Example IA - Field Work - Aquatic Ecology
This page takes you through an IA that investigated populations of mayfly nymphs in river habitats. It is primary data collection.
Teacher only boxThis was an IA which was chosen as part of the sample required by the IB. The moderators agreed with teacher marking; this IA scored 27 points out of 30 and thus scored a top 7 in the current ESS course.
Note that I have made some small corrections to improve spelling and the references, but otherwise, the report is authentic.
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explains a local or global environmental topic or issue with sufficient background research to support the research question states a focused research question that addresses the chosen environmental topic or issue. |
I marked this RQ in the upper marband. The RQ contains an independent and dependent variable and a location. It is clear and concise and is appropriate to address the chosen environmental issue.
The RQ needs an independent variable, dependent variable, control variable/context and a time frame. The RQ could be improved by stating the month the investigation took place.
Alpine freshwater ecosystems, such as the Petite Gryonne river in Chesieres, Switzerland, are critical for biodiversity, water purification and local livelihoods. However, human activities in mountainous regions, including agriculture, often introduce pollutants that threaten these fragile habitats. Point sources of pollution,
such as agricultural runoff channels, can drastically alter water quality, with significant effects on aquatic organisms.
This investigation focuses on the impact of a point source of pollution resulting from agricultural runoff, discharged into the Petite Gryonne River by a drainage pipe. I will be investigating the abundance of the mayfly nymph, an organism commonly used as a bioindicator of freshwater ecosystem health, as it is highly sensitive to pollution. Mayfly nymphs require clean, well-oxygenated and chemically balanced water. By comparing the abundance of mayfly nymphs above and below a point source of pollution on the Petite Gryonne river, this research aims to understand the localised effects of pollution on aquatic invertebrate populations. The Petite Gryonne is a small alpine stream that runs through areas of mixed land use, including pastures and farmland. In this region, agricultural practices, such as the use of fertilisers and livestock grazing, can lead to nutrient-rich runoff entering water. This runoff is often channelled through man-made systems such as drainage pipes, making it a clear point source. These discharges can contain elevated levels of nitrates, phosphates, and organic matter, which may lead to downstream effects such as eutrophication and oxygen depletion. Several global studies have demonstrated the impact of point source pollution on aquatic invertebrate populations, particularly those sensitive to water quality, like mayfly nymphs. A study by Clements et al. (2000) (of America 2) in the Rocky Mountains, USA, found that aquatic insect diversity, especially mayflies and stoneflies, significantly declined downstream of metal-contaminated mine drainage, showing their sensitivity to heavy metal pollution. In a separate study, Arimoro and Ikomi (2009) (Anthony E. Ogbeibu, Priscilla A. Oriabure) investigated the impact of wastewater pollution on the River Ethiope in Nigeria and observed a substantial reduction in mayfly and caddisfly populations downstream of the discharge point, indicating deteriorated water quality due to organic and nutrient pollution. Iwasaki et al. (2011) (Yuichi Iwasaki), research conducted in northern Japan, compared macroinvertebrate communities just upstream and downstream of treated industrial effluent inputs. They discovered a ~58% decline in mayfly abundance below the discharge point, compared to reference sites, signifying marked ecological stress from localised pollution. These studies reinforce the reliability of mayflies as bioindicators and the ecological risk posed by localised pollution inputs into freshwater systems.
To investigate the effect of agricultural runoff on mayfly nymph abundance, 28 sampling sites were selected along the Petite Gryonne River in Chesières, Switzerland, 14 upstream of the wastewater pipe and 14 downstream, therefore assuming the abundance of mayfly nymphs will differ as they are sensitive to the pollution. Sites were chosen based on accessibility and the presence of similar physical characteristics to reduce the impact of confounding variables. Flow velocity (200–350 cm/s) and depth (12–16 cm) were consistent across sites, ensuring differences in abundance could be due to pollution rather than environmental variation. Although 14 replicates per area is a relatively small sample, it provided sufficient data for a valid comparison, as well as I considered the time available in which was the maximum I could do.
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explains a local or global environmental topic or issue with sufficient background research to support the research question states a focused research question that addresses the chosen environmental topic or issue. |
The background information is very detailed and links back clearly to the environmental issue under investigation.
Using maps to provide a context for the IA is essential and can also be used in the method to ensure it is “repeatable”. This student has also cited academic articles which improve academic rigour.
