The Economics of Desertification, Land Degradation, and Drought

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Figure 2.12—Areas affected by human-induced land degradation measured by a declining NDVI (Change in NDVI from 1982–2003 with a three-year base- and endline) Source: Vlek, Le, and Tamene 2010. To analyze the role of population as a factor influencing land degradation, the authors used three classes of population density: low, high, and very high. Consistent with Bai et al (2008b), Vlek, Le, and Tamene (2010) found low population densities in areas most affected by degradation. These areas may constitute marginal or fragile lands with limited carrying capacity. In addition, in some areas, high population densities are associated with land degradation on probably more fertile lands. Examples of such areas are the densely populated areas in western Africa—especially the humid southwestern areas. In those areas, degradation problems could be addressed by improved access to fertilizer and erosion control measures. The authors also used FAO soil classes to assess whether soil and terrain constraints affect NDVI decline; they observed that 30 percent of the degraded areas relate to unsuitable agricultural soils. In addition, information on land use can help explain the human impact by the land use type of the degraded land. Finally, the authors analyzed the pressure of anthropogenic activities on land using Human Appropriation of Net Primary Production (HANPP), which is the amount of NPP used by humans (for example, for harvested crops). The higher the HANPP (expressed as a percentage of NPP), the greater the human consumption or appropriation. For Sub-Saharan Africa, the average HANPP suggests a light human impact, though there is wide variability across countries. High values of HANPP are associated with areas known for food insecurity and may also reveal areas with future insecurity. This finding is consistent with Bai et al. (2008b), who observed a positive correlation between land degradation and poverty. However, Bai et al (2008b) admitted that this study can only be seen as a way to locate global hot spots that appear to be threatened by human-induced land degradation; further verification and analysis in the field would be needed. The coarse resolution of 8 kilometers may also hide improvement or degradation; finer resolution is required to give better estimates. This study is also only limited to Sub-Saharan Africa; future studies should provide analysis in other regions of the world. 26
Global Land Degradation Information System (2010) The Global Land Degradation Information System (GLADIS), published as a Beta Version in June 2010, will be the final product of LADA. It is based on the ecosystem approach and combines preexisting and newly developed global databases to inform decisionmakers on all aspects of land degradation at this scale (Nachtergaele et al. 2010). GLADIS provides a range of maps on the status and trends of the main ecosystem services, supplemented with maps and databases on the physical and socioeconomic parameters (Nachtergaele et al. 2010). Land degradation was perceived as a complex process, the assessment of which must address more than only biophysical indicators with more than only one method. GLADA mainly used remote sensing—in particular, NDVI—for land degradation monitoring on a global scale. GLADIS is based on six axes for biomass, soil, water, biodiversity, economics, social indicators, and cultural indicators. It aims to capture the present status of land resources, as well as the degradation processes acting on them. According to Nachtergaele et al. (2010), the status of the ecosystem’s provisioning capacity is as important as its decline. Therefore, the degradation and improvement of ecosystem services are presented in GLADIS. The WebGIS of GLADIS 11 is divided into four sections (Land Use Systems, Database, Analysis and Land Degradation Index). The Land Use Systems of the World map (see Appendix B, Figure B.1) contains about 40 different classes that give information about land cover, 12 livestock density, and management (irrigation, protected, unmanaged, no use). The second section— Database—gives an overview of the input of the six axes, which are listed in Figure 2.13. Figure 2.13—The six axes of GLADIS: Four biophysical axes (light gray) and two socioeconomic axes (dark gray) Source: Nachtergaele et al. 2010. The Analysis section shows ecosystem status, which corresponds to its actual degraded status, and ecosystem processes and trends for each axis. The status gives a summarized picture of the different input variables, whereas the trend combines two datasets from either two years or a time series (as used for the Greenness Trend, in which the NDVI time series of the GLADA approach [extended to 2006] was incorporated). In addition to information on land use, the degradation process and pixel- and country-level trends are shown. Regarding the land degradation process, a margin of 0– 50 shows land degradation, whereas a margin of 50–100 shows the improvement of ecosystem conditions. Within the land degradation status maps, the status itself is described with a margin of 0 (worst) to 100 (best). 13 The final section shows the Land Degradation Index—or the simplified 11 Link to GLADIS WebGIS: http://www.fao.org/nr/lada/index.php?option=com_content&view=article&id=180&Itemid=168&lang=en 12 Forest, agriculture, grassland, shrubs, rainfed crops, crops, wetlands, urban, sparse vegetated areas, bare areas, open water, no data 13 Although this feature seems to be interesting, it is not applicable to the national level, as determined by GLADIS itself, with a “warning to the users of GLADIS” occurring on the LADA website in October 2010. Therefore, unfortunately, this feature is useless. 27
Page 1 and 2: IFPRI Discussion Paper 01086 May 20
Page 3 and 4: Contents Abstract vii Acknowledgmen
Page 5 and 6: List of Figures 1.1—Conceptual fr
Page 7 and 8: ABSTRACT Attention to land degradat
Page 9 and 10: 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 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 62 and 63: Results Correlation Analysis Consis
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
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governing land use patterns (Leeman
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promotion of community forest manag
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Box 4.3—Reducing emissions from d
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Soil Nutrient Depletion Soil nutrie
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that the yields of salt-tolerant wh
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Figure 5.3—Forest area as a perce
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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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Page 152 and 153:
Page 154 and 155:
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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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