(6A) Kite diagrams to show abundance and distribution of organisms

Kite diagrams are used to show abundance and distribution of organisms along a transect.

The transect can be measured out in a linear way across a habitat e.g. a field, a stretch of woodland, a rive bank - methods of surveying and using quadrats has already been described in previous sections.

You might counting the abundance of identified species in 1 m² quadrats.

A kite diagram could also be produced based on the depth of an aquatic or marine environment, where the transect is simply a vertical sampling line - you sample the water a fixed depth intervals.

You might be counting the number of identified species in given volume of water e.g. 1 litre.

An example of a kite diagram is shown below involving counting three species at 1 m intervals.

The vertical y axis represents the abundance of the organism e.g.

the percentage cover in vegetation or lichen on a stone surface,

It might represent the number of crustaceans per volume of water,

or any other quantitative measure of the abundance of an organism.

The abundance is plotted above and below the zero base line to give a symmetrical shape (often 'kite looking').

The relative abundance of each organism at a given distance along the transect is given by the thickness of the 'kit shape'

The horizontal x axis is the distance along the line of the transect.

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Examples of interpreting a kite diagram (based on repeat of diagram above)

Species 1:

To the nearest m, it occurs twice between 1 and 24 m, and, 32 and 45 m along the transect.

The maximum abundance of 14% occurs at 5 m and 18.5 m along the transect.

Species 2:

To the nearest m, it occurs three times at 1-10 m, 11-36 and 38-55 m along the transect.

The maximum abundance of 14% occurs at 29 m and 43 m along the transect.

Species 3:

To the nearest m, it occurs once between 35 and 56 m along the transect.

The maximum abundance of 22% occurs at 51 m along the transect.

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(6B) Graphical representations of biodiversity and ecology data

Examples (B = x axis, A = y axis)

Graph 1 Positive correlation

Variable B could be distance in km from a polluted urban area into farmland and woodlands.

Variable A could be a measure of biodiversity e.g. all species of animals or perhaps specific type of organism like butterflies.

A not unsurprising positive correlation as the environment becomes less polluted.

Graph 2 Negative correlation

Variable B could be the concentration of a pollutant in a lake.

Variable A could be the population density (concentration) of an organism affected by the pollution.

A not unsurprising negative correlation, increase in pollution levels, decreases the population of an organism.

Graph 3 No obvious correlation

Variable B could be the distance from the centre of deciduous woodland to the edge of the wood.

Variable A could be the population density of a particular organism e.g. a fungus growing on the ground.

If the woodland is fairly constant in composition, then you not expect any gradation in the density of the population of the fungus.

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Key points about kite diagrams of species abundances (plants or animals)

Based on the syllabus-specifications for students taking the UK AQA, Edexcel and OCR GCSE level biology examinations (~US grades 9-10 biology).

Revision notes for biology students on Kite Diagrams and Graphical Representation of Biodiversity Data - essential for understanding how ecologists visualize patterns and relationships in ecosystems.

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Kite Diagrams: Abundance & Distribution

What Is a Kite Diagram?

A kite diagram is a type of graph used in ecology to show how the abundance of organisms changes across a transect (a line through a habitat).

It provides a visual representation of where and how much of a species is found.

Structure of a Kite Diagram:

• Horizontal axis (x-axis): Distance along a transect line (e.g. from seashore inland).

• Vertical axis (y-axis): Abundance of species.

• Symmetrical shape: Each species is plotted with a shape (like a kite) extending above and below the axis, proportional to how many were found at each point.

Why Use It?

• Shows distribution patterns along environmental gradients.

• Makes it easy to compare multiple species in the same habitat.

• Highlights zones of dominance and changes in biodiversity.

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Graphical Representation of Biodiversity Data

Common Graphs in Ecology:

1. Bar Charts

• Show abundance of individual species in a single location.

• Useful for comparing species richness.

2. Line Graphs

• Track change over time or distance (e.g. along a transect).

• Ideal for continuous data, such as temperature or light.

3. Scatter Graphs

• Show correlation between two variables (e.g. light intensity versus moss cover).

• Each point represents a pair of values.

• Look for:

  • Positive correlation: both variables increase.

  • Negative correlation: one increases, the other decreases.

  • No correlation: no clear pattern.

4. Pie Charts

• Show relative abundance of species in a habitat.

• Great for illustrating species diversity and dominance.

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Biodiversity Indices (Bonus Tip!)

You might be expected to interpret or discuss biodiversity based on graphical data. Biodiversity is influenced by:

• Species richness: how many species present.

• Species evenness: how similar their abundances are.

Graphs help identify:

• Low biodiversity areas (e.g. dominated by one species).

• High biodiversity areas (many species evenly distributed).

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Exam Tips

• Practice drawing and reading kite diagrams — they often appear in paper 2 or practical questions.

• Make sure you can explain trends in a biological context (e.g. species decline due to lower moisture).

• Know when to use each graph type and what it tells you.

• Correlation ≠ causation — be cautious when interpreting scatter graphs!

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Keywords, phrases and learning objectives for this part on ecological surveying and biodiversity

Be able to draw or interpret kite diagrams to show the abundance and distribution of organisms as their population varies with some factor e.g. distance.

Understand graphical representations of biodiversity from an ecological survey and understand the importance of data correlation between two variables using graphical analysis.

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