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Question 23M.2.SL.TZ1.1

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Date May 2023 Marks available [Maximum mark: 13] Reference code 23M.2.SL.TZ1.1
Level SL Paper 2 Time zone TZ1
Command term Analyse, Compare and contrast, Evaluate, Outline, State, Suggest Question number 1 Adapted from N/A
1.
[Maximum mark: 13]
23M.2.SL.TZ1.1

Remote sensing satellites are used to monitor the Earth’s ecosystems. One measure of ecosystem status is leaf area index (LAI), which is the total area of leaves in square metres per square metre (m2 m−2) of the Earth’s surface. The graph shows LAI estimates, calculated using data from the Global Inventory Monitoring and Modelling System (GIMMS), during the period from 1981 to 2011. The data points are monthly averages in four latitudinal zones in the northern hemisphere.

[Source: Zhu, Z. et al., 2013. Global Data Sets of Vegetation Leaf Area Index (LAI)3g
and Fraction of Photosynthetically Active Radiation (FPAR)3g Derived from Global Inventory
Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) for
the Period 1981 to 2011. Remote Sensing, [e-journal] 5, pp. 927–948.
https://doi.org/10.3390/rs5020927. Open access.]

(a)

Compare and contrast the LAI data for the arctic and temperate zones.

[2]

Markscheme

Similarity
both rise to peak/maximum/are highest in summer/warmest months/June/July/August
OR
both lowest in winter/December/January
OR
both rise then fall;

Difference
temperate always higher/higher overall/higher throughout year
OR
temperate peak is higher/is one month later/is in August versus July in arctic;

For the difference, accept answers given as the converse of the mark point.
For the difference, do not accept answers stating just that arctic LAI is lower or that the arctic has lower LAI on average.

(b)

Suggest reasons for the differences in LAI between the boreal and equatorial zones.

[3]

Markscheme
  1. climate/temperature/light consistent throughout year in equatorial but seasonal variation in boreal;
  2. conditions suitable for photosynthesis throughout the year in equatorial but not in boreal;
  3. temperatures higher/growing season longer in equatorial versus lower/shorter in boreal;
  4. water frozen/unavailable in boreal during winter whereas always available in equatorial;
  5. shorter daylengths in winter in boreal (than those months in equatorial so lower LAI);
  6. boreal LAI higher (than equatorial) in July due to longer daylengths;
  7. equatorial trees/plants are evergreen / boreal trees/plants are deciduous/have less/no leaves in winter;
  8. variation in angle of light rays (between different latitudes);

There is evidence of a change in mean LAI values on Earth over recent decades. Changes can be quantified by calculating LAI anomalies. These are differences between annual LAI values and the mean LAI for the entire given time period.

The graph shows global LAI anomalies for the period from 1981 to 2014, based on data from GIMMS. It also shows mean global LAI anomalies between 1981 and 2009, based on data from three other remote sensing programmes. Vertical bars show the timing of El Niño events. The darkness of the bars indicates the intensity of the El Niño events. The darker the bar, the more intense the event.

[Source: Material from: Zhu, Z., Piao, S., Myneni, R., et al., Greening of the Earth and its
drivers, published 2016, Nature Climate Change, reproduced with permission of SNCSC.]

 
(c)

Analyse the data shown in the graph for evidence of a relationship between LAI and El Niño events.

[2]

Markscheme
  1. decreases in LAI during El Niño
    OR
    increases in LAI between El Niño events;
  2. 1983-4/other example of a decrease during El Niño
    OR
    1984-6/other example of increase between El Niño events;
    OR
    94-95/2009 anomalous as LAI rises during El Niño event;
    OR
    99-2000 anomalous as LAI decreases between El Niño events;
  3. larger decrease (in LAI) with more intense/longer El Niño events
    OR
    no/less decrease during less intense/briefer El Niño events;

Mpa refers to changes in LAI, not whether levels were high or low.

The example given for mpb must correspond with the trend given in mpa. The graph does not show the years clearly so we must show some lenience in mpb – award this mark if it is clear which period the candidate was referring to.

For mpa, do not accept answers implying that decreases in LAI cause El Niño or increases in LAI prevent El Niño.

(d)

The data in the graph show a long-term trend in global LAI.

(d.i)

State the trend.

