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Resource PlusCambridge International AS & A Level Marine Science 9693
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Investigating the effect of particle size on the permeability of substrates video transcript
Shorelines often have sediments deposited. The size of particles on these shorelines can vary considerably from one shore to another, as shown here, or within one shoreline
Prepare the bottle for the experiment by placing a piece of cloth over the top where the bottle cap was. secure this in place using a rubber band tightly wrapped around the neck of the bottle. Mark a line half way up the bottle to indicate a level to fill the sediment to. Place the bottle into a clamp stand.
Add 10-15 mm gravel to the bottle up to the fill line, ensuring the top is fairly level.
Use a measuring cylinder to measure 100 cm3 of water.
Place the other measuring cylinder beneath the bottle ready to catch the water.
Add the water to the bottle and start timing how long it takes to pass through the 10-15 mm gravel before the flow noticeably slows.
Record the volume of water collected in this time.
Repeat the experiment with the second largest diameter gravel. Record the volume of water collected after the largest gravel.
Repeat the experiment again with the other types of sediment, each time measuring the volume of water that passes through after the largest gravel.
The rate at which water drains from sediments can have a significant impact on the conditions on or in the shore, and the ability of a range of organisms to survive there during low tide.
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Investigating the effect of pH on empty mollusc shells video transcript
It is quite well known that sudden changes in sea temperature can cause corals to bleach. What are the effects of changes in pH on marine life? In this investigation we will change the pH of a solution and investigate the effect this has on the mass of empty mollusc shells.
To obtain precise results you must use a balance that measures to at least 0.1 g increments.
Using an oven is not essential but this will speed up drying the empty shells.
Place the empty mollusc shells into an oven at least 1 day before the experiment to ensure they are completely dry.
Label the five beakers with the pH 0, 1, 3, 5 and 7.
Use a measuring cylinder to measure 50 cm3 of 1.0 M hydrochloric acid and carefully pour this into the beaker labelled “pH = 0”.
Record the total mass of three of the mollusc shells for pH = 0, and place these shells into the pH = 0 beaker.
Record the total mass of three of the mollusc shells in your results table for pH = 0.
Leave the shells in these solutions for 24 hours.
After 24 hours remove each set of shells, rinse each shell carefully with water and place into an oven to dry, taking care to organise the shells in a way that you can identify which solution each group of shells have been in.
Leave the shells to dry for at least 24 hours.
When the shells have been left to dry, remove them from the oven and re-weigh each group of 3 shells, recording the mass of each set carefully in your results table.
Calculate the change in mass of each group of shells.
What do your results tell you about the potential impact of acidification of sea water on the shells of molluscs?
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Dissection of a fish head video transcript
In this experiment we shall look at how the structure of the fish head in bony fish aids gas exchange in the fish’s ventilation mechanism. We’ll do this by dissecting a fish head to see the internal structures.
But first, let’s look at how the ventilation mechanism in a bony fish works.
The main external structures involved with ventilation are the mouth, and the operculum, which is the bony flap that covers the gills.
The process of gas exchange in bony fish using pumped ventilation happens like this.
The fish’s mouth opens and the operculum is closed.
Inside the mouth is the buccal cavity. The buccal cavity floor is lowered as the fish opens its mouth, and this increases the volume and decreases the pressure of the cavity compared to outside.
Because the pressure decreases inside the cavity, this causes water to rush into the mouth down a pressure gradient.
The opercular cavity behind the operculum expands, and the buccal cavity floor is raised. The pressure inside the buccal cavity is now higher than in the opercular cavity, so water moves from the buccal cavity over the gills and into the opercular cavity.
The fish now closes its mouth and the operculum opens. At the same time the sides of the opercular cavity move inwards, increasing the pressure and water rushes out of the fish through the operculum
The operculum covers the gills below. To get better access to the gills, we first remove the operculum where it attaches to the fish’s head.
Now that the operculum has been removed we can see the complete structure of the gills.
There are 4 gill arches on each side of the fishes head and through each of these blood vessells flow to supply blood to and from the gills.
The arches in turn support the gill filaments, on which are the gill lamellae, whch are very small so cannot be seen here. These structures help to increase the surface area of the gills to its maximum to promote more efficient gas exchange.
To see the structure of the gills more clearly, we next remove them from the opercular cavity by cutting through the bone attaching the gills to the inside of the head.
When the gills are in air you can see that the gill filaments clump together, reducing surface area. To see the structure of the gills more clearly as they would be when the fish is in water, you can place the gills in a beaker of water.
When the gills are placed in water we can see that the filaments fan out, producing the maximum surface area for gas exchange
The gill lamellae are very small, so it is best to view them under a microscope.
To do this, trim a small piece off one of the gill filaments with scalpel and mount it on a slide.
Looking at the filament under a microscope shows the lamellae as feather-like projections from the gill filament. Capillaries in each lamellae carry blood close to the surface where gas exchange occurs. The lamellae help to further increase the total surface area available for gas exchange in the fish’s gills.
So we can see from our investigation how the structures of the fish head have been finely developed to promote maximum efficiency in gas exchange.
Using pumped ventilation, bony fish, even when moving slowly, can move large amounts of oxygen rich water over their gills, where the surface area produced by the filaments and lamellae ensure the maximum extraction of oxygen from the water and into the fish’s blood supply. -
Salinity video transcript
Salinity is tied to many processes that occur in the ocean.
For example, density-driven currents are affected by changes in salinity and temperature, called thermohaline circulation.
Warmer, less dense and therefore less saline water on the surface of the ocean at the equators is transported to the polar regions, where it cools, gains in salinity and returns to the equator in cold bottom currents, so playing a role in transporting heat from the tropics to other parts of the ocean
The melting of glaciers and icebergs because of climate change adds more freshwater to the ocean, affecting salinity, which could disturb the flow of the currents, and therefore the balance of temperature across the planet.
Salinity is the concentration of dissolved salts in sea water, and the unit of measurement is parts per thousand, or PPT.
On average the ocean has a salinity of 35ppt, though measurements can vary between 32ppt and 37ppt, and in some polar region salinity may be less than 30ppt as the cold salty water sinks leaving less saline water and ice behind.
In this experiment therefore, we are going to consider how salinity affects the freezing point of water.
Start by making up a concentration of salt water.
For this experiment make a stock solution of 40ppt salt water from which further dilutions will be made.
Begin by adding about 400 cm3 of distilled water to a 500 cm3 measuring cylinder.
Next weigh 20.0g salt out on an electronic balance, accurate to at least 1 decimal place.
Pour the salt into the measuring cylinder of distilled water and mix thoroughly. Top up the volume of solution to 500 cm3 exactly then mix again to produce the stock solution. This can then be poured into a large beaker or other container.
Label the beaker as ‘Saline solution 40ppt’.
From this stock solution of saline water make up 4 dilutions to test the effect of salinity on the freezing point of water.
The dilutions are at 100 percent, 75 percent, 50 percent and 25 percent of the stock solution. Additionally, there will be a solution of pure distilled water.
These dilutions correspond to 40ppt, 30ppt, 20ppt, 10ppt and zero ppt solutions.
To make up the 40ppt solution, pour 100cm3 of the stock solution into a measuring cylinder, and then add this to a plastic cup and label it ‘40ppt’
Next make up the 30ppt solution. As 30ppt is a 75% dilution of the stock solution, pour 75cm3 of the stock solution into a measuring cylinder, then top up to 100cm3 with distilled water.
