The art and science of field work
Health and safety in carrying out field work is key. While hazards in the lab might extend to toxic chemicals and disposing of GM microorganisms, hazards in the field can be even more diverse. Terrain, weather conditions and isolation can all play into this, depending on location. It only takes a brief look at wild animal documentaries to see how venturing out into nature can pose many hazards.
On one hand, it is important to think about the safety of those who are carrying out the work, while on the other hand the integrity and health of the habitat being investigated must also be kept in mind. Human intervention and equipment can be disruptive to some species. This is doubly critical when dealing with legally protected areas that may house rare or vulnerable species.
The method of investigating species is also dependent on how that species lives. For example, point counting might work for trees but not insects. Other methods include transects that asses the length of a given section of land in set increments (e.g. every 10 metres), and even remote detection via signals given by tags.
Sampling of organisms must be like those annoying, attention-seeking Snapchat friends. It must be random. Random sampling can be carried out using quadrats. If you’re wondering what they are, look no further – they’re squares.
How would you make sure that your sampling is random? In a field, you could lay two long tapes perpendicularly to define the limits of the area where the samples will be taken from.
As you can see above, a tape is laid on one side of the sampling area. As you can’t see above, another tape is laid from one end of the first tape, across on the adjacent side of the sampling area (like a giant L). Then two random numbers are generated using a random numbers table. These numbers are used to determine the coordinates of the first quadrat placed on the field, by matching them on the two tapes. And voila! You have yourself a system for random sampling using quadrats.
Transects are tapes (like above) placed across an area which has some form of gradient caused by abiotic factors which directly determines the distribution and abundance of the organisms present. For example, a beach is not suited for random sampling because there are clear zones ranging from the low population zone near the sea, to the more densely inhabited areas further up the shore. In this case the best way of obtaining useful data is by systematic sampling.
After placing the tape across the shore, place quadrats at set intervals such as every 5 metres, then take your data down.
Monitoring indicator species is central to classifying vegetation as well as assessing the health of a community. Indicator species can communicate through their absence, presence or abundance whether certain environmental factors are playing certain roles in the habitat at a given time. For example, pollutants can impact indicator species, so how the species is doing can be used to determine what the level of pollutant is currently in their environment.
Eutrophication is a good example of a factor that could alter vegetation type, and give rise to indicator species. This information could be used to assess unknown habitats. Vegetation types, such as different types of woodland, can also be established through indicator species e.g. Carex rostrata (bottle sedge) woodland.
Mobile species such as shrimps can’t be counted by the quadrat method. Instead, they are investigated using the mark-release-recapture method. This is something I personally did on my field trip for A level:
1. Capture shrimps using nets and count them.
2. Mark them by nipping half their tail diagonally (not proud :D)
3. Repeat, ensuring to account for the marked shrimps.
The more marked individuals you get, the smaller the total population is likely to be.
In order to calculate this, we can call the number of initially captured individuals M, and the number of those captured the second time C. The recaptured ones (with the mark) in the second sample C can be termed R.
This gives the equation N = (MC) / R where N is the total number of individuals in the population.
For example, if we caught 45 shrimps, marked and released them; then caught another 45 of which 31 were marked, then the total population would be:
N = (MC) / R
N = (45 x 45) / 31
N = 65.32 [shrimps are whole numbers so round down] N = 65 shrimps
The total population obtained this way is an estimate that depends on an equal probability for all individuals to be recaptured, and no migration into and out of the population to occur. Juvenile individuals might not be captured, ill individuals might not be captured, or the population might be connected to others, skewing the data from the mark-release-recapture method.
Methods of marking different species include banding, tagging, surgical implantation, painting, hair clipping, etc. Any marking method must minimise impact on the species, both during the marking process but also during subsequent observation through the mark.
In the case of elusive species that can’t be handled directly, camera traps are used to monitor them. Another method is scat sampling which involves taking a sample of faeces left behind on the ground. This is used for cheetahs. Something to bear in mind is to not take all the scat available, as it is used by the animals as a territory mark.
Trained dogs can be used to assists with scat finding. The sample can be analysed genetically to establish how many different individuals are present in the area.
Depending on the size and type of organism, data can be collected in the form of numbers by counting the present organisms in each quadrat (frequency), or working out the percentage of area within a quadrat that a species occupies (percentage cover), then scale it up to the whole area investigated by multiplying.
For percentage area, you’d count the smaller squares within the quadrat that your target species covers, and convert that number to a percentage (there are 100 smaller squares in the quadrat). So for example, our green plant would cover approximately 25 squares, giving us a 25% coverage. Both these methods are quantitative, giving us 11 plants per quadrat and 25% quadrat coverage, but there is another less quantitative, more descriptive method called ACFOR.