Use of in Denmark (Audet) has been created to capture nitrogen and phosphorus from fertilisers before they reach rivers. These wetlands act as natural filters, improving water quality while also still allowing farming to continue. Backed by government funding helps encourage them to implement it. Ecocentrics believe, this solution is beneficial because it prioritises the health of ecosystems. The wetlands prevent the run-off from going to the water, protect the biodiversity in rivers, especially mayflies, which detect the water quality. As ecocentric people would be against human activities which harm the rivers, the use of the wetlands would be a step towards restoring the environment and sustainability. However, their perspectives can be even more serious, maybe to significantly reduce the use of fertilisers for a more long-term effect. From an anthropocentric perspective, this solution is also good because it allows farming, so the economy can grow while causing less harm to the environment. However, challenges remain for farmers, as the cost of implementing constructed wetlands can be high if not subsidised by the government, and the wetlands also require a significant land area that could be used for farming and bring farmers revenue. There can be a tension between the perspectives because the ecocentric may see wetlands as only a partial fix that fails to address the root cause of over-fertilisation, and the anthropocentric may want to continue increasing economic growth through farming without spending money on solutions. The ecocentric may push for more restrictions on agriculture, the anthropocentric may argue that they would like to be cost-effective and maintain competitiveness in agriculture. constructed wetlands are a good balance between protecting rivers and supporting farming, but they should not be seen as the final solution. They help reduce immediate pollution risks and protect species like mayflies, but stronger regulation of fertiliser use is still needed to address the root causes of runoff. I think Switzerland, like Denmark, could adopt wetlands near ski resorts and farmland, but also introduce stricter rules to reduce harmful chemicals. This combined approach would reduce conflict while ensuring rivers are protected in the long term.
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| states an existing or developing strategy that addresses an environmental issue linked to the research question describes a tension between different perspectives (economic, social, cultural, political or environmental) that results from the strategy | describes an existing or developing strategy that addresses an environmental issue linked to the research question explains a tension between different perspectives (economic, social, cultural, political or environmental) that results from the strategy |
The student did a great job of describing an existing strategy and explaining the tensions which exist between the different stakeholders.
To control for potential sources of error and bias, sampling was conducted during consistent weather conditions, avoiding periods of rain or runoff surges that could artificially influence the results. One of the goals was not to disturb the sediment or riverbed upstream of sampling locations prior to collection, as this could lead to inaccurate data by displacing organisms. Additionally, organisms were returned to the river immediately after counting to minimise environmental disturbance, in line with ethical fieldwork practices.
Method A: measuring biotic factors (mayfly nymphs)
Equipment needed:
1. Kick sampling net
2. White tray or basin
3. Pipette
4. Loupe (hand lens)
5. Identification sheet for freshwater organisms
6. Waders or waterproof boots
7. Stopwatch or timer
8. Clipboard & data sheet
9. Measuring tape
Instructions:
1. Find the location in the Villars-sur-Ollon in the river Petite Gryonne above and beneath the wastewater pipe, using Google Earth.
2. Randomly choose sites, however, ensuring safety: avoid strong currents and slippery rocks.
3. Fill up the white tray with river water.
4. Place the kick net downstream, flat against the riverbed.
5. Ensure the mouth of the net is facing into the current and is held steady.
6. Stand upstream of the net.
7. Make sure the distance between where you stand and the net is 30 cm.
8. Vigorously disturb the substrate (stones, gravel) for 2–3 minutes using your feet, so that mayfly nymphs can flow into the net.
9. Carefully lift the net and turn it inside-out into a white tray filled with river water, and swish the net in the tray to transfer all material.
10. Use the pipette to pick out small, moving organisms (mayfly nymphs) from the tray.
11. Place them in smaller containers with clean river water.
12. Use the loupe (hand lens) to observe key features of the nymphs (be sure it is a mayfly nymph, look for these characteristics):
- 3 tail filaments
- Gills on the sides of the abdomen
- Slender, soft body
13. Compare your sample to a biological identification key or sheet to confirm the presence of mayfly nymphs.
14. Count the number of mayfly nymphs and note their abundance.6
15. Fill in your data sheet
16. Return all live organisms gently back into the river at the same location.
17. Repeat the procedure on each site
18. Rinse the net, tray, pipette, and loupe to avoid cross-contamination between sites.
The abiotic factors were monitored throughout the investigation. I did it to understand whether they could be a reason for the difference in the mayfly population, or if they were consistent, through that I hope to strengthen the reliability of my conclusions.