Pour the dilution into a plastic cup, mix thoroughly, and label it ‘30ppt’.
Wash the glass rod used to mix the solution with distilled water.
Make up the remaining solutions in a similar manner, labelling each plastic cup appropriately.
Finally, measure 100cm3 of distilled water and pour it into a plastic cup and label it ‘0 ppt’.
Place the cups on a tray ready to be put into the freezer.
Next cut some card to cover the top of each cup, and pierce a hole through the middle large enough to push through a temperature probe.
Push the temperature probes through the card and position them so that they sit in the middle of the solution without touching the sides or the bottom of the cup.
The hole should be a tight fit on the probe wire so that it can be positioned accurately within the cup.
Connect each temperature probe to the data logger.
Start the data logger and place the tray of cups into the freezer.
Allow the experiment to run.
The data logger will show when each solution has frozen as the cooling curve will level off at or below 0oC.
Once the last solution has frozen, the data logging can be stopped and the now frozen solutions removed from the freezer.
The data logging software will produce a graph displaying the cooling curves for each solution, showing temperature against time.
In this experiment the graph shows that the distilled water froze quickest at approximately nought degrees Celsius, which is what we would expect of pure water.
The saline solutions froze at lower temperatures than the distilled water, with the 40ppt solution freezing at the lowest temperature.
This is normal because for every 5ppt increase in salinity we would expect to see that the freezing point decreases by about 0.28 degrees Celsius, so clearly the greater the salinity the lower the freezing point of water.
The 30ppt solution is the most similar to ocean water in polar regions, and the graph shows that saline water freezes at about -1.8 degrees Celsius which is similar to what we see in real life.
Investigations of this type can be used by scientists to model the effect of climate change on the icecaps and ocean currents.
An interesting application of salinity is used in colder climates during winter months, salt is added, with grit, to roads to reduce the freezing point of water, and this helps reduces the chance of ice forming on roads, making them safer to use. -
Sampling video transcript
Random sampling is useful to estimate the population of different species in a habitat that is generally similar across the habitat. By sampling random areas of the habitat we can estimate the population of each species without having to count all individuals in the entire habitat which would be very difficult to achieve.
To select random areas to sample we can create coordinates using the measuring tapes…
…use one of the long measuring tapes to mark out an ‘x-axis’ for our coordinates…
…and place the other measuring tapes to mark out a ‘y-axis’ for our coordinates.
Use two random numbers to identify the coordinates to sample…
…the first should be the ‘x-axis’ coordinate, the second the ‘y-axis’ coordinate.
Carefully place the quadrat in the position identified by the coordinates. Measure and record the different species inside the quadrat:
Species with clearly identifiable individuals can simply be counted, recording the total number of individuals in the quadrat.
Species such as grass that are difficult to identify individual organisms you can estimate the total coverage of the quadrat – this is much easier using quadrats divided into smaller squares, e.g. 5x 5 squares, as each small square can be estimated to the nearest quarter (e.g. 3 quarters) and these totalled to give a percentage out of 100.
Record all the different species in your results table for the quadrat.
Repeat this process at least 9 more times to collect at least 10 sets of data, each from randomly generated coordinates in the marked habitat.
Systematic sampling is useful to show changes in the population of different species in a habitat that may be due to changing conditions across the habitat, such as the time exposed to air and submerged in water by changing tides. By sampling areas of the habitat along a line (transect) e.g. from low to high tide levels, we can measure changes in the distribution of different species along the transect.
To measure changes in distribution of different species in the habitat we create a transect…
…use the long measuring tape to mark out a transect…
…decide what type of transect you have time to carry out:
For a continuous belt transect you record the abundance of each species in the quadrat and repeat these readings by moving the quadrat up the line without leaving any gaps between. (This method is best for very short transects and when you have lots of time to record your results).
For an interrupted belt transect you record the abundance along the transect using a quadrat but leave regular spaces between areas sampled with the quadrat – this collects a representative sample of results and can be used for longer distances where you want to indicate the abundance as well as where different species are present.
For a line transact you simply record every species touching the line along its whole length (best for very long transects and when you don’t have a lot of time to record your results).
Starting some time before low tide (ideally at least an hour), place a quadrat next to the transect line and record the abundance of each organism in the quadrat – either by counting the number of individuals, or estimating the percentage cover. Starting before low tide gives you time to get used to recording your results as the tide goes out.
For an interrupted belt transect move the quadrat along the line leaving a gap between where it was previously.
Record the abundance of each species in the quadrat in the second position.
Repeat this process of moving the quadrat along the transect and recording the abundance until low tide, then return to above the point where you started on the transect and continue up the shore until you reach the splash zone. You should try to record results from about 10 quadrats along the transect line.
By recording information about different species and repeating these measurements over several years it is possible to monitor changes in populations …
… such as to monitor for new invasive species that may move into a habitat, or to monitor the spread or increase in invasive species populations to ensure these are not becoming a problem. -
Designing tables video transcript
In the Cambridge International AS and A Level Marine Science syllabus, one of the practical requirements of assessment objective 3, requires that you should be able to design results tables to hold the data either from investigations you carry out, or from an investigation described in an examination question.
So let’s look in more detail about what you need to consider when designing a results table to record experimental data. Here we have a table illustrating collected data for three different species of barnacles at different distances from the low water tide line. This results table matches the practical requirements you’ve just seen for recording data and observations in tables.
Let’s look at the table in more detail.
We could have created three separate data tables for these results, but point 2.1 (a) in the practical requirements says that you should collect all data in a single table of results.
So what else is correct about this results table?
First, the cells in the table are large enough to comfortably fit all data and headings.
Second, the table does not require extra columns for averages because each species is listed separately.
And finally, the column headings are clear and descriptive, with the units, in this case metres, included in the headings and not in the data. Ok, let’s look at an example question:
A student investigated the effect of light intensity on the rate of photosynthesis for an aquatic plant.
An aquatic plant was placed into a boiling tube of water, this was placed into a beaker of water to maintain a constant temperature. An electric lamp was placed 10 cm from the beaker and switched on.
The plant was left for three minutes to adjust to the light intensity. The number of bubbles produced by the plant was recorded for one minute. This was repeated three times at the same distance.
The lamp was then moved a further 10 cm from the beaker and left for three minutes for the plant to adjust to the light intensity before recording the number of bubbles produced in one minute. This was repeated three times at 20 cm. This method was repeated at 30 cm, 40 cm and 50 cm.
That’s a lot to take in! But if you follow a few simple steps you’ll be able to easily identify the key information you will need to capture in the results table. The first piece of information we need to identify is the independent variable. This is the variable we are changing systematically in the experiment. We have control over the values for this variable and will normally fix these values before we start to collect data. Examples of independent variables often include water temperature, water salinity, depth or distance.
In this experiment we are changing the distance of the lamp from the beaker; so this is our independent variable.
Next, we need to identify the dependent variable. This is the variable we will measure in each trial. It is the measurement that depends on the independent variable we have changed. For example this might be a counted number, a length or a volume.
In this experiment we are measuring the number of bubbles produced in one minute; this is our dependent variable.
Now we need to consider the number of repeat measurements that will be taken, as each will require a separate column for results.
In the question we are told that the results for each distance were repeated 3 times, so we will need to include three columns to record the mean number of bubbles produced in one minute.
Then we must consider whether we need to make any calculations on the data. Because we have three repeat measurements, you would expect to record a mean average for each set of repeats. So that means we need an additional column in which to calculate the mean averages.