ACFOR is a somewhat subjective system for describing the abundance of species within a quadrat. It follows:
A = abundant
C = common
F = frequent
O = occasional
R = rare
Based on this, we might describe the above scenario for the green plants as perhaps, frequent. Are they common instead? Maybe just occasional? Hard to tell, and dependent on what the overall area looks like, and what other species there are.
This is why it is important to select the appropriate ecological technique for the ecosystem and organism to be studied. For example, if our area contains many different species with scattered distributions, we are likely to get many different numbers for each, which might take a very long time, and might not be that necessary for our analysis. Perhaps we are only intending to compare whether two species are equally abundant or not.
In that case, we wouldn’t be spending time counting small squares to get a percentage cover, but rather using the ACFOR scale. Another scenario is looking at very small species that we cannot count individuals for! Think grass. We would use a percentage cover or ACFOR in this case.
In another case, we might have a scarce area with very few individuals for each whole quadrat, nevermind little square within. In this case we might prefer to simply count them rather than try ACFOR which wouldn’t work because it’s too generic and we might end up with all “R”s, or percentage cover which would also mostly be totally empty and give 0% for no individuals present, or 10% if one quite large individual is present that covers many squares. In this case, counting would give the most useful data as we would get a few whole numbers, e.g. 1 for the first quadrat, 0 for the next, 2, then 5, then 1.
Principles of taxonomy and model organisms
Species and their classification
Taxonomy refers to the classification of living things by giving unique names to each species, and creating a hierarchy based on evolutionary descent. This is a challenging task, as most species that have ever lived on this planet are now extinct, and many more alive today have yet to be discovered and classified.
In order to achieve the above, though, we need a definition for both species and hierarchy. In the old days, a species was known as a collection of individuals similar enough in resemblance to be put in the same box. This was purely based on physical features. Today we know that similar physical characteristics on their own aren’t enough to define a species.
A species is defined in terms of observable physical features as well as the ability to produce fertile offspring.
This is Hercules, the liger. Hercules has a lion father and a tiger mother. Does that mean tigers and lions are really one species? This is one example of the issues surrounding both the definition of species, and taxonomy generally.
What is a hierarchy? A hierarchy, put simply, is a system of classification comprised of small groups contained within larger groups contained within larger groups, and so forth, where there is no overlap.
The above diagram is a phylogenetic tree. It is a representation of various species in terms of their genetic relatedness. Each “crossroads” is a different ancestor. From this diagram it is easy to see that humans are more closely related to whales than to birds, or indeed any other species represented.
The species with a red circle beneath are extinct. If a phylogenetic tree was made with all species that have ever lived up to today, the vast majority would be extinct.
Aside from simple observable features and their similarity, advances in immunology and genome sequencing can add to the information required to create, maintain and update the tree of life according to new findings. Different organisms’ genes, proteins and physiologies can be compared to see how closely related they are.
The names above are used for convenience, yet the scientifically correct way of classifying organisms is by giving them a two-word (binomial) name. These names are in Latin or Greek.
Let’s take Homo sapiens for example (us!):
1. It’s written in italics as all species names should be, by convention.
2. It’s made up of two words: Homo and sapiens.
3. Homo denotes the genus to which the species belongs to. A genus is the group higher than species. For example, Homo erectus and Homo neanderthalensis are part of the same genus as Homo sapiens (both now extinct). That genus is called Homo… getting the hang of it?
4. Sapiens denotes the species itself, and is the smallest group in the hierarchy.
What does the rest of the hierarchy look like?
Domain, Kingdom, Phylum, Class, Order, Family, Genus, Species (fearing you can’t possibly remember this sequence?)
Dazzling, Kinky, Policemen, Can, Often, Find, Gay, Sex. You’re more than welcome.
Determining evolutionary relationships between species
In the era of molecular biology, we no longer have to rely on superficial visual cues only in order to classify species. We can look at and compare their DNA, proteins, etc. A common method of visualising these differences is gel electrophoresis which involves loading small volumes of samples on a gel and running a current across it in order to separate the samples by size.
Since the gel has a microscopic matrix inside that provides resistance against sample movement through it, the larger molecules move more slowly while the smaller fragments can move more quickly.
The positive charge is at the bottom of the tank, while the samples are loaded at the top. This way, they will move downwards towards the bottom of the gel because they have a negative charge as molecules. The current is run across the gel for around 30-60 minutes (ensuring the samples don’t run too long and hence run off the gel into the buffer solution! if that happens they are lost) after which the sample’s progression on the gel can be visualised by using a stain solution or pre-existing coloured label visible under UV light.
The protein or DNA samples for example can come from the different species’ muscle or some other tissue source. DNA samples can be replicated in the lab using specific primers (in PCR) to make certain genes or sections of DNA that are to be compared and looked at on a gel. Alternatively, all present proteins in a sample can be investigated by running the whole sample on a gel and comparing the differences.
The bands on the gel might look something like this. Based on the height on the gel of the different bands (which represent different proteins in the sample), we can see that all species have the band at the top. This is a protein of the same size that they all share.
