The Economics of Desertification, Land Degradation, and Drought

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Results Correlation Analysis Consistent with past studies (for example, Grepperud 1996), Table 2.8 shows a negative correlation between change in population density and NDVI in all regions except Sub-Saharan Africa (SSA), the European Union (EU), and Near East and North Africa (NENA). This is contrary to Bai et al. (2008), who observed a positive correlation between NDVI and population density on a global scale. Consistent with Bai et al. (2008b), however, population density was positively correlated with NDVI in the SSA, EU, and NENA regions. In SSA, population density is highest in the most fertile areas, such as mountain slopes (Voortman, Sonneveld, and Keyzer 2000). This leads to the positive correlation between NDVI and population density even in areas south of the equator, which have seen severe land degradation (Bai et al. 2008b). Figure 2.20 also shows that there was a positive correlation between population density and NDVI in central Africa, India, North America, and Europe. We also see an increase in NDVI accompanied with negative population density in Russia (Figure 2.20). Our results show that in all regions, GDP changes are positively correlated with NDVI changes (Table 2.8). Figure 2.21 also shows an increase of both GDP and NDVI in North America, Russia, India, central Africa (north of the equator), and China. This suggests the role ecosystems could play in economic growth. Table 2.8—Correlation of NDVI with selected biophysical and socio-economic factors Variable East Asia European Union Latin American Countries Near East and North Africa 50 North America Oceania South Asia Sub Saharan Africa Δ Population density -0.03* 0.002 -0.01* 0.04* -0.01* -0.01* -0.02* 0.01* Δ Precipitation -0.02* -0.04* 0.17* 0.23* -0.01* 0.09* 0.24* 0.13* Δ Agricultural intensification 0.06* -0.01* 0.20* 0.01* -0.14* -0.10* 0.14* -0.01* Δ GDP 0.06* 0.17* 0.03* 0.28* 0.14* 0.10* 0.21* 0.09* Δ Government effectiveness 0.09* -0.04* 0.24* 0.23* -0.14* 0.10* 0.08* 0.10* Source: Author’s calculations. Notes: Statistical significance codes: *significant at the 5% level. Δ = Change from end line to baseline period. Figure 2.20—Relationship between change in NDVI and population density Source: Author’s compilation based on simulation results.
Figure 2.21—Relationship between GDP and NDVI Source: Author’s compilation based on simulation results. Consistent with expectations, the correlation analysis showed that in most regions, government effectiveness is positively correlated with NDVI. It was negative only in the EU and North America, which is largely due to a decrease in government effectiveness during the period under review accompanied by an increase in NDVI in both regions (Figure.22). Figure 2.22—Relationship between government effectiveness and NDVI Source: Author’s compilation based on simulation results. With the exception of the EU, North America, Oceania, and SSA, the correlation between agricultural intensification (proxied by fertilizer application) and NDVI is positive as expected (Table 2.8). The EU, North America, and Oceania have seen a decrease in fertilizer application (Figure 2.23), which could explain the apparent negative correlation with NDVI. In SSA, land conversion to agriculture is responsible for the declining NDVI. 51
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IFPRI Discussion Paper 01086 May 20
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Contents Abstract vii Acknowledgmen
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List of Figures 1.1—Conceptual fr
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ABSTRACT Attention to land degradat
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ABBREVIATIONS AND ACRONYMS ADB Asia
Page 11: SCAR Soil Conservation in Agricultu
Page 14 and 15: In the present report, the conceptu
Page 16 and 17: Framework: Confronting Action versu
Page 18 and 19: understand these arrangements in or
Page 20 and 21: Figure 1.3—Prevention, mitigation
Page 22 and 23: on assessments at the micro level (
Page 24 and 25: does not clearly distinguish betwee
Page 26 and 27: Figure 2.1—GLASOD (1991) global a
Page 28 and 29: International Earth Science Informa
Page 30 and 31: Box 2.1—Continued Normalized Diff
Page 32 and 33: Figure 2.4—Loss of annual NPP, GL
Page 34 and 35: Figure 2.7—Annual loss of NPP in
Page 36 and 37: Table 2.2—Nitrogen application ra
Page 38 and 39: Figure 2.12—Areas affected by hum
Page 40 and 41: output—which is a selection of su
Page 42 and 43: GLADIS also underlines the linkage
Page 44 and 45: Box 2.2—Continued A map on global
Page 46 and 47: Table 2.3—Global land degradation
Page 48 and 49: Table 2.3—Continued Project and d
Page 50 and 51: Table 2.4—Continued Location 10 2
Page 52 and 53: Table 2.6—Extent and severity of
Page 54 and 55: National Level Policies As discusse
Page 56 and 57: Such support has also been directed
Page 58 and 59: Migration, either as outmigration o
Page 60 and 61: The preceding discussion shows the
Page 64 and 65: Figure 2.23—Relationship between
Page 66 and 67: Effects of Land Degradation On-Site
Page 68 and 69: soils and higher land productivity.
