Figure 6-4: Global land-use
patterns, shares (%) of croplands and energy biomass, forests, and other
categories including grasslands - historical development from 1970 to
1990 (based on B1-IMAGE) and in SRES scenarios. As for the energy triangle
in Figure 6-3, each corner corresponds to a hypothetical situation in
which land use is dedicated to a much greater extent than today to one
category - 60% to cropland and energy biomass at the top, 80% to forests
to the left, and 80% to other categories (including grasslands) to the
right. Constant shares in total land area of cropland and energy biomass,
forests, and other categories are denoted by their respective isoshare
lines. For 1990 to 2100, alternative trajectories are shown for the
SRES scenarios. The three marker scenarios A1B, B1, and B2 are shown
as thick colored lines, and other SRES scenarios as thin colored lines.
The ASF model used to develop the A2 marker scenario projects only land-use
change related GHG emissions. Comparable data on land cover changes
are therefore not available.The trajectories appear to be largely model
specific and illustrate the different views and interpretations of future
land-use patterns across the scenarios (e.g. the scenario trajectories
on the right that illustrate larger increases in grasslands and decreases
in cropland are MiniCAM results).
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6.2.3.2. Land-use Patterns
Figure 6-4 illustrates that the land-use patterns diverge
over time. It shows the main land-use categories - the percentages of total
land area use that constitute the forests, the joint shares of cropland and
energy biomass, and all other categories including grasslands. As for the energy
triangle in Figure 6-3, in Figure
6-4 each corner corresponds to a hypothetical situation in which land use
is dedicated to a much greater extent than today to two of the three land-use
categories: 40% to cropland and energy biomass and 20% to forests at the top,
60% to forests and 40% to other categories (including grasslands) to the left,
and 80% to other categories (including grasslands) to the right.
In most scenarios, the current trend of shrinking forests is eventually reversed
because of slower population growth and increased agricultural productivity.
Reversals of deforestation trends are strongest in the B1 and A1 families. In
the B1 family pasture lands decrease significantly because of increased productivity
in livestock management and dietary shifts away from meat, thus illustrating
the importance of both technological and social developments.
The main driving forces for land-use changes are related to increasing demands
for food because of a growing population and changing diets. In addition, numerous
other social, economic, and institutional factors govern land-use changes such
as deforestation, expansion of cropland areas, or their reconversion back to
forest cover (see Chapter 3). Global food production can
be increased, either through intensification (by multi-cropping, raising cropping
intensity, applying fertilizers, new seeds, improved farming technology) or
through land expansion (cultivating land, converting forests). Especially in
developing countries, there are many examples of the potential to intensify
food production in a more or less ecologic way (e.g. multi-cropping; agroforestry)
that may not lead to higher GHG emissions.
Different assumptions on these processes translate into alternative scenarios
of future land-use changes and GHG emissions, most notably C2, CH4
and N2O. A distinguishing characteristic of several
models (e.g., AIM, IMAGE, MARIA, and MiniCAM) used in SRES is the explicit modeling
of land-use changes caused by expanding biomass uses and hence exploration of
possible land-use conflicts between energy and agricultural sectors. The corresponding
scenarios of land-use changes are illustrated in Figure 6-4
for all SRES scenarios. In some contrast to the structural changes in energy
systems shown in Figure 6-3, different land-use
scenarios in Figure 6-4 appear to be rather model specific,
following the general trends as indicated by the respective marker scenario
developed with a particular model.