The second largest protein (the second highest band on the gel) belongs to Species Y and is unique to it, not being shared by the other species. Same for the third one down of Species Z. Looking at all the bands for each species, we can see that Species A and Species Z share the most bands in common (3), so we assume from this data that based on their proteins, Species A and Species Z are the most closely related compared to any other species combination here (A, X, Y, Z).
With advancing technology, scientists no longer have to rely on capturing animals or gathering data manually in the field. Bioinformatics enables the analysis of a whole genome from a computer. Once the initial DNA sequencing has taken place, a lot of research can be conducted just from that data. For example, the DNA, mRNA or amino acid sequence between two individuals or species can be compared.
From this short sequence of amino acids in the haemoglobin of these different species we can infer several things. Let’s do humans and chimps first! How many differences are there? Lys, Glu, His, Iso and… Lys, Glu, His, Iso. Right. Absolutely no difference. Humans and gorillas have one difference, zebras and horses have one difference and zebras and humans have 3 differences!
We can infer a lot of different information from this table, and it’s just a very small sequence in just one protein looking at just five different species. The potential of investigating diversity with molecular biology tools is astounding.
DNA can be studied similarly, and a lot of creativity can be employed to come up with ways to twist and turn heaps of genetic data in such a way that interesting information can be pulled out. In this example, it’s a fairly straightforward, run of the mill comparison between the DNA sequence itself of a mouse gene versus a fly gene.
We can see that the sequence itself is 76.66% identical, while the protein product resulting from the exons only, is actually identical in its entirety at 100% between the two sequences (highlighted in green).
Three domains or five kingdoms?
An example of the role of the scientific community in validating evidence is the classification of life into 3 domains versus 5 kingdoms. Archaea, Bacteria and Eukarya or perhaps Monera, Protista, Plantae, Fungi and Animalia?
Domains are higher up than kingdoms, so refer to the very earliest differences between living things. Originally, the kingdoms were established based on superficial analysis of different organisms, and an even earlier classification called Linnean classification simply split everything into animals and plants, based on whether they moved!
Monera (or Prokaryotae) kingdom was split into bacteria and archaea because very fundamental differences between these organisms were found as a result of better comparisons such as molecular biology techniques such as those outlined above. The remaining 4 kingdoms could then be grouped under Eukarya.
The response of scientists to this evidence follows that older evidence was treated differently in light of newer, more insightful evidence. Evidence can always build up, break down or change in other ways to change our understanding of life. At first, archaea and bacteria looked similar, so they were treated as closely related. As their inner workings were investigated with the use of more sophisticated tools, it became apparent that their characteristics beyond appearance were very different.
Outline of the plant and animal kingdoms
The plant kingdom Plantae comprises of mosses, liverworts, ferns, conifers and flowering plants. Despite their popularity, flowers are actually very new relative to other plants.
Some plants do not make seeds, such as ferns, while other do e.g. flowering plants. The structure of a plant’s stems, roots and leaves is associated with its genus and species.
Knowledge of taxonomy is useful in being able to make predictions in unknown species by using information on a more common, often model organism. In the plant kingdom, Arabidopsis thaliana is a model organism subject to a lot of research.
It is easy to cultivate and has a very small genome for a plant, as well as being diploid. It has so far been used in a lot of genetics and evolution research, and has been key to working out how flowers develop (the ABC flower development model).
In the animal kingdom, classification goes into phyla such as the Chordata i.e. vertebrates and sea squirts, Arthropoda (joint-legged invertebrates), Nematoda (round worms), Platyhelminthes (flatworms) and Mollusca, to name just some.
Arthropods like insects and arachnids are differentiated through their segmented bodies with paired legs, 6 in the case of insects. Nematodes include many different species of parasitic worms. Flatworms, part of the Platyhelminthes phylum have bilateral body symmetry with internal organs, but no actual body cavity. Molluscs include snails and other shelled species.
Model organisms from multiple phyla have been used to investigate biology, including worms, flies, mice and rats.
From the kingdom Monera, a ubiquitous model organism is E. coli. A bacterium, it is commonly used in molecular biology. All these model organisms across kingdoms have been central to the progress of current biological knowledge.
Ethology is the study of animal behaviour, as previously seen with welfare in domesticated animals. An ethogram is a reference of all behaviours seen in a species in the wild.
In studying animal behaviour, time budgets can be put together which show the time spent by the animal doing each activity. They can be characterised according to latency, frequency and duration. For example, a dog might have a 1 minute latency of “toying” 3 times (frequency) for 4 minutes (duration).
Latency refers to the delay between exposure to a stimulus and reaction.
Actions in an ethogram must be mutually exclusive, objective and lacking in explanation. For example, the dog may be “biting”, but not “biting angrily”. Tendency to anthropomorphise animal behaviour must also be prevented. This refers to the human bias of trying to explain behaviour from a human point of view, using human emotions, etc.