 m2
quadrat, sub-divided into 20 cm x 20 cm smaller quadrats.
Here you could count each species of flower per m2
or choose a smaller are of 20 x 20 cm2 (0.04 m2
quadrat) or 40 x 40 cm2 (0.16 m2 quadrat)
areas - you just have to make a sensible decision.
of quadrat calculations based on
1. Calculating a population
Suppose you did a count of some very small
species of flower in 10 of 10 cm2 mini-quadrats (10 cm x
10 cm) of a 1 m2
quadrat placed in a sunny location. The mini-quadrats can be
selected using the random number generator.
Data counts 1-10: 7, 8, 12, 9, 9, 10, 11,
10, 9, and 8 flowers
Total count = 93 flowers
Average per 10 cm2 = 93/10 =
Now there are 100 10 cm2 squares in
the full 1 m2 quadrat.
Therefore total in 1 m2 quadrat =
9.3 x 100 = 930 flowers.
The 'flower density' =
930 per m2
If you repeated the measurements in a more shaded spot, you might find a much lower population density of
the same flower.
population size from the population density
Using the above data from small sampling areas (see also
If you know the total area, call it
A in m2,
you just multiply the 930
x A = total population in that area (see next example).
This is just a scaling up exercise from several small sample areas
chose at random.
Calculating a population
Suppose you counted the abundance of a
relatively rare flower using a 1 m2 quadrat placed
times at random across a piece of land (its habitat) measuring 80 m
x 120 m.
Flower data counts 1-8: 2, 5, 0, 1, 2, 0, 1
(a) Calculate the average density of
the rare flower per metre2
Total flower count = 15
Flower density = 15/8 =
(no need to round up at this stage)
(b) Calculate the whole population size
of the flower in this particular habitat
Total area of habitat = 80 x 120 = 9600 m2
Total population = density x total area
Population size = 1.875 x 9600 =
(maybe its not that rare in this made-up
Keywords, phrases and learning objectives for this part on ecological surveying
Be able to describe methods of data collection for surveying
the abundance of plant and animal species using quadrats.
Be able to do quadrat calculations based on sampling data
as a measure of ecology
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