Finally, we need to record the units for both the independent variable and the dependent variable in the column headings for the results table. The independent variable mentioned in the question is the distance between the lamp and the beaker measured in centimetres. The dependent variable is simply a count of the number of bubbles in a minute, so it requires no units.
Once we have identified the data we plan to record, we can then design a table into which we can record this data. Use a pencil and ruler to create your table so you can easily make changes if required.
The first column will be for our independent variable: the distance of the lamp from the boiling tube, with the units as centimetres.
The next column is the number of bubbles produced in a minute, but we need 3 repeats and an additional column for a mean, so we must add 4 columns here to record this information. To make the table clearer, we can add an additional heading, grouping these columns together. As you can see, the first 3 columns are for the 3 repeats and the fourth is for a calculated mean.
Now we have the main structure of the table, the final step before we start collecting data is to determine the range of results we plan to collect by fixing the values for the independent variable.
The question states that the results should be recorded with the lamp at a distance of 10, 20, 30, 40 and 50 centimetres, so these should be added to the table as our independent variable in rows below each column heading.
Now our table is complete we are ready to collect data and complete the practical itself.
Ok, let’s look at a slightly different example question from a past exam paper:
A student investigated the effect of water temperature on the ventilation rate of tilapia. Three tilapia were placed into separate tanks of water. The number of times each fish opened its mouth within a period of thirty seconds was recorded. The water temperature was maintained at 10 degrees celcius using a thermostatically controlled water bath. The experiment was repeated at different temperatures.
Design a results table to accommodate all of the results from this investigation. In this experiment we are changing the water temperature; this is our independent variable, and we’re measuring the ventilation rate of tilapia; this is our dependent variable.
The question tells us that three tilapia are used, this means that we are repeating the experiment three times at each temperature, so we will need columns for each repeat and an extra column to record the mean ventilation rate of tilapia at each temperature.
The temperature is recorded in units of degrees Celsius, and the ventilation rate of tilapia is the number of mouth openings in thirty seconds.
However this is not a true rate, as rate is usually a complete unit. In this case the unit of time would be per minute, so we must also convert this value into mouth openings in one minute. This will of course require doubling the mean mouth openings in 30 seconds that is originally observed. As before, once we have identified the data we plan to record, we can design a table into which the results can be entered. Again, use a pencil and ruler to create your table so you can easily make changes if required.
The first column in the table will be for our independent variable: the water temperature, and the units are in degrees Celsius.
The next column, the dependent variable, is the ventilation rate of tilapia, but we need 3 repeats and an additional column for a mean, so we must add 4 columns here to record this information. To make the table clearer we can add an additional heading grouping these columns together. The first 3 columns are for the 3 repeats, the fourth is for a calculated mean. We must also add the units for the ventilation rate of mouth openings in 30 seconds, as this is what we will be recording.
Finally, to record the true ventilation rate we must convert the mean into mouth openings in one minute, so we must double the mean rate in 30 seconds. This gives us our final column with slightly different units. Now we have the main structure of the table, the final step before we start collecting data is to determine the range of results we plan to collect by fixing the values for the independent variable.
Ideally, we should plan to record results for at least five different values of our independent variable. The question states we are starting at 10 oC, so this is our first value in the table.
For living organisms we need to respect that very high temperatures will be harmful to them, so we must set a realistic maximum temperature – a maximum of 30 oC with 5 oC intervals would be ideal as this would not be too hot to cause the fish significant issues, and gives us 5 different sets of values.
Now our table is complete we are ready to collect data and complete the practical itself.
So we’ve have worked through some examples and seen how to design a table to record experimental data. Why not test out the skills you have learnt on some other examples. Good luck! -
Drawing graphs video transcript
In the 2022‐24 Marine Science syllabus there is more detail included on what types of graphs candidates are expected to be able to create, including histograms.
You need to be able to decide which type of graph is appropriate to draw based on the data you will use.
For all types of graph you should include appropriate headings (and units where data has units), choose an appropriate scale that utilizes at least half of the grid in both directions, plot clear points that are correct, and can be read accurately to within half a square of the value, to choose an appropriate line or lines on line graphs.
Where multiple sets of data are plotted these must be clearly identified using a key and/or label.
When the independent variable is continuous (i.e. measurements with ‘inbetween’ values) then the graph should be a line graph, as this allows us to extrapolate estimated readings for values in between those recorded, or possibly beyond the range of values recorded if appropriate. In this example the independent variable is the depth, but as this is a distance it would be possible to obtain values at smaller intervals. The values are plotted as points or crosses and either a best fit line drawn or ruled lines drawn between points.
When the independent variable is categoric (i.e. there is no direct link between values of the independent variable) then a bar chart should be used, in this case species is categoric as each species is distinct from each other each bar should be equal in width and separated by a space.
When the independent variable relates to grouped frequency data, (i.e. the independent variable is continuous but items are grouped together within narrow ranges), a histogram is required – this uses a continuous scale on the x‐axis and bars that do not have spaces between them. In this example the number of mass of salmon has been recorded, and the frequency of groups of salmon in ranges of masses have been shown in the histogram, e.g. 0‐0.5 kg, 0.5‐1.0 kg, etc
In this question a table of data is provided showing the number of coral colonies of different species at different depths.
The question asks us to plot the data at a depth of 4m. We therefore ignore the data at 2 m and 12 m.
Species is a categoric variable, there is not a linear relationship between the different species, so we must draw a bar chart of this data. ‘Species’ should be placed on the x‐axis, we will need to plot six bars.
The y‐axis will be the number of coral colonies. The range for these values is 0 to 22.
The first step is to set up the axes.
The x‐axis is the species. This has no units so the label ‘species’ is all we need to write here. We have 6 values and 6 ‘large’ squares (marked by slightly darker lines) to use, so we will place one species in each of these larger sets of squares. Each bar must have a space between them and the bars must be equal widths, so to make this easy to be consistent we can make each bar 8 small squares wide in the middle of each set of 10 small squares.
The y‐axis is the number of coral colonies. This also has no units so the label ‘number of coral colonies’ is all we need to write here. The range of values we need to plot for this axis is 0 to 22, we have a grid of 6 ‘large’ squares (60 small squares) and the plots must occupy at least half the grid. It is best to use scale going up in ‘1’, ‘2’, ‘5’ or ‘10’ to make plotting and checking simple. ‘1’s will only allow plots to ‘6’ so this is not suitable. ‘2’s would only allow plots of 0‐12 so this is also not suitable. ‘5’s will only allow plots of 0‐30 so this will fit out data and the plots would occupy over half the grid.
If we were to use ‘10’s here we would have a scale of 0‐60, although the data will fit on this scale it occupies less than half the grid so is inappropriate. For this data and grid using ‘5’s is the most appropriate scale, although we don’t need to continue the scale beyond 25.
When we plot the data we need to carefully check we are using the scale accurately. On the y‐axis every 10 small squares is an increase of 5, so each small square is an increase of 0.5 (a common mistake at this stage is to plot as though each square is a full ‘1’) so if you have made this mistake previously you could add small marks to show were each full value.
Finally we plot the bars by carefully plotting the value on the y‐axis, so for this data species A has a value of 4, this is two small squares below 5, so we draw a horizontal line at this height, remembering to leave a gap and then extend vertical lines to from the x‐axis to meet this.