Equipment needed:
1. Clean sample containers (x3–5)
2. pH, nitrate, and ammonia test strips
3. TDS meter
4. Conductivity meter
5. Digital thermometer
6. Data sheet + clipboard + pen/pencil
7. Waste bag for used strips
8. Gloves (optional)
Instructions:
1. Choose a flowing part of the river in both sites, avoiding eddies and pools.
2. Ensure stable footing, wear boots or waders if needed.
3. Collect river water from just below the surface (~10 cm deep).
4. Start recording the abiotic factors:
- Dip pH strip into water sample (as per package instructions, 1–3 sec).
- Remove and wait 15–30 seconds for colour to stabilise.
Remove and wait 15–30 seconds for colour to stabilise.
- Record value in data sheet
2. Test for nitrates and ammonia: (same procedures)
- Dip nitrate strip into new water sample.
- Hold in water or swirl as instructed (~10 seconds).
- Wait for colour development (30–60 seconds).
- Compare with nitrate colour chart.
- Record result in data sheet
3. Measure TDS:
- Turn on the digital TDS meter and place the probe in the water.
- Wait for reading to stabilise.
- Record value in data sheet
4. Measure temperature:
- Place the thermometer directly in the river or the sample.
- Wait 30–60 seconds.
- Record temperature in °C
The method is clear, comprehensive, repeatable and collects sufficient data for the statistics to be used.
Table 1: Table of Abiotic Data from 5 sites above the pollution (monitored variables)
Table 2: Table of Abiotic Data from 5 sites below the pollution (monitored variables)
Table 3: Biotic data: Abundance of mayfly nymphs above and below the runoff pipe
Table 4: This table shows the controlled variables of velocity and depth above and below pollution.
The sampling depth was carefully controlled between 13 and 17 cm at each site to ensure consistency and reliability in the data collection. I have used a ruler to measure the depth. Controlling for depth is crucial because depth directly affects environmental conditions such as water temperature, which can influence the distribution and affect the abundance of mayfly nymphs. By standardising the depth, we minimise variability that could come from sampling in habitats that naturally differ. in these conditions. This makes the comparison between sites more reliable and valid. In addition to controlling for depth, water velocity was also standardised between 200 and 500 revolutions/m at all sampling points to improve the reliability of the results. Water velocity can significantly influence the distribution of aquatic organisms, including mayfly nymphs, as faster-moving water typically has higher oxygen levels and can better support these sensitive organisms. Slower water, on the other hand, often has more sediment build-up and lower dissolved oxygen, which can negatively impact mayfly populations. This ensures that any differences in mayfly abundance observed above and below the runoff pipe are more likely due to the effect of the pollution source, rather than natural variations in flow speed. In addition to the quantitative data on mayfly nymph abundance, which I have collected, I made some qualitative observations during sampling, which provide further context for interpreting the results. Above the runoff pipe, the water appeared clearer, with less visible sediment, and the riverbed was covered in stable stones and aquatic vegetation, offering suitable microhabitats for mayfly nymphs. In contrast, below the runoff pipe, there was a noticeable change in water quality, including increased turbidity and a slight smell, which may suggest organic pollution or nutrient loading. As well as above the pollution, the accessibility to the sites was much easier, as there were no dangerous conditions like rocks, which could cause potential health issues, unlike in the pollution sites below the source.
I have used a Mann-Whitney U test to test for differences between two sets of data by measuring the amount of overlap in the data. I have taken 14 samples at each site, so this meets the requirement of the test, which is 5 to 20 samples. My data doesn't show a normal distribution, so this makes this test best for my investigation. Using the Mann-Whitney U test was a strong choice for this investigation because it adds scientific rigour and statistical validity to the analysis of my results. I used Mann- Whitney because it can handle really small samples like mine. There is a large standard deviation, which implies there is a high degree of overlap.
Graph 7: Shows the non-normal distribution of data above the source of pollution
Graph 8: Shows the non-normal distribution of data below the source of pollution
Null hypothesis: There is no statistically significant difference between the abundance of mayflys above and below the run-off pipe.
