The Economics of Desertification, Land Degradation, and Drought

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Table 2.3—Continued Project and duration GLADA (2000–2008) MA (2005) GLADIS (2010) What is monitored? Techniques used and strength(s) Soil degradation, Remote sensing (GIMMS vegetation dataset of 8-km-resolution NDVI degradation, national data); input of SOTER in assessment (LADA), support of general NDVI global assessment of methodology. Based on degradation and quantitative satellite data; not improvement on expert opinion; correlation of (GLADA); over a land degradation with certain period (1981– 2003, extended to 2006) socioeconomic data Drylands (62% of 14 studies (global, regional, and global drylands) subregional); based on remote sensing and other data sources, with georeferenced results compiled into a map with grid cells of 10 x 10 km 2 Mapping of the status of LD and pressures applied to ecosystem goods and services by using six axes of biophysical and socioeconomic determinants (biomass, soil, water, biodiversity, economics, and social) Remote sensing, GIS, (LADA database); Modeling; “Spider diagram approach;” integration of more than population data in socioeconomic determinants; broad analysis of the process of land degradation Extent/severity of land degradation 24% of the land area was degraded between 1981 and 2003 (80% of the degraded area occurred in humid areas). Relationship: LD and poverty: 42% of the very poor live in degraded land, 32% of the moderately poor, and 15% of the nonpoor. 36 Scale/ resolution of maps Grid cells of 32 km² Data for 1981–2003 (extended to 2006) LADA: 1:500,000– 1:1 million Grid cells of 100 km² Data within the 1980–2000 period 5 arc minute (corresponds to 9 km x 9 km) Limitations End product Primarily monitoring of land cover; analyzing trends—lack of information on the present state; degradation before 1981 and in areas where visible indicators could not be monitored yet were not included Different studies used for MA with different definitions of LD and different time periods of assessment; no economic assessment of ecosystems