Agriculture Reference
In-Depth Information
services such as loss of medicinal plants and timber, regulating services, and sup-
porting services.
9.4 DRIVERS OF LAND DEGRADATION
The discussion below is based on the model that simultaneously controls all major
drivers. Hence, the results derive stronger correlation between land degradation/
improvement and its drivers than the simple correlations discussed above using
maps and descriptive statistics. As emphasized above, however, these results
should not be interpreted as causality but rather as only correlations between the
land degradation/improvement and its drivers. The focus of the discussion is on
the direction of relationship and their statistical significance rather than the mag-
nitude of the coefficients. Hence, Table 9.3 reports only the direction of the rela-
tionship (positive or negative) and the statistical significance of the coefficients.
We focus on the underlying drivers of land degradation from which we can draw
policy implications for actions against land degradation. We also discuss agricul-
TABLE 9.3
Regression Analysis on Association of Change in NDVI and Major Drivers of
Land Degradation, 1981-2006
East
Asia
European
Union
South
Asia
Global
LAC
MENA
SSA
Variable
A
S
A
S
A
S
A
S
A
S
A
S
A
S
Δ Population
density
+
NS
+
*
-
*
-
NS
+
*
-
**
-
***
Δ Precipitation
+
*
+
NS
+
**
+
*
+
*
+
*
+
***
Δ Agricultural
intensification
+
*
+
NS
+
***
+
*
-
*
+
*
+
NS
Δ GDP
-
*
+
***
-
**
-
*
-
*
+
*
+
***
Δ GDP
2
+
*
-
**
+
NS
+
*
+
*
-
NS
-
***
Δ Government
effectiveness
+
*
-
NS
+
*
+
*
+
*
-
+
***
Source:
Modified from Nkonya, E. et al. The Economics of Land Degradation. Toward An Integrated
Global Assessment, Peter Lang, Berlin, 2011.
Notes:
+ and - respectively mean positive and negative relationship of change of the NDVI and driver of
land degradation. A = association of change of NDVI with associated variable; S = statistical sig-
nificance of association: NS = not significant (at
p
= 0.10) and *,**,***, respectively, mean signifi-
cant at 0.10, 0.05, and 0.01. LAC = Latin American countries; MENA = Middle East and North
Africa; SSA = sub-Saharan Africa; Δ = change end line period - baseline period. Since GDP and
agricultural intensification (fertilizer application per hectare) were at a country level, it was not
possible to run regional level regression in the Oceania and North America regions—both of which
have few countries.
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