Alternative hypothesis: There is statistically significant difference between the abundance of mayflys above and below the run-off pipe.
I used an online calculator to solve this equation as shown in Figure 2:
The calculated value of U (71.5) shows there is an overlap in the two data sets. The U value is greater than the critical value (55) at p<0.05, therefore accept the null hypothesis. There is no significant difference between the abundance of mayfly nymphs above and below the run-off pipe.
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| The communication of raw and processed data is clear. The techniques used to process the raw data lead to findings that do not fully address the research question. The raw data is processed with some minor errors. | The communication of raw and processed data is clear and detailed. The techniques used to process the raw data lead to findings that fully address the research question. The raw data is processed correctly. |
Some of the data presented lacks the correct headings and could be more clearly presented. That being said, the student has explored all possible ways of manipulating and processing the data to reach a supported conclusion.
Graph 6 shows a slight decrease in the abundance of mayfly nymphs in the area below the run-off pipe compared to the area above the run-off pipe, from an average of 4 to 2.71. Samples above the pollution source showed slightly higher numbers of mayfly nymphs, but the difference was not dramatic or consistent across all samples. While this may initially suggesThis means the difference in mayfly nymph abundance between the two sites is not statistically significant, and we cannot confidently say that the runoff pipe has a measurable effect based on this test alone, meaning that we need to consider all of the factors which indicate the relationship. This lack of statistical significance may be due to n environmental conditions, or it may indicate that the runoff is not yet having a strong or consistent impact on mayfly populations, considering the weather conditions, as it was thundering in Villars for a week, and there was increased precipitation therefore, some of the pollution and mayfly nymphs were washed away. An anomaly was observed at site 1 below the source of pollution, where I found 6 mayflies, which significantly differ from all of my other data in that area, which contrasts with the overall expectation. This means that species might have been adapted to the habitats that are present, and this can influence the results stronger than the pollution. However, it can also be just the nature of random sampling, this may be an anomaly for no real reason, so there is a chance there are some more in a certain location. Abiotic factors likely played a significant role in the variability observed. As shown from the graphs 1- 5 and the table 1-2, the factors which were constant across both areas were temperature and pH, as well as ammonia, which on both sites was 0. The nitrates were greater in the area above the pollution pipe of 1.56 compared to 1.34; however, the electrical conductivity and average TDS are greater below the run-off pipe. Also, the standard deviation shows that the range where the percentage of error might occur differs on both sites; however, all abiotic factors have significantly low standard deviations, meaning that the results are reliable. These factors may have varied slightly between sampling locations, even though efforts were made to control them by maintaining consistent depth and flow velocity. Additionally, the visual clarity of the water, the presence of algae, or sunlight exposure may have indirectly affected the samples. Although uncertainties, such as counting errors, the natural environment, and I couldn't control the biotic and abiotic variables, such as uneven distribution in the substrate, may have influenced the results, the control measures applied in the investigation helped improve the reliability and validity of the data. However, the small sample size and limited time spent on investigation reduce the strength of any conclusions drawn.
Conclusion
The data do not show a statistically significant difference in the abundance of mayfly nymphs above and below the point source of pollution. While there is a slight trend toward lower abundance downstream below the run-off pipe, the Mann-Whitney U test indicates that this pattern is not strong enough to be considered reliable. Therefore, the conclusion is that the pollution source may not be having a measurable effect on the mayfly population under current conditions, or that abiotic variation and natural habitat may have a hidden real impact.
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| The analysis describes patterns or trends within the data that are relevant to the research question, including (some) measures of bias, reliability, validity and uncertainty. The conclusion addresses the research question and is partially supported by the analysis presented. | The analysis explains all the patterns and trends within the data that are relevant to the research question, including measures of bias, reliability, validity and uncertainty. The conclusion addresses the research question and is supported by the analysis presented. |
Although the student presented a valid conclusion, the reference to measures of bias and uncertainty were perhaps a little limited.
