The Economics of Desertification, Land Degradation, and Drought

Figure 2.6—Areas most affected by land degradation, GLADA, 1981–2003
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18
16
14
12
10
8
6
4
2
0
13
18
Africa - south
of equator
Source: Compiled from Bai et al. 2008b.
6
14
Indo-China,
Mynmar &
Indonesia
% of global area degraded
% of global NPP lost
5 5 5
South China Australia The Pampas
The relationship between aridity and land degradation, measured as a decrease in NDVI, was
negative at global level, suggesting that the extent and severity of land degradation was more severe
in humid and subhumid areas than in semiarid, arid, and superarid areas. This finding is contrary to
conventional wisdom, which states that drylands are more degraded than humid areas. Unfortunately,
Bai et al. (2008b) did not offer an explanation for this finding. Wessels (2009) argued that the
negative trends might rather be due to management practices, such as logging and crop rotation, than
to land degradation; hence, the results require analysis of the causes of land degradation.
The GLADA study examined the relationship between land degradation and poverty and
population density. Although causal relationships cannot be derived from this approach, the results
challenge conventional wisdom, pointing out greater land degradation in areas with high population
density, though it must be stressed that land degradation was measured as changes in NDVI or NPP
indicators. The GLADA study observed a negative relationship between population density and land
degradation, supporting studies that observed the phenomenon of “more people less erosion” (Tiffen,
Mortimore, and Gichuki 1994; Vlek, Le, and Tamene 2008). Vlek, Le, and Tamene (2008) offered as
an explanation that these areas may constitute marginal lands with low carrying capacity, which can
easily be overpopulated. The GLADA study also observed a positive correlation between poverty
measured as a proportion of mortality rate of children under five years old and land degradation,
supporting other studies that observed a vicious cycle of poverty and land degradation (Way 2006).
Tree planting in Europe and North America and land reclamation in northern China increased
the NDVI. Woodland and bush encroachment into rangeland and farmland also increased,
contributing to a positive NDVI trend. Overall, land area improvement accounts for 16 percent, with
rangelands contributing 43 percent of the improvement and with forests and crop areas contributing
23 percent and 18 percent, respectively. However, the increase of NDVI was not attributed to
atmospheric fertilization, which describes the rising carbon dioxide levels of the atmosphere and the
corresponding vegetation growth and which might, hence, be overestimated.
Weaknesses of the GLADA study, as acknowledged by the authors, include the usage of stillcoarse
data of 8 kilometers. The validation of the global assessments based on field-level observations
in several countries often contradicted the GLADA results (for example, in South Africa, only 50
percent of the global predictions was correct). NDVI as an indicator of land degradation has
shortcomings, as vegetation depends on several factors—not just the degradation status of the land.
Wessels (2009) criticized the summation of NDVI over calendar years instead of summing over the
vegetation period. The GLADA study also shows degradation in areas where there is sparse
population density. For example, Gabon and Congo show the most severe land degradation (Figure
2.7), but population density in these two countries is among the lowest in Sub-Saharan Africa. 10
10 The population densities of Gabon and Congo are, respectively, 6 persons per square kilometer and 12 persons per
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4
4
3
.