[1]

Markscheme

Increase/increasing/upwards/rising (trend);

Reject ‘positive’, ‘positive trend’ and ‘positive correlation’
Accept linear increase.

(d.ii)

Global ecosystem modelling suggests that most of the change in LAI is due to increases in atmospheric carbon dioxide. Explain how rising atmospheric carbon dioxide (CO2) concentration could cause the observed change in LAI.

Markscheme
  1. more photosynthesis (with higher carbon dioxide concentration);
  2. more plant growth/more (plant) biomass/more leaves/more plants;

If the answer focuses on greenhouse effect or global warming, do not award mpa, but mpb can be awarded if one of the alternatives is included in the answer.

The 2015 Paris Agreement sets out an international framework for avoiding dangerous climate change. A key aspect is conserving and enhancing sinks of greenhouse gases, including forests.

Free air carbon dioxide enrichment (FACE) experiments are being used to investigate whether increases in atmospheric CO2 concentration will cause biomass increases in existing forests. Three FACE experiments have been running for at least ten years in young, developing forests. Photosynthesis rates are measured in 25 to 30 m diameter plots. In control plots, carbon dioxide concentrations remain at current atmospheric levels (ambient CO2). In treatment plots, the COconcentration is raised by 50 % (elevated CO2).

The table gives some details of these experiments and the highest annual net primary production recorded during the period of the experiment. Net primary production is the mass of carbon absorbed and fixed by photosynthesis in plants that is not released due to plant respiration.

 

    Maximum annual
net primary production
/ kg C m–2 y–1
Site of experiment Dominant tree species Ambient CO2 Elevated CO2
Rhinelander, 
Wisconsin
Populus tremuloides 
(deciduous angiosperm)
0.81 0.98
Oak Ridge, 
Tennessee
Liquidambar styraciflua 
(deciduous angiosperm)
1.00 1.26
Duke, 
North Carolina
Pinus taeda 
(evergreen conifer)
1.21 1.55
 

 [Source: Walker, A.P., De Kauwe, M.G., Medlyn, B.E., et al., 2019. Decadal biomass
increment in early secondary succession woody ecosystems is increased by CO2 enrichment.
Nature Communications, [e-journal] 10, 454. https://doi.org/10.1038/s41467-019-08348-1.
Open access.]

(e)

State the effect of elevated CO2 on net primary production in these young, developing forests.

[1]

Markscheme

increases it/higher (maximum annual net primary production);

The answer must be referring implicitly or explicitly to NPP. 

(f)

Outline one benefit of conducting similar FACE experiments in multiple locations.

[1]

Markscheme

check whether trend is confirmed/replicated/not specific to some forests
OR
investigate worldwide effects (of rising carbon dioxide)
OR
(check whether results are affected by) differences in tree species/types of tree/soil types/rainfall/temperature/climate/latitudes/conditions/biome/ecosystem;

Reject general answers about reliability or anomalies.

In each forest, there are two or three trial plots per CO2 treatment. The bar chart shows the allocation of carbon from net primary production to different parts of the trees in these trial plots.

[Source: Walker, A.P., De Kauwe, M.G., Medlyn, B.E., et al., 2019. Decadal biomass increment
in early secondary succession woody ecosystems is increased by CO2 enrichment.
Nature Communications
, [e-journal] 10, 454. https://doi.org/10.1038/s41467-019-08348-1.

Open access.]

(g)

Evaluate the evidence from the bar chart that increases in carbon dioxide cause increases in carbon storage in young, developing forests.

[3]

Markscheme
  1. more carbon stored/allocated (by the tree as a whole) with elevated carbon dioxide;
  2. evidence (from the bar chart) is strong (for the trend/hypothesis);
  3. all elevated plots have more carbon stored than all ambient plots in all sites/no overlap;
  4. more/most carbon allocated to wood (in stems and roots) with elevated carbon dioxide;
  5. more carbon allocated to narrow roots/leaves with elevated carbon dioxide;
  6. narrow roots increase most in Oak Ridge;
  7. most increase in wood (in stems and roots) in Rhinelander and Duke;
  8. much/more variation between plots at Oak Ridge (than at Rhinelander and Duke);
  9. no error bars so significance of differences is uncertain;

Accept mpd and mpe if the answer refers only to Rhinelander and Duke.

Allow mph if the answer describes an anomaly at Oak Ridge that does not follow the trend seen in Rhinelander and Duke.