Page 70 and 71: Acknowledging the work of GLADIS, a
Page 72 and 73: health, education, security, enviro
Page 74 and 75: Box 3.1—Recent major economic ass
Page 76 and 77: An appropriate economic tool for a
Page 78 and 79: Figure 3.4—Cost of action and cos
Page 80 and 81: enefit—for example, income. This
Page 82 and 83: Figure 3.6—Ecosystem services fra
Page 84 and 85: Replacement Cost Approaches The rep
Page 86 and 87: Box 3.2—Measuring land degradatio
Page 88 and 89: land degradation and conservation m
Page 90 and 91: Flooding and Aquifer Recharge Richa
Page 92 and 93: year (Diao and Sarpong 2007). Sonne
Page 94 and 95: Bringing together the different cos
Page 96 and 97: This section discusses the most imp
Page 98 and 99: governing land use patterns (Leeman
Page 100 and 101: promotion of community forest manag
Page 102 and 103: Box 4.3—Reducing emissions from d
Page 104 and 105: Soil Nutrient Depletion Soil nutrie
Page 106 and 107: that the yields of salt-tolerant wh
Page 108 and 109: Figure 5.3—Forest area as a perce
Page 110 and 111: Figure 5.5—Per capita water stora
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Introduction 6. CASE STUDIES Five c
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Salinity The effects of salinity on
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Third, to correctly decide which ac
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Costs of Action and Inaction We eva
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The NGOs and religious organization
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have a strong influence on NRM (And
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We estimated the cost of action (de
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Figure 6.15—Costs of action and i
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Of interest to us is the strategy t
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7. PARTNERSHIP CONCEPT The review o
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degradation. All this should be don
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Finally, the global assessment of D
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the experience of and lessons learn
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Table 7.3—Example of E-DLDD resea
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8. CONCLUSIONS Since the publicatio
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lowest in the region. From a socioe
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Table A.1—Land degradation assess
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Table A.2—Continued Author Region
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Table A.3—Continued Author Countr
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Table A.5—Costs of land degradati
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Figure B.1—Land use systems of th
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REFERENCES Abelson, P. 1979. Cost B
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Benin S., E. Nkonya, G. Okecho, J.
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Clark, E. H. 1985. The Off-Site Cos
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De Jager a., D. Onduru and C. Walag
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Foster, V., and C. Briceño-Garmend
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Holden, S. and H. Lofgren. 2005. As
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Lapar, M. L., and S. Pandey. 1999.
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Nachtergaele, F., M. Petri, R. Bian
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Pender, J. L. 2009. “Food Crisis
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Sauer, J., and H. Tchale. 2006. Alt
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Tan, Z. X., R. Lal, and K. D. Wiebe
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———. 2010. “Assessment of L
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RECENT IFPRI DISCUSSION PAPERS For
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The Economics of Desertification, Land Degradation, and Drought

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