Alternatively you might find it easier to draw the vertical line first then complete the bar. It doesn’t matter which way you choose, use the sequence you find easiest. Then plot the remaining bars, ensuring you remember to leave a gap between each bar.
In this question a table of data is provided showing the population density of a species at different depths.
“Both variables are continuous, so we must draw a line graph of this data. ‘Depth’ is the independent variable so should be placed on the x‐axis, while ‘population density’ is the dependent variable, so should be placed on the y‐axis. However, there is an alternative approach that can be used for depth here.
The y‐axis will be the number of coral colonies. The range for these values is 0 to 22.
The first step is to set up the axes.
The x‐axis is the depth, with units ‘m’. We have values of 2‐12 and 6 ‘large’ squares (marked by slightly darker lines) to use, so we can use intervals of ‘2’ to fill the axis.
The y‐axis is the number of population density, with the units number per meter squared. The range of values we need to plot for this axis is 1 to 5.2, we have a grid of 6 ‘large’ squares (60 small squares) and the plots must occupy at least half the grid. Once again it is best to use scale going up in ‘1’, ‘2’, ‘5’ or ‘10’ to make plotting and checking simple. ‘1’s will allow plots to ‘6’ which fits the data and the plots will occupy over half the grid.
When we plot the data we need to carefully check we are using the scale accurately. On the y‐axis every 10 small squares is an increase of 1, so each small square is an increase of 0.1.
Finally we plot the points by carefully plotting a cross where the values intersect, so the first value is depth 2 m, population density 3.8 per m2. An alternative way of plotting points is to mark a distinct dot surrounded by a small circle, but be careful not to make these dots bigger than half a square in diameter.
Plot the rest of the data, taking care to plot accurately
A line graph requires the points joining by a ruled lines or a line of best fit. In this case ruled lines are most appropriate – but make sure you start at the value at 2 m, we don’t know what the value is at 0 m so must not assume it to be zero. Then plot the remaining bars, ensuring you remember to leave a gap between each bar.
As this data relates to depth in the ocean, an alternative, possibly preferable method of plotting the data can be carried out by plotting the depth (independent variable) on the y‐axis with the zero depth at the top of the scale, and increasing depth going vertically downwards. The dependent variable (population density) is then plotted on the x axis. This approach is only appropriate for depths as this conceptually better matches the vertical change in depth in the ocean. Other than this change in orientation the choice of scale, plotting the points and drawing the lines is identical to the approach shown in the previous graph…
So we have seen how to draw graphs to present data to identify trends and patterns in a suitable format. Why don’t you now test your skills out on other examples. Good luck. -
Biological drawing video transcript
In the 2022-24 Marine Science syllabus there is an explicit requirement in Assessment Objective three, that you can draw biological drawings.
This does not mean you have to be a great artist, but the syllabus provides clear guidelines on how you should present your diagrams:
Use the space you have your finished diagram should occupy at least half of the space provided. Use single unbroken lines to show structures and outlines, and never use shading.
Always use a sharp pencil, ideally an HB or medium hard pencil you can use an eraser to rub out mistakes or rough lines.
When adding labels use a ruler to draw a straight line to end on the structure you are labelling, do not use arrow heads just a straight line, and make sure it touches the structure to clearly identify what you are labelling.
So, remembering this guidance, think about how you would go about drawing the following example…
In this example question, a photograph of a shark has been provided, and you are asked to draw the shark and label two features, the gill slits and the caudal fin.
The first stage is to lightly sketch an outline of the main shape or shapes to use the space appropriately. These initial lines will be rubbed out so make sure they are lightly drawn so the lines are easy to erase at the end.
Then add more detail on the fins and mouth, making sure these fins are approximately in the right proportions to the main shapes drawn, and at roughly the correct angles to each other. In this image the dorsal fin begins just after the widest part, halfway along the main shape drawn. Dividing the body further into quarters helps us to place other fins and features appropriately. The caudal fin is about as tall as the last quarter of the shark, shown here by double headed arrows.
Next, add in additional detail on the body such as the position of the eye and gill slits. Again we can use proportions to place these in the correct location. The gill slits are roughly one quarter of the way along the body, while the eyes and mouth are approximately one eighth of the way along, halfway between the gill slits and the snout.
Now draw over the outline of your diagram to make it more distinct, but leave lines that won’t be required in the final diagram alone as these will be erased.
Finally, rub out the lighter lines that are no longer required, to leave a clean, unbroken outline on your diagram
Finally, the question asks you to label the gill slits and caudal fin, so we use a ruler to draw a line from an empty space around the drawing where we can add the label, ending the line on the feature we want to label. We repeat this for any other labels required, in this case the caudal fin.
Now it is time for you to develop your drawing skills. This is an electron micrograph of a mitochondrion. Draw the main structures clearly visible in the image. You can compare your diagram with a completed version once you are done.
The first stage is to lightly sketch an outline of the main shape to use the space appropriately
Then draw the main internal shapes, making sure that these are approximately in the right proportions to the outer shape, and at roughly the correct angles to each other When there are numerous similar structures inside cells it is not essential to accurately repeat exactly the same number of structures in your drawing, as long as there are a similar amount and the diagram looks reasonably similar to the photo or image provided.
Next add any significant details. In this case there are several black granules that should be drawn. Again, it is not essential to show all of these, as long as the more significant granules are in the diagram. Check that you are happy with the relative size and proportions of all the features before you go any further.
Now carefully go over your outline with a firmer press on the pencil, to draw a single continuous line with no obvious gaps. You can take your pencil off the paper, but just make sure you don’t leave any gaps!
When you have gone over your diagram, carefully rub out your light pencil marks that are no longer required, to leave your finished diagram
This is a light micrograph of strands of algae. Draw two cells adjacent to each other in the image. There are several strands of cells in the photo, so you should choose cells that contain the clearest cell structures. This strand appears to contain the clearest images with at least two full cells. Try and draw two cells and compare your drawing with the structures shown on the example coming up.
Here is an example of a correctly drawn diagram. Your drawing might not look exactly the same, but key features examiners would be looking for in your diagram would include that you have drawn two cells next to each other with no gap. This shows that you have followed the original instructions in the question. Second, that the diagram takes up over half the space provided which demonstrates that you have made full use of the space available. Third, that the length of each cell is approximately double the width of each cell, which demonstrates that you presented the correct proportions. Fourth, that each cell has 5 vertical ‘pillars’ , or internal sections like the cells in the original micrograph. You should note that examiners will usually allow one more or less in each cell, so between four and six internal sections would be fine in your drawing. Finally, examiners would expect that most of the internal sections have at least one round structure shown. Providing this extra information on the diagram would gain a detail mark in the exam.
Okay, let’s practice your drawing skills on one last diagram
This is a photograph of part of an Atlantic salmon. Draw a large diagram of the head to include the operculum.
Here is an example of a correctly drawn diagram of the salmon head. Your drawing might not look exactly the same, but key features examiners would be looking for in your diagram would include that the diagram takes up over half the space provided so that the available drawing space has been used correctly. Second, that the length of the drawing from the operculum to the front of the mouth is longer than from the top of the fish above the operculum, to the bottom below the operculum, so the proportions are correct. Finally, that the diagram includes two lines showing the operculum, and the eye has also been drawn in, which gains a detail mark.