This investigation helped to understand how pollution (from agriculture) might affect the aquatic biodiversity, specifically through the abundance of mayfly nymphs. However, some of the variables, like weather and environmental conditions, so there are still significant limitations that influenced the outcome and overall confidence in the conclusion. Random errors, such as misidentifying nymphs or overlooking small individuals during counting, could have influenced the accuracy of the results. One major limitation was the limited sample size of 14 samples per site. Although this is statistically good amount of data for using the Mann-Whitney U test, it reduces statistical power and makes random variation more influential. In further study, I would aim to have a larger dataset (30+ samples per site) to reduce uncertainty and allow for stronger statistical analysis. A larger sample size can also make patterns clearer and allow detection of weak ecological effects. Another crucial improvement would be to include abiotic data measurement at all sampling points. While I controlled for depth and velocity, I did not measure variables. like pH, dissolved oxygen, temperature, turbidity, or substrate type that significantly affect mayflies. When conducting a future study, I would use portable sensors to measure these abiotic factors along with the biotic data. These quantifications would help determine if pollution or other environmental gradients are affecting changes in the abundance of nymphs. The kick sampling method could also be improved. Variable kicking force and sampling angle could have led to variability in the number of invertebrates sampled. I would improve this by using a timer and consistent foot movement, and making multiple kick samples per site to average variability. To further improve accuracy, I could also use video or digital counters for the ring consistency of the sampling method. To even better strengthen the study, I would consider seasonal repetition, wherein the same tests are replicated in spring, summer, and autumn to account for seasonal life cycle differences between aquatic insects. Mayflies naturally fluctuate in population over the course of a year, so sampling within only one season is not general enough to make conclusions. The data addresses the research question to some extent by exploring potential patterns, but due to the lack of significance and the influence of confounding factors, no firm causal link can be established; however, looking at some factors, there is clearly a little change and relationship between the run-off pipe and abundance of mayfly nymphs. Next time I should use a digital measuring device, instead of strips, because personal perspective of colour can vary. Only looking at one species limits the overall understanding of the impact of any pollutant on the system. Mayflies are very sensitive to pollution, but they are not the only species, so I would suggest measuring all the biodiversity in the area. Further investigation with a larger sample size, repeated seasonal sampling, and more detailed abiotic measurements would be needed to draw more definitive conclusions.
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| describes methodological limitations or weaknesses that impact the conclusion describes improvements to the method that address the identified limitations or weaknesses outlines unresolved questions that arise from the investigation. | evaluates specific methodological limitations or weaknesses that impact the conclusion evaluates improvements to the method that address limitations or weaknesses describes unresolved questions that arise from the investigation as they impact the conclusion. |
This is definitely the hardest part of the IA - not for the technical skills as in the processing but in the deep thinking required to reflect on the weaknessses of the IA and to suggest unresolved questions. This student did a commendable job but still ran out of steam for the unresolved questions.
Anthony E. Ogbeibu, Priscilla A. Oriabure. “Assessment of the Water Quality of the Benin River, Southern Nigeria, Prior to the Seaport Development Project.” Assessment of the Water Quality of the Benin River, Southern Nigeria, Prior to the Seaport Development Project, Anthony E. Ogbeibu, Priscilla A. Oriabure, 15 november 2009,
https://www.scirp.org/reference/referencespapers?referenceid=3603655&utm. Accessed 20 may 2025.
Joachim Audet. “Nitrogen and phosphorus retention in Danish restored wetlands.” Nitrogen and phosphorus retention in Danish restored wetlands, Joachim Audet, 16 April 2019, https://pmc.ncbi.nlm.nih.gov/articles/PMC6888804/. Accessed 7 September 2025.
of America, Ecological Society. “HEAVY METALS STRUCTURE BENTHIC COMMUNITIES IN COLORADO MOUNTAIN STREAMS.” HEAVY METALS STRUCTURE BENTHIC COMMUNITIES IN COLORADO MOUNTAIN STREAMS, 2000, p. 13. pebbledocs,
https://pebbledocs.org/Fisheries/Clements%20et%20al%20%20Metals%20%26%20Benthic%20Communities%20in%20Colorado%20Streams%2020May99.pdf. Accessed 20 may 2025.
Yuichi Iwasaki. “Responses of Riverine Macroinvertebrates to Zinc in Natural Streams: Implications for the Japanese Water Quality Standard.” Responses of Riverine Macroinvertebrates to Zinc in Natural Streams: Implications for the Japanese Water Quality Standard, Yuichi Iwasaki, 3 january 2011,
https://www.researchgate.net/publication/227238682_Responses_of_Riverine_Macroinvertebrates_to_Zinc_in_Natural_Streams_Implications_for_the_Japa nese_Water_Quality_Standard. Accessed 20 may 2025.