An image of the BIFOR entrance sign

Biology A level revision resource: Measuring species diversity

Biodiversity means the variety of organisms that can be found within ecosystems. At A Level, biodiversity can refer to the number of different species present, the richness and distribution of a particular species, the diversity of habitats in an area, or even the variety of alleles of a particular gene in a population.

What methods can be used? 

You may remember methods like transects, pitfall traps and quadrats from GCSE biology. These methods are also useful at A Level and even university, however, the way that you collect and interpret data becomes more sophisticated. You can use a random, stratified, systematic or even an opportunistic strategy, depending on the types of organisms you are interested in, the ecosystem you are sampling and the research question that you want to answer.

There are advantages and disadvantages to of all of the sampling strategies, so think carefully about the methods that you use, and consider multiple approaches if you have the time and equipment. If resources are limited, then it is important to select a method that will suit your study. For example, if you want to determine the number of a particular tree species in an ecosystem then pitfall traps are unlikely to help you! However, a systematic sampling of trees (such as identifying the species of every tenth tree) might be more effective.

An image of apparatus in the forest

This image shows some of the sampling equipment used at the Birmingham Institute of Forest Research (BIFoR) where researchers are hoping to determine the long-term effects of elevated carbon dioxide levels on ancient woodland over many years. For such a detailed project they have to use a wide range of sampling methods. Alongside some very sophisticated machinery you can also see more familiar equipment; at the back of the picture you can see a large green net that is actually leaf-fall trap, and there are pitfall traps in the sampling areas too. The video below shows many of these sampling methods in action at BIFoR.

Do researchers use the same sampling techniques?

An image of a man wearing an orange safety hat and yellow jacket
How do we sample species distribution?
An image of the FACE construction in the forest

Why is a control important?

The findings from the BIFoR experiment are hoped to have a direct impact on climate change policy, so it is vital that the results are reliable and that the conclusions that are drawn are accurate. In an experiment like the Free Air Carbon dioxide Enrichment (FACE) programme, where scientists intentionally change a variable (in this case carbon dioxide concentration), we have to know that it was that variable causing any observed change - not another unexpected part of the experimental set up.

As mentioned in the video, although there are 6 FACE arrays at the site only 3 of them are raising carbon dioxide concentrations within their experimental sampling areas. The other 3 arrays have been assembled identically to the first, but they pump normal air out into their sampling areas. This allows researchers to be more confident that the results that they get from the experiment are due to elevated carbon dioxide gas levels.

In most A Level species diversity practical assessments, it is more likely that your variable will not be controlled by humans, but based on what is available in the field. If you are observing the difference between species distribution in shaded and sun-lit areas, or on different inclines, then a control must be part of this experiment too, so think carefully about what your variable is and what is acting as a control.

Be aware of other variables that could influence your experiment. At BIFoR, researchers air-lifted the towers in by helicopter to ensure that the woodland was not affected by heavy building machinery, they took measurements in the forest for an entire year before even beginning the construction of the towers, and they are running the experiment for 10 years - all to ensure they have controlled for as many variables as possible. What variables can affect your experiment? Might seasonality or even time of day affect their distribution? Might human activity have an effect on your measurements? The more variables you can identify and control for, the better your experiment will be.

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What do your measurements mean? 

Remember that data collection is only part of the experimental process. Data has to be processed and presented in a way that is coherent and logical to allow you to come to a conclusion that is backed up by sufficient evidence.

There are different measures that can reveal different characteristics of your habitat. The species richness is a count of the number of different species in a habitat, but it does not tell you anything about the representations of species to one another - their abundances. A measure like Simpson's diversity index can be useful to show how the abundant organisms are in an ecosystem, and builds a better picture of the resilience of that ecosystem to damage or disturbance.

Ecological findings in situ can help conservationists to protect endangered species, or to build a case for an environment to qualify for special protection. This can then form part of local, national or even international agreements to protect against the effects of human population growth, agriculture and climate change. When trying to establish agreements like these, the evidence they are based on needs to be as reliable and robust as possible - which is why controlling for variables and establishing a suitable control is so important.