Biological drawing is a skill that you can develop throughout your course. Practice will help you improve, and by taking note of the tips given in this video you should be able to prepare well for your exams. Good luck! -
Planning investigations Part 1 video transcript
The Cambridge International AS and A Level Marine Science syllabus you are studying will require you to plan practical investigations and experiments. To do that you will need to be able to define a problem to investigate and choose appropriate techniques to undertake the experiment. This video will help you to understand what you need to think about, or plan, when you are starting out on a piece of practical work. The video will focus on how to:- Identify the independent and dependent variables in an investigation
- As well as identifying the key variables that need to be standardised so that they have a minimal effect on your experiment results
- And finally, the video will also show you how to go about making a prediction or hypothesis by sketching a graph of what you might expect to happen.
This video will also focus on how to choose appropriate techniques when planning your experiment or investigation. These include:
- How to change the value of the independent variable
- Selecting an appropriate range and intervals for both the independent and dependent variables
- Considering if any replicates are needed, and how many replicates to record
- Deciding how to measure the independent variable
- Planning to control other variables to ensure the investigation is valid
- And identifying risks and how to reduce these in your method
In this example question a hypothesis is stated which is that, ‘Light intensity increases the rate of photosynthesis in seagrass’, and you are asked to describe a laboratory experiment to safely test the hypothesis. You must therefore identify key information to record from the hypothesis before you start your experiment:
- The first thing you need to know is what’s the INDEPENDENT VARIABLE? The hypothesis states that light intensity increases the rate of photosynthesis, so light intensity is the independent variable.
- Second, you need to know what’s the DEPENDENT VARIABLE? Because the rate of photosynthesis will depend on the light intensity, the rate of photosynthesis is the dependent variable.
- And finally, you will need to know what are the key variables. This is because there are variables that affect the rate of photosynthesis which should be controlled or standardised to minimise their effect on your investigation. These might include the temperature of the water and the seagrass itself, for example the amount of seagrass, the size of seagrass plants and species or type of seagrass used. Additionally, other variables would include the supply of carbon dioxide in the water, as carbon dioxide is used up in photosynthesis, and other sources of light around the room or from outside the room where you plan to carry out the investigation.
Having now identified the key variables in your experiment, you now need to plan how to investigate the hypothesis.
First, let’s consider the Independent variable which you know is light intensity. How do you think you can change this variable so that you can collect suitable data?
Light intensity will decrease as a lamp moves further from the seagrass, so you could start by moving a lamp along a line, such as a tape measure, so that the light source can be brought closer or further away from the seagrass.
Next you need to think about the range you will use to alter the light intensity. You could move the lamp from very close to the seagrass, 10 cm would seem close enough, to perhaps 50 cm away.
Then you should try and get results for at least 5 separate values along the range, so for your range of 10 to 50 cm this would give 10 cm intervals meaning you would record data at 10, 20, 30, 40 and 50 cms.
And finally, you should try and get several results at each light intensity to allow you to calculate a mean. Three results at each distance would allow you to do this.
Now let’s consider the dependent variable which you know is the Rate of Photosynthesis. How do you think you can measure this? Well, rate is a measure of change over a period of time, so you will need to fix a period of time to collect results in for each light intensity.
You already know that photosynthesis produces oxygen and glucose, so these could be your measures of change. You can’t see how much glucose is produced, but oxygen is often produced as bubbles in aquatic plants, so you could measure the volume of oxygen produced every minute to record the rate of photosynthesis.
Now that you have a basic outline of your method, you need to ensure that other variables do not affect the results.
One important variable is the temperature of the water, which needs to remain constant and of course at a suitable temperature for the seagrass. The light bulb will produce heat which may heat up the water especially where it is placed close to the seagrass. You could reduce the impact of this by either placing the experiment in a large beaker of water to keep it cool, or by placing a Perspex screen between the lamp and the experiment to reduce heat transfer. Using cooler running LED lighting would also help of course.
Another variable you should consider is the seagrass. The Seagrass used should be the same species throughout the experiment, and you should use the same number and size of plants. You might actually choose to use the same plants throughout the experiment, just moving them to different distances to standardise this variable.
A third variable you will also need to consider is the supply of carbon dioxide. As you know, plants need carbon dioxide for photosynthesis and any reduction of carbon dioxide in the water will reduce the rate of photosynthesis in the seagrass. By adding a little sodium hydrogen carbonate to the water, you will make sure that carbon dioxide does not limit the rate of photosynthesis.
Finally, one other variable that you should think about is the background light; there may be other lights on in the room, or bright light coming in from outside through the windows. To reduce the impact of these light sources you should switch them off or close blinds so the main light source is the lamp you are moving.
Finally, the question also asks you to Safely describe a method, so you should include safety considerations for your chosen method
You will be using electrical equipment and water together in this investigation, so you will need to be careful not to have wet hands when handling electrical equipment
Additionally, the bulb in the lamp may get very hot, so you will need to be careful not to touch the bulb to avoid burns.
So this completes your plan to safely test the hypothesis that ‘Light intensity increases the rate of photosynthesis in seagrass’.
But what if you are asked to sketch a predicted graph for the hypothesis? You would need to show what you expect the trend for the results to look like. Let’s have a look at what you could draw.
The x-axis on your graph should represent the independent variable. Because you changed the light intensity by changing the distance from the lamp; this is the label for the x-axis.
The y-axis on your graph should represent the dependent variable. Because you measured the rate of photosynthesis by measuring the volume of oxygen produced per minute; this is the label for the y-axis.
Finally, you should sketch a line to show what you expect to happen. You might expect the rate of photosynthesis to decrease as the distance from the lamp increases, so this is your predicted sketch graph.
So next time you plan an experiment remember to do the following:
First, identify the independent variable, and decide how it’s measured and how to change it’s value.
Then choose an appropriate range and intervals or replicates for the independent variable.
Next identify the dependent variable, and decide how to measure it.
And finally, identify any key variables and decide how to control or standardise each one so that they don’t adversely affect your experiment results.
You might also have to consider safety issues, so always consider the risks and take appropriate precautions.
If you are asked to predict a result in the form of a graph, you need to show what you expect the trend for the results to look like
Place the independent and dependent variables on the appropriate axes and draw a sketch of your predicted trend of results on the graph.
Good luck!
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Planning investigations Part 2 video transcript
The Cambridge International AS and A Level Marine Science syllabus you are studying will require you to plan practical investigations and experiments. To do that you will need to be able to write a prediction or hypothesis for your experiment or investigation. This video will help you to understand what you need to think about when you are starting out on a piece of practical work. The video will focus on how to:
Write an appropriate hypothesis, by stating a null hypothesis to investigate, which allows you to plan to use a statistical test to test a null hypothesis.
The video will also cover; Identifying the independent variable, dependent variable and the key variables which will need to be managed.
This video will also focus on how to choose appropriate techniques when planning your experiment or investigation.
These include:- Deciding how to change the value of the independent variable
- Selecting an appropriate range and intervals for both the independent and dependent variables
- Considering if any replicates are needed, and how many replicates to record
- Deciding how to measure the independent variable
- Planning to control other variables to ensure the investigation is valid.
- Identify risks and how to reduce these in your method
- Considering how to treat living organisms ethically to reduce the risk of stress or harm.
- And deciding how the data could be used in a statistical analysis related to a null hypothesis.
In this example exam question, you are asked to include a null hypothesis.
But before you can do this, you must identify key information from the question to determine a hypothesis and, therefore, a null hypothesis. So, let’s consider what’s the key information you need to gather from the question.
The first step you should take, is to pull out the independent and dependent variables from the question.
