Sampling and Recording Data

Wildlife recording and sampling

David Beeson, June 2020

You are interested in the natural world. You keep your eyes open or go out actively looking for organisms. So, what do we do with what we see? How useful is that data?

Here are my thoughts on wildlife data and an encouragement for us all to do more with our skills and knowledge.

Level 1. We all go for a walk and spot some organism and do nothing with that information  – this is useless to science, but we all do it because we enjoy the environment and the stimulation of what we do or might see.

Level 2. We spot something and tell a friend – virtually useless unless the data is then passed on.

I’m as guilty as anyone!

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Shall I take the results here? Yes, there are lots of them! NO!!!!!

Level 3. We see something and pass it on via a phone app or similar. A bit like stamp or train number collecting!

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I must only collect one stamp … numbers not important!

However, at least it allows science to see the distribution of a species. It gives no indication of numbers or the environment, so, the information is rather lacking. However, this is better than nothing.

I do this level when recording mammal sightings in the hope The Mammal Society can do something with my dot on a map. I’m not fully convinced.

This information can be greatly improved if the task is repeat at regular intervals.

I used this when recording otter spraints on a present / absent basis along the River Avon and Itchen at near regular intervals. Gives an indication of population size.

But, is the RSPB Big Garden Bird Watch of any value? Do you think folks count one bird twenty times? I do. Data is only valuable when it’s accurate.

A non-accurate way of recording data. Plenty of subjective decisions and criteria will vary person to person. Cannot be repeat by another person.

Level 4. The recorder gives some indication of number – absent, rare, occasional, frequent and abundant or a similar system.

This can be repeated at regular intervals, e.g. recording damselfly numbers at a site. But, the sampler can select the data collection site, so, a bit dodgy! What about elsewhere? Did they just select the best location for them?

I used this level with new students sampling a freshwater habitat or plants on a site because it is quick and simple. Best if repeated and using a quadrat to improve data.

A transect is basically a line along which you record data. Results can be taken at regular or at random locations.

Level 5. The recorder follows a transect – a line of data collection of known length and location.

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Longworth trap. The big snag is the worry about catching shrews. Needs regular checking of traps to release shrews before they are stressed or die. Caught animals often humanely marked and released, then hopefully recaptured – allows population to be estimated.

I used this belt transect system when seeking harvest mouse nests and so assessing the animal’s density and when setting out Longworth (live mammal) traps on Brownsea Island nature reserve (Vole sampling) and the Arne RSPB Reserve (Small mammal sampling). The use of a transect takes away much recorder bias.

Useful technique when recording physical conditions: e.g. wind levels between open and closed canopies.

Some butterfly recorders use this recording level.

% cover of plants within a quadrat is a good way to assess populations.

This is now real quantitative data. Real numbers, rather than present / absent which is qualitative. Proper research information is being generated.

Level 6. For plants you now employ a quadrat along a transect or at random (Random numbers generate the sampling sites.) locations over the whole site. The randomness stops the recorder moving to seek the species he / she wishes to observe. Far more scientific than just wandering a location.

Level 7. You sub-divide the site into different zones according to their environmental factors – wetter, scrub, near woodland etc. Random quadrats used. Called stratified random sampling. Great data as records not subject to recorder’s whims and statistical analysis worth the effort.

Used by my students to assess the impact of badgers on vegetation around a sett.

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Point frame – you only record the plants touched by the pointer. Possibly the most accurate sampling technique for plants. With random locations it avoids sampling errors.

Level 8. As 7 but using a point-frame quadrat (for plants mainly) that avoids all errors with selecting specimens or working out % cover.

My students employed this when assessing trampling on flora. In this situation random numbers pinpointed sampling sites which were line transects across the pathway.

Certainly, as one moves down the list the quality of the data improves, while the effort increases. A PhD student will probably be at Level 6 or 7, the average person at Level 2 or 3. You, now, will be at level 7!

Different techniques need to be employed according to the target habitat or species. The capture-mark-release–recapture technique is great for mammals but less useful for plants! There are plenty of sampling techniques in the textbooks.

By sharing data with conservation bodies the material can be aggregated and is potentially useful.

Sorry, that was a bit boring! But, hopefully worth saying.

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