IGCSE Environmental Management Paper 2 — Environmental Management in Context

1 independent variable: distance from the edge of the footpath (in metres)

2 dependent variable: percentage cover of grass OR percentage of bare ground

do not credit "trampling" for the independent variable — trampling was never measured, only distance was

1 any 1 from: the size of the quadrat (0.25 m²); the same person estimating cover, or the same counting rule; the time of day and the weather; the slope and aspect of the ground; the soil type; the same day

2 explains what would otherwise happen, for example: a larger quadrat further from the path would cover more ground, so the percentage figures could not be compared between positions

3 states the consequence for the conclusion: a change in cover could then have been caused by the change in quadrat rather than by the distance from the path, so it would be impossible to tell which caused it

full marks need the chain: what is kept constant → what would go wrong → why the conclusion would be unsafe

1 identifies that the class is looking for a change with distance, so quadrats must be spread evenly along a line (a belt or line transect) from the path outwards

2 any 1 from: fixed 2 m intervals guarantee a reading at every distance, including close to the path; random positions could by chance cluster in one zone and miss the gradient altogether; the pattern in Table 2.1 (8% rising to 82%) is only visible because the positions are evenly spaced

3 limitation, any 1 from: fixed intervals can coincide with a repeating feature in the ground and give a biased picture; a systematic sample is not a random sample, so it should not be used to estimate the average cover of the whole field; the person choosing the line still chooses where the transect starts

accept the reverse argument for mark 3: random sampling would be the better choice if the aim were the overall abundance of grass in the field rather than the change with distance

1 pitfall trap

2 justification, any 1 from: beetles walking on the soil surface fall into the sunken container and cannot climb out; the trap collects animals continuously so it does not depend on the students being present; it catches animals that are active at night

3 rejects an alternative with a reason, any 1 from: a sweep net samples invertebrates living in the vegetation, not on the ground; a pooter can only take an animal you have already found by hand-searching, so the number caught depends on the searcher; aerial photography and drones cannot resolve an animal of this size

for a valid comparison the traps must be the same size, use the same bait or none, and be left for the same length of time at both distances — credit this as an alternative to mark 3

1 a specific risk, any 1 from: sunburn or heat exhaustion in open grassland; a tick or insect bite; contact with a stinging or irritant plant; tripping on uneven ground; contamination of hands with soil bacteria; being struck by a cyclist or vehicle using the path

2 a precaution that matches the risk, any 1 from: sun hat, sunscreen and drinking water; cover arms and legs and check for ticks afterwards; wear gloves when handling vegetation and soil; wear closed walking shoes and watch the ground; wash hands before eating; work to one side of the path and keep the tape flat

the precaution must reduce the risk that was named; a mismatched pair scores one mark only

M1 selects the renewable resources only — hydro-electric, wind and solar: 24 + 40 + 20 = 84 TWh

A1 84 ÷ 200 × 100 = 42%

nuclear is not renewable — it uses uranium, which is a finite resource. Including it gives 45% and scores zero for A1

1 110 million tonnes (accept 108–112)

2 2019 — the 2018 point is above the 120 gridline and the 2019 point is below it

read across from the point to the axis using the minor gridlines, which are every 10 million tonnes

M1 reads 150 for 2015 and 90 for 2025 and divides the change by the 2015 value: (90 − 150) ÷ 150 × 100

A1 = −40%, a decrease of 40%

1 total generation is unchanged at 200 TWh, so the fall in emissions is not caused by generating less electricity — the mix has changed

2 coal generation halved, from 120 to 60 TWh, and combustion of coal releases carbon dioxide

3 renewable generation rose from 30 to 84 TWh (15% to 42%), and hydro, wind and solar release no carbon dioxide as they generate

a mark is also available for noting that natural gas rose from 40 to 50 TWh, which offsets part of the fall because gas is also a fossil fuel

1 confirms the average is correct: (150 − 90) ÷ 10 = 6 million tonnes per year, and 90 ÷ 6 = 15 more years, which is 2040

2 identifies that the line is not straight — the fall was about 8 million tonnes per year in the first five years but only about 3 million tonnes per year in the last three (100 to 90 between 2022 and 2025)

3 uses the recent rate instead: at about 3 million tonnes per year, 90 ÷ 3 would take a further 30 years, well beyond 2040 — so the average across the whole period flatters the trend

4 any 1 from: extrapolating 15 years beyond the last data point assumes the trend continues, which the graph cannot show; the remaining emissions come from coal and gas plants that may be the hardest to replace; demand could rise; a new policy could speed the fall up; reaching exactly zero is a stronger claim than the data support

an answer that argues the claim could be met, provided it gives a reason from the data (for example that the 2021 to 2022 drop shows a faster rate is achievable), can take mark 4

B1 identifies plot 3 (11.6 kg) as an anomalous result — it is nearly three times the other two plots of the same treatment, and higher than every plot given treatment B

M1 excludes it and averages the remaining replicates: (4.2 + 3.8) ÷ 2

A1 = 4.0 kg

a mean of all three values (6.5 kg) scores B0 M0 A0, because the anomaly has not been identified

a candidate who keeps the anomaly but states clearly why it is being kept, and calculates 6.5 kg correctly, can take M1 only

1 4.0 kg — on the labelled 4 gridline, between the bars for B and D

allow the value carried forward from part (a) if part (a) was wrong but the reasoning here is right

M1 (12.2 − 2.1) ÷ 12.2 × 100

A1 = 82.8% (82.786... to 3 significant figures)

an answer of 82.79% or 83% loses A1 — the question specified three significant figures

1 a statement linking the independent variable to the dependent variable, for example: plots that keep a cover of vegetation or crop residue will lose less soil than bare plots

2 it is testable, that is it predicts a direction and names something that was actually measured (mass of soil collected), so the results can support it or contradict it

accept the null form: there will be no difference in soil loss between the four treatments

do not credit a question ("does mulch reduce soil erosion?") or an aim ("to investigate soil erosion") — a hypothesis is a statement that can be shown to be false

1 a steeper slope makes water run off faster OR gives the run-off more energy, so more soil particles are carried away

2 so if the plots had different slopes, a difference in soil loss could have been caused by the slope rather than by the treatment, and the two effects could not be separated

3 one further control variable, any 1 from: soil type and texture; rainfall received by each plot; the crop grown; the initial organic content of the soil; the drying method and time before weighing; the length of the season monitored

mark 2 needs the consequence for the conclusion, not just the words "fair test"

1 one limitation, any 1 from: only one rainy season was monitored, and a wetter or drier season could give a different ranking; only three replicates per treatment, so one odd plot has a large effect on the mean, as treatment C showed; one site and one soil type, so the results may not apply elsewhere; rainfall on each plot was not measured, so it is assumed rather than known to be equal; soil that moved but was not caught by the trough was not counted

2 an improvement that matches the limitation, any 1 from: repeat over several seasons; increase to five or more replicate plots per treatment; repeat at sites with different soil types; place a rain gauge on each plot and record the rainfall; extend the trough across the full width of the plot

3 a judgement supported by the spread of the data, for example: the difference between A (12.2 kg) and D (2.1 kg) is far larger than the spread within any treatment (11.7 to 12.6 kg in A), so the conclusion that ground cover reduces soil loss is well supported; but the ranking is less secure for treatment C, where one of only three plots had to be set aside

1 Town P: 12 ÷ 24 000 × 10 000 = 5.0 per 10 000

2 Town Q: 210 ÷ 30 000 × 10 000 = 70 per 10 000

both values are needed; one correct value scores one mark

1 Town P had 36 hours of warning against 6 hours in Town Q, and evacuated 90% of its people against 45%

2 explains the link: a longer warning gives time to move people inland or to shelters before the flooding and storm surge arrive, so far fewer people are in the damaged buildings when the cyclone strikes

3 shows the storm itself was of similar strength in both towns, so the warning is the likely cause: buildings damaged per 1 000 people is 75 in P and 70 in Q, and the cost per person is similar

accept for mark 3 any use of the damage figures to argue the hazard was comparable, or a comment that other factors such as building quality were not recorded

1 place X

2 X meets all three conditions: latitude 15° N lies between 5° and 30°, the sea surface is 28.0 °C which is at least 27 °C, and the ocean is 90 m deep which is at least 60 m

3 any 2 of the rejections: W is only 2° from the Equator, inside the 5° limit; Y is 24.0 °C, below the 27 °C needed; Z is at 40° N, outside the 5° to 30° band

note that W, Y and Z each satisfy two of the three conditions — all three must be met

Level 3 (5–6 marks) both benefits and limitations are developed, at least one point is supported by the data in Table 5.1, and a clear judgement is reached that follows from the points made.

Level 2 (3–4 marks) both sides are given but one is thin, or the points are correct but undeveloped, or there is no judgement.

Level 1 (1–2 marks) only one side is given, or general statements with no reference to cyclones.

Benefits — any 3 from: warning allows evacuation, which is what separated Town P from Town Q (5 against 70 deaths per 10 000); it protects people wherever they are, not only those in newly built houses; it is cheap compared with rebuilding a coastline; it works for the buildings that already exist; the same monitoring network also serves flooding and drought warnings; satellite and computer forecasting keeps improving.

Limitations — any 3 from: a warning does not reduce damage to property at all — Town P still lost 1 800 buildings and US$40 million; it depends on the message reaching people, and the transmitter fault in Town Q shows how a single failure removes the whole benefit; there must be somewhere to evacuate to, so shelters and roads are also needed; some people will not leave livestock or property; forecasts of the exact track are uncertain, and a false alarm reduces the response next time; spending everything on one strategy leaves nothing for building standards or land use zoning, which reduce damage rather than only deaths.

Judgement a supported conclusion either way, for example: warning is the most effective single way to reduce deaths per dollar and should be funded first, but funding it alone is not justified because the damage figures show that lives and property need different measures. An answer arguing that a poorer country should still prioritise warning, because saving lives matters most and the buildings can be rebuilt, is equally creditworthy if argued from the data.

1 14%

2 7%

both bars end exactly on a gridline; the minor gridlines are every 1% and the labelled ones every 2%

M1 adds males and females in the 0–9 and 10–19 bands and in the 60–69 and 70+ bands

A1 Country J: (14+14) + (12+12) + (1.5+1.5) + (1+1) = 52 + 5 = 57%

A1 Country K: (5+5) + (5.5+5.5) + (6+6) + (7+7) = 21 + 26 = 47%

a useful check: each pyramid must total 100%, so the working population is 43% in J and 53% in K

1 comparison with figures: J has a wide base and narrow top — 52% are under 20 and only 5% are 60 or over; K is far more even, with 21% under 20 and 26% aged 60 or over

2 a problem for J, any 1 from: 43% of the population supports the other 57%; demand for school places, healthcare for children and, in ten to twenty years, for jobs and housing as the wide base reaches working age

3 a problem for K, any 1 from: 26% are aged 60 or over, so demand for healthcare and pensions is high and rising; only 21% are under 20, so the working population will shrink as the large 40–59 group retires

for mark 1 a comparison must mention both countries; describing only one scores zero for that mark

Level 3 (5–6 marks) both benefits and limitations are developed, the answer is set in Country J’s situation rather than being general, and a clear judgement is reached that follows from the points made.

Level 2 (3–4 marks) both sides are given but one is thin, or the points are correct but undeveloped, or there is no judgement.

Level 1 (1–2 marks) only one side is given, or general statements about education with no link to population size.

Benefits — any 3 from: women who stay in education longer tend to have their first child later and to have fewer children, which lowers the birth rate; education explains how contraception works and where to obtain it; educated women are more likely to enter paid work, which raises household income and reduces the economic reason for having many children; it also lowers infant mortality, so families do not need extra births to be confident of surviving children; unlike an anti-natalist law it is voluntary and does not restrict anyone’s choices; the same schooling raises the skills of the workforce, which J needs as its large young population reaches working age.

Limitations — any 3 from: it is slow — the effect on the birth rate appears a generation later, and J’s 52% under-20s will reach childbearing age long before then; building schools and training teachers is expensive for a low-income country; families who need children to work may keep them out of school whatever the government provides; where the number of children per family is a strong social or religious expectation, education alone may not change it; it does nothing about the immediate demand for school places, jobs and housing; it may need to be combined with access to healthcare and contraception to have any effect.

Judgement a supported conclusion either way, for example: education is the most durable strategy because it is voluntary and brings benefits beyond population size, but it cannot be J’s only measure because it acts too slowly for a population already this young. An answer arguing that the slowness is acceptable because faster strategies are coercive, or that limited funds should go to healthcare first, is equally creditworthy if it is argued.