The question states that Pacific Salmon may alter the rate of pumped ventilation in response to different temperatures, so the temperature of the water the salmon is in is the independent variable, as this will be the variable you will change in the investigation.
Next, the question states that Pacific Salmon may alter the rate of pumped ventilation in response to the different temperatures, so the ventilation rate of salmon is the dependent variable, as it should change as you alter the temperature.
Now that you have identified the independent and dependent variables, it should be possible to create a hypothesis, and from this a null hypothesis. Let’s consider the hypothesis first.
A hypothesis usually states that an independent variable, one that you can change, may have an impact on the dependent variable. You will measure this to see if this is true in your investigation of course, but for now your hypothesis would be something like ‘The temperature of water changes the ventilation rate of salmon’.
Now that you have developed the hypothesis, it’s possible to write a Null hypothesis using this statement. A Null hypothesis is a statement in which the two variables, independent and dependent, that you have identified do not have an effect on each other. So for this question you would write something like ‘The temperature of the water has no effect on the ventilation rate of salmon.’
Right, now that you have written the null hypothesis you should identify the key variables that need to be controlled or standardised to minimise their effect, just like you would do with any other experiment or investigation.
These might include;- Differences in the Salmon you will be using, such as their age, mass, size or species.
- The salinity of the water.
- The volume of water you use in the investigation.
- And the supply of oxygen in water.
Having identified the key variables, you now need to plan how to carry out the investigation. As you know, you’ll need to consider how you’ll manage both the independent and dependent variables in your experiment.
You’ve identified that the Independent variable is the Temperature of the water, and that that variable is the one you’ll change in your investigation. So, let’s consider how you’ll change and control the temperature of the water in the investigation, what range of temperatures you will use, and how you will record your data.
You could heat or cool the water using a heating or cooling device in an aquarium, and a thermostat will help to maintain the temperature at the target levels.
The question provides you with clues about the range of temperatures you should use in your experiment, as you will need to be careful not to stress or damage the salmon. So, a range of temperatures between 10 to 20 degrees centigrade will ensure that the water does not get too cold or too hot for the fish.
When thinking about the number of values at which to record data for the dependent variable, you should try and get results for at least 5 separate values. Looking at the range of 10 to 20 degrees centigrade, you could use 2 centigrade intervals, giving you 6 values of 10, 12, 14, 16, 18 and 20 centigrade.
Finally, you should try and get several results at each temperature to allow you to calculate a mean, and three values at each temperature would allow you to do that.
So, moving on to the dependent variable, this you know is the ventilation rate of salmon. For this variable, you just need to determine how you can measure this?
The question tells you that the ventilation rate can be measured in the Salmon by the rate at which the operculum opens and closes. So you could measure the dependent variable by recording the number of operculum openings over a suitable time period, such as a minute.
Now that you have a basic outline of your method, you need to ensure that the other key variables you have identified, don’t affect the results.
The first of these variables is the Salmon you will use in the investigation. Different species of salmon may respond differently to particular temperatures, so using the same species of salmon throughout the investigation will help to standardize that variable. Additionally, the age, mass or size of the salmon may also affect the results you get, so you should try and keep these constant.
The second variable you identified is the salinity of the water you use in the experiment. To ensure consistent results, the water used should have the same salinity throughout the investigation.
The third variable you identified is the volume of water used. Using tanks that are the same size and filled to the same level will ensure that the variable is standardised.
Finally, the last variable you identified is the supply of oxygen to the water in the tanks, as fish need oxygen for respiration and a shortage could affect the ventilation rate. To reduce the impact of limited oxygen supply you should add oxygen or air to the water in each tank, at the same rate in each test.
Finally, the question also asks you to describe a Safe and ethical method for your investigation, and you should include a plan to cover both of these points for your chosen method.
As already mentioned, the temperature range in the investigation will be between 10 and 20 degrees centigrade, to minimize stress on the salmon, since the question tells you that the salmon grow at temperatures down to 5 degrees centigrade, and that temperatures above 24 degrees centigrade can be fatal. You could potentially use lower temperatures down to 5 degrees centigrade, but you are best to avoid getting too close to 24 degrees centigrade in case the equipment allows the water to get slightly too warm.
Another ethical consideration would be that you should also allow the fish to rest between experiments if you are using the same fish and it looks like they are getting distressed. You should also ensure that the fish have enough space in their tank to move around, and you need to handle the fish with care at all times to minimise the risk of damaging or stressing the fish.
In terms of safety considerations, if you are using electrical equipment and water, you need to be very careful not to have wet hands when handling electrical equipment!
Now you have an outline of your method you need to provide more detail as the question asks for full details of the method. To make the method as clear and easy to follow as possible, it is a helpful tip to create numbered steps for each part of your method, as this makes it easier for you to refer back to earlier steps in your method without having to repeat your instructions each time. Steps 5, 6 and 7 are good examples of this in the method for the investigation shown here.
So in summary;- 1. Fill an aquarium with saltwater (35 ppt) and place a thermostatically controlled cooler / heater inside.
- 2. Allow the water to reach 10oC before carefully placing a salmon in the aquarium
- 3. Allow the salmon to acclimatise to the water temperature for 5 minutes
- 4. Count and record the number of times the operculum opens for 1 minute
- 5. Repeat step 4 two more times for another minute each time
- 6. Adjust the temperature to reach 12oC and repeat steps 3-5
- 7. Repeat step 6 for 14oC, 16oC, 18oC and 20oC
One last thing the question asks you to describe is how you would analyse your results, and to do this you should refer back to the null hypothesis you developed, ‘The temperature of the water has no effect on the ventilation rate of salmon’.
To show that there is in fact a correlation between the data recorded for the two variables, you should carry out a Spearman’s Rank analysis. This would show if there is a strong relationship, either positive or negative, between the two variables. You do not need to explain how to do that when answering the question, however, you do need to show that you are aware of the appropriate statistical method to analyse the results.
Now that has been done you have successfully completed the question by planning an ethical investigation that includes a clear statement of a null hypothesis, identifies the key variables, includes full details of a method, describes how you would analyse your results and ensures that the investigation is safe and ethical.
So next time you plan an experiment remember to do the following:
First, identify the independent variable, and decide how it’s measured and how to change it’s value. Then choose an appropriate range and intervals or replicates for the independent variable. Next identify the dependent variable, and decide how to measure it.
If you need to write a hypothesis, write this in the form of the independent variable having an impact or effect on the dependent variable, and if asked for a null hypothesis, adapt the hypothesis to state the independent variable has no effect on the dependent variable.”
Finally, identify any key variable variables, and decide how to control or standardise each one so that they don’t adversely affect your experiment results.
You might also have to consider safety or ethical issues, so always consider the risks to yourself or other organisms and take appropriate precautions.
If you are asked to predict a result in the form of a graph, you need to show what you expect the trend for the results to look like. Place the independent and dependent variables on the appropriate axes and draw a sketch of your predicted trend of results on the graph.
Good luck!
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Evaluating practical work video transcript
The Cambridge International AS and A Level Marine Science syllabus you are studying will require you to evaluate investigations. This video will focus on how you can:
• Consider an experimental procedure and suggest how it could be improved,
• Identify particular sources of error in a method for an investigation
• And identify anomalous results in an experiment or investigation, and suggest possible reasons to explain these anomalies.
Let’s take a look at an experiment that a student has performed. In this example the student has described a method for their investigation, and has included a diagram to show you how the experiment was set up.
They have investigated the effect of particle size on the permeability of sediments, and used five different grades of sediments.
