Scenarios

Five scenarios are defined:

• Climate conditions as predicted for the year 2020 (stylised representation of a typical environmental driving force).

• Increase in total food energy demand by 10% (stylised representation of an increase in food exports driven by increased global food demand).

• Decrease in meat energy demand by 10% (stylised representation of a change in lifestyles towards more vegetarian diets).

• Decrease in available crop land by 10% (stylised representation of increased demand for land for non-food purposes, e.g. bio-fuel production).

• Joint scenario - all 4 previous scenarios combined.

For our sample region Germany we have restricted our set of relevant cropping activities in MAgPIE to 5 crop types (food grains, feed grains, oil crops (i.e. rapeseed), sugar crops (i.e. sugar beets), and green fodder (i.e. silage maize)). According to FAO statistics these crop types currently account for about 87% of total crop land in Germany.

In Step (1) of our analysis we run LPJ for a selection of 185 grid cells covering Germany, with all CFTs separately in order to define potential yields for each grid cell. We do this twice, once with the average climate for the years 1991-2000 and once with a climate scenario for the average in years 2011-2020, taken from the ECHAM4 model.12 Figure 7.1 shows yield distributions for the CFT 'temperate cereals' (i.e. wheat) in 2000. The map reveals significant variation in yields across the region. However, yields seem to depend too strongly

12 ECHAM = European Centre for Medium-Range Weather Forecasts model, Hamburg version. For more information on ECHAM4 and other climate model scenarios see: http://ipcc-ddc.cru.uea.ac.uk/dkrz/dkrz_index.html.

on precipitation and less on soil conditions. This is partly to be explained by the rather crude soil classification in the global FAO soil data set used in LPJ.

Temperate cereal yields 1991-2000

Temperate cereal yields 1991-2000

Figure 7.1 Regional distribution of cereal yields in Germany in 2000 (tonnes dry matter/ha; own calculations with LPJ)

Figure 7.1 Regional distribution of cereal yields in Germany in 2000 (tonnes dry matter/ha; own calculations with LPJ)

In Step (2) we use normalised yields of all CFTs in order to define 6 productivity zones. These can be roughly characterised by high, medium and low cereal yields in combination with high and low silage maize yields. Due to different climate conditions and yields, the spatial distribution of zones varies considerably between both years. Table 7.5 shows average yields for the 5 cropping activities in different zones as calculated in LPJ. A comparison with official FAO statistics on crop yields for Germany shows that LPJ currently overestimates yields in cereals and oil crops, while sugar beet yields are underestimated.

Table 7.5 Characteristics of productivity zones under different climate conditions

Zone Share of

Precipitation

Yield (ton/ha)

regional crop land (%)

(mm/year)

Cereals

Sugar beet Rapeseed

Silage

maize

Climate 2000

1 9

953

9.7

43.0

6.1

34.1

2 7

1016

9.9

32.0

5.7

23.0

3 19

755

8.7

42.1

5.5

32.7

4 39

691

8.6

35.4

5.4

25.6

5 4

653

7.8

39.3

5.0

31.9

6 22

593

7.8

36.0

4.9

26.3

Climate 2020

1 3

967

10.8

49.7

6.7

36.1

2 2

1305

12.1

34.4

6.4

5.8

3 24

737

8.9

46.2

5.6

34.2

4 18

632

8.3

41.6

5.2

29.0

5 1

627

7.7

42.8

4.8

31.9

6 52

552

7.0

35.6

4.4

26.1

Source: Own calculations (LPJ), ECHAM4 climate scenario.

Source: Own calculations (LPJ), ECHAM4 climate scenario.

In Step (3) of our analysis these characteristics of zones and yields are imposed on the production activities in MAgPIE, and in Step (4) agricultural production and resource use are optimised for Germany.

Total food energy demand for Germany is calculated by multiplying a population of 82 million by an average daily food availability of 3,411 kcal or 14,272 MJ (according to the FAO food balance sheets). Note that this is not strictly food consumption, but rather food availability for consumption. More precise data on effective food intake are not available. The shares of total food energy consumption are 69 % for plant-based energy, 17% for meat-based energy, and 14% for milk-based energy.

With the current specification of MAgPIE, in the reference situation total food demand in Germany can be met, in fact the self-sufficiency ratio is about 110%. Under these conditions the optimal solution for the model leaves about 10% of the crop land and 9% of the pasture unused. The resulting average land use shares for the whole region in all scenarios are shown in Table 7.6. To illustrate the variation in land use patterns among the zones, Table 7.7 shows the shares for all zones in scenario (b).

As a further important economic output of our modelling exercise we show calculated shadow prices for the combined Scenario (e) in Table 7.8. The results show considerable variation between zones, as e.g. crop land and pasture are

Table 7.6 Average land use shares for Germany under various scenarios (%)

(reference)

(a)

(b)

(c)

(d)

(e)

Description .

Year 2000 Climate

Demand

Reduced

Reduced

Combined

2020

increase

meat

crop land

scenario

Bread grain

16

11

11

21

11

13

Feed grain

50

53

55

45

55

52

Rapeseed

14

15

19

9

22

18

Sugar beet

0

0

3

0

1

0

Silage maize

10

11

12

10

11

12

Unused crop

land

10

9

0

15

0

5

Unused pasture

9

1

4

9

10

1

Source: Own calculations (MAgPIE).

Source: Own calculations (MAgPIE).

Table 7.7 Land use shares (%) in all zones in Scenario (b) (demand increase by

Description _Zone_

Table 7.7 Land use shares (%) in all zones in Scenario (b) (demand increase by

Description _Zone_

1

2

3

4

5

6

Bread grain

66

66

3

0

0

0

Feed grain

0

0

63

66

66

66

Rapeseed

14

9

16

22

0

26

Sugar beet

0

0

8

0

24

0

Silage maize

20

25

10

12

10

8

Unused crop land

0

0

0

0

0

0

Unused pasture

0

55

0

0

0

0

Source: Own calculations (MAgPIE).

Table 7.8 Zone-specific shadow prices in Combined Scenario (e)

Constraint

Zone

1

2

3

4

5

6

Green fodder balance

-14

-127

-12

-14

-11

-13

Crop land

-612

-1,288

-319

-213

-106

0

Pasture

-2,800

0

-2,848

-2,819

-2,875

-2,841

Rotation cereals

-291

0

-319

-310

-301

-272

Water

0

0

0

0

0

0

Source: Own calculations (MAgPIE).

Source: Own calculations (MAgPIE).

scarce in some zones, but not in all. Water is not a binding constraint in any zone, i.e. the shadow price is always zero. The rotational constraint on cereals is binding in all zones, except zone 2, which is, however, rather small in this scenario.

In Step (5) of the analysis the land use patterns for each zone are implemented in LPJ and in Step (6) the impacts on net primary production (NPP), carbon and water balances are calculated. Figure 7.2 shows the difference in NPP in scenario (e) compared to the reference situation in 2000. In this case the differences are mainly due to changes in climate conditions.

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