The method the student used was as follows:
1. They marked two lines approximately half-way up and 1 cm from the top of the inside of a plastic funnel made from a cut-off plastic bottle, as shown in the diagram.
2. They plugged the bottom of the funnel with loose cotton-wool to prevent sediment escaping.
3. They half-filled the funnel with fine sand to the lower marked line.
4. Then held the funnel over a measuring cylinder to catch the water.
5. Using a second measuring cylinder, they measured 100 centimeters cubed of water and poured the water into the funnel over the sand. At this point they started timing.
6. They recorded the time it took for 20 centimeters cubed of water to drain out of the funnel into the measuring cylinder below.
7. Then repeated the experiment with two further samples of fine sand and water.
8. Finally, they repeated steps 3 to 7 with each of the other sediments in the table shown in the method.
You are now asked some questions about this method.
And the first is to ‘Identify a key variable to be controlled and suggest how this may be achieved.’ Can you identify a key variable in the method that can be standardised? Well, one of the key variables would be the water being used, as the viscosity, or runniness, of water changes with temperature. Warmer water is runnier than colder water and this could affect the results, so you would have to ensure that the water was at the same temperature each time you ran the experiment.
Another key variable that you could identify is the cotton wool plug. The cotton wool could be very compacted which would slow the flow of water through it compared to a loose cotton wool plug, so for each repeat of the experiment you would have to ensure that the same mass of cotton wool was used, and it was placed at exactly the same point in the neck of the funnel.
Next you are asked to ‘Identify possible sources of error in the method described and explain why these could cause errors.’ Well, one error would be that the ranges of sediment sizes overlap slightly and are on the whole very similar in size. Therefore, it might be difficult to obtain significantly differentiated results because water flow through the sediments might be very similar.
Another possible source of error is the water dripping into the measuring cylinder. As the water drips in the splashes could make reading the volume in the measuring cylinder tricky.
Finally, another source of error is that the method does not describe how the funnel is being held. If a person holds it, the funnel could be unsteady and possibly not held perfectly vertically, which could affect the results.
Now moving on to the final question, where you are expected to suggest improvements to the experiment. Here you are asked to ‘Suggest how the student could modify the experiment to obtain more reliable results.’ It makes sense here to refer to the possible sources of error you identified in the previous question. You have already highlighted that the ranges of sediment sizes overlap, so instead you could use a wider range of sediment sizes to avoid these overlaps, such as not using the medium or very coarse sands, and using an even smaller and even larger sediment to give a wider range of results.
Another possible improvement you could make would be to hold the funnel steady with a clamp stand. This would help to reduce the splashes as the water drips into the measuring cylinder, and by holding the measuring cylinder level it will be easier to read off accurate measurements.
A further improvement could also be to use a more precise measuring cylinder that would give more accurate results. This might help to better differentiate the results between the different sediments which you have already identified as overlapping in size.
Finally, you could use a better piece of equipment that contains fewer variables that could affect the results of the investigation. For example, in question 1 you identified that the cotton wool plug is a potential issue as it needs to be set up the same for each repeat of the experiment. As you have to replace the plug each time the experiment is run, this might mean that the new plug you create isn’t the same as the previous plug, which would affect the flow of water into the measuring cylinder. You could provide a description of a modification to the experiment equipment that would help overcome the issue with the cotton wool plug, such as suggesting removing the cotton wool plug and using a fine mesh to contain the sediment instead, as this would make the flow of water more consistent between each experiment.
Now let’s look at the final two questions for this investigation. The results the student obtained are in the table shown here, and you are now asked some questions about these results.
The first questions states that ‘One of the results in the table is anomalous. Identify the anomaly by circling the data on the results table.’ When you are looking for anomalous results, you need to look for results that don’t match the pattern of the other results you are given. Results that look either too high or too low compared to the other results around them. It is often a good idea to compare results across repeats of an experiment to see if any stand out as being significantly different than the other repeat results recorded. Looking at each row in the table of data the student has devised, the only row with a significantly different result is for Fine Sand in the first run of the investigation, so circling that result answers the question correctly.
Next you are asked to ‘Suggest a possible reason for this anomalous result, and how this could have been avoided.’ Well, there could be several different reasons, and in an exam question the marks available for the question will give you a clue as to how many you should provide in your answer. Let’s consider what reasons there could be for the anomalous result in this investigation, and think about how they could’ve been avoided.
First, it’s clear that the time for the anomalous result is much longer than those for the other two repeats on the investigation. Why might this have been? Well perhaps the person conducting the investigation was not watching the experiment carefully? This could be avoided by watching the experiment at all times.
Another possible explanation could be that the first run had more sediment in the funnel, so it simply took more time for the water to go through the extra depth of the sediment. The way you would avoid this would be to check the level of the sediment carefully each time you filled the funnel, making sure that the level of the sediment was the same each time you repeated the experiment.
Finally, you already know that there are a range of particle sizes in the fine sand, and another possibility is that the sediment in the first sample was much finer that the other two samples, which possibly contained more of the larger sand particles. To avoid this issue, you would need to thoroughly mix the fine sand at the start of the experiment before taking samples from it for each repeat.
So you’ve looked at an investigation and suggested ways in which there are limitations and potential sources of error in the method. You’ve also suggested ways in which the method could be improved and identified anomalous results in the investigation, and suggested how these could be avoided. These are all skills you can now use on your own experiments, or when reviewing other peoples’ experiments and the data they have collected.
When evaluating practical work and identifying the limitations in a method and potential sources of error remember;
To identify the key variables in an experiment, and consider what could influence them? These variables are often such things as temperature and time, and you need to think about how you can ensure consistency of these variables across the repeats in your experiment or investigation.
You also need to identify possible sources of error in the method for the experiment. Consider what things will stop making results consistent and clear across repeats.
When considering improvements to the method, refer to the key variables and sources of error you have identified previously, and then decide how they could be improved or overcome.
When looking for anomalous results, look for results that do not follow the pattern of other results. These are often those that are significantly higher or lower than other results around them. In particular, look at results across the repeats and highlight any that stand out as being very different.
And finally, remember that there may be multiple reasons for an anomalous result.
Why not exchange methods and experiment results with your fellow learners and try out the skills you have begun to develop in this video. There are also plenty of past paper questions you can practice your skills of evaluation on.
Good luck!
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Analysing practical work video transcript
The Cambridge International AS and A Level Marine Science syllabus you are studying will require you to describe patterns and trends from both tables of data and graphs. This video will help you to:
• Identify key points in data and the variability of data.
• Describe the main patterns and trends shown in tables and graphs
• And describe the key points from a set of observations.
Let’s look at an exam question that requires these skills to answer it. In this example a graph is provided, and you are asked to describe the change shown on the graph.
Looking at the graph it is possible to describe the trend in the line from left to right as body mass increases. At first there is a sharp or steep decrease in gill surface area to body mass ratio, then the gill surface area to volume ratio levels off as the body mass of the fish increases further.
This is a straightforward description, but remember that both parts of the trend are required for one mark, it would not be enough to simply state that the gill surface area to body mass ratio decreases as the body mass of fish increases, as this does not sufficiently describe the line shown on the graph.
Okay, let’s look at another exam question, and see if you can describe the changes shown in the graph. In this example the graph has two sets of data plotted and you are asked to describe the change shown by one of the sets of data. How do you think you would describe the changes in percentage live coral cover between 1996 and 2005 on the graph?
Maybe you need some help? So, let’s walk through how to answer this question using the skills you have learnt.
The first step is to identify the correct line to describe.
The question asks you to describe the changes in percentage live coral cover, so you need to describe this set of data, which is this line on the graph. Additionally, the question states that you only need to describe the changes between 1996 and 2005, which is just this section on the graph. A good tip here is that it can be useful to mark the dates on the graph to help you focus on the relevant sections.
Ok, now that you know which part of the graph you need to focus on, let’s start to describe the trend. The change shown on the graph is straight forward as the percentage of live coral cover decreases steeply during the time period, but answering the question like that would only receive one mark and there are two available. To achieve the second mark, you need to describe changes in the percentages as well. Looking at the percentage coral cover in 1996, this starts at 80% and decreases by 2005 to 14%. So, you can either state this change as ‘from 80% to 14%’ or even better you can calculate the decrease as 80 subtract 14 which is a 66% decrease. Adding this to your description would achieve the second mark for this question.
So your description of the changes in percentage live coral cover between 1996 and 2005 would be something like, ‘the graph shows that percentage live coral cover decreases by 66% between 1996 and 2005.’
Now let’s look at another example exam question that this time contains a table of data to consider. In this example the table of data contains three sets of data for different species of barnacles and their distribution on a shoreline. You are asked to compare the distribution of the three species. What do you think the table shows?
Looking at species 1; this species is more abundant further from the low water tide line, or higher up the shore, with very few lower on the shore. You can therefore state that species 1 is more abundant higher up the shore where it survives better.
Species 2 is more abundant closer to the low water tide line, or lower down the shore, with very few found a little higher up the shore, and none at all further up the shore. You can therefore state that species 2 is more abundant and survives better close to the water and cannot tolerate the higher shoreline environment.
Species 3 has the widest range of tolerance as it is found at all heights on this shoreline, but it is most abundant at 4 to 6 metres in particular. You can therefore state that species 3 has the greatest range on this shoreline, but is most abundant on the middle of the shoreline.
So, by writing down the descriptions of each species, highlighting where each is more or less abundant on the shoreline, you will be able to compare the barnacles and gain each of the three marks available for this question.
Here’s another example question, this time containing a graph containing data that changes less consistently between each point. Here you need to be able to identify the general trends as well as some particularly notable changes. How would you describe the changes mentioned in this question?
Well, the first step you would need to take would be to identify the range of dates relevant to the question. You only need to describe the changes in catch between 1980 and 2011, which is just this section on the graph. A good tip is that it can be useful to mark the dates on the graph to help you focus on the relevant sections.
As you can see, there are fluctuations, or smaller changes, within this time period, but the general trend is a decrease, and recognising this in your description of the changes in the graph is worth one of the possible three marks for this question.
The second point to note is that the decrease is more rapid initially, particularly from 1983 to 1989, so you can state in your description that the period of most rapid decrease is from 1983 to 1989, which would gain another mark.
Then after this more rapid decline, the catch has generally levelled off, or decreased much more slowly, and highlighting this in your description would gain the final mark available, although there have been smaller changes from year to year, so you could add that there are small fluctuations during this time period.
Finally, you could manipulate some of the data to state a calculated change for a period of time, which may be easiest for the total time change in the question. This shows a decrease of 32 thousand tonnes from 1980 to 2011, and this calculated decrease could also be worth a mark.
Okay, let’s look at one last exam question on which you can test your newly learnt skills. In this example question two graphs are provided with data that show changes in the mean number of lobsters caught per trap per day, at two different sites over five years, following the introduction of Marine Protected Areas, or MPAs, and control sites for comparison.
You can see that this question is worth 5 marks, so you will need to give a more detailed analysis of the graphs to score full marks compared to the previous questions you have looked at. The question asks you to “discuss the extent to which the results of this investigation support this conclusion”. Discussion questions require you to answer them in depth in a structured manner, so in this example you should normally expect to state reasons both for how the results do support the conclusion and how they don’t support the conclusion to gain all five marks.
The question states that the investigation led to the conclusion that ‘Marine Protected Areas assist in the recovery of the stocks of commercially fished species’. You are asked to discuss the extent to which the results of this investigation support this conclusion. So, let’s look at the graphs to see why they might have made this conclusion and whether the results of the investigation do actually support the conclusion.
Looking at the graph, you can see that the catch in the MPAs is shown by the grey bars, while the white bars are control areas, so how do you think the catch compares in these two areas for both sites? You can see that in both site A and site B the catch in the MPAs is higher than the catch in the control area in every year. So this supports the conclusion and is worth a mark.
Then, if you compare how the catch changes in each site over the five years, the catch in the MPAs generally increases over the five years, which also supports the conclusion and is worth a mark. There is a small decrease at site A from 2006 to 2007, and from 2009 to 2010. Identifying either of these is worth a mark but the error bars which represent standard deviations in the data show that the decrease is not significant as the margins of error for these bars overlap, so there could actually have been an increase in the catches if you allow for this error. By making this observation in your discussion of the results of the investigation, you would get credit for using the standard deviation error bars in an appropriate way to discuss the results.
Another way you could use these bars is to state that there is not a significant difference in the mean number of lobsters caught in the MPAs and control areas at both sites A and B in 2006, but in every year that follows the difference IS significant, supporting the conclusion again that the MPAs do assist in the recovery of the stocks.
So what else do the graphs show? You can see that they show that the rate of increase in catches in the MPA at site B is greater than the rate of increase in catches in the MPA at site A. This is also worth a mark.
At site B the number of lobsters caught at both the MPA and the control sites have increased each year, which could be explained by the increase in catches in the MPA indicating that the population of lobsters there has increased, which has resulted in some of these lobsters spilling out of the MPA into surrounding areas. Including this in your discussion would be worth one mark. However, there may also be another reason that has not investigated, that has caused the increase in both areas at site B that is resulting in an increase in the catch which would not support the hypothesis. Making that point in your discussion would also be worth one mark.
Finally, the conclusion states that MPAs assist in the recovery of the stocks of commercially fished marine species. On this point you should be aware that the data on the graphs is only for lobsters, so while the data supports the conclusion relating to lobster catch, there is no evidence to support the conclusion for any other species, so that part of the conclusion is not valid and a better conclusion from this data would be: ‘that MPAs assist in the recovery of the stocks of commercially fished lobster’.” Coming to this conclusion in your discussion would gain the final mark.
So, when you next analyse data in table or graphs remember to do the following:
It is always a good idea to highlight the data that you need to analyse if you aren’t expected to review all the data in a table or graph. Physically marking ranges on a graph or highlighting data in a table for example, can help ensure that you focus your efforts on analysing trends and patters in the correct area.
When writing up your description of the patterns and trends, make sure that you always draw attention to the key points in the data, and include it’s variability such as providing percentage increases or decreases.
Always pay attention to the number of marks available for questions asking you to explore patterns and trends. Questions with more marks will need to you provide a more in-depth analysis than questions worth fewer marks.
And if you are asked to analyse data in a graph or table against a conclusion or hypothesis, you should be aware that the data might both support and not support it.
In this video you have experienced a number of different exam questions on which to develop and test out your skills in identifying patterns or trends. Some have been relatively simple questions and data, whereas the last question clearly requires you to look much more critically at the data being presented. Why not now look at some more past paper questions that you can try out yourself, and when you are next writing up experiments or investigations make sure you consider the patterns and trends your data is displaying.
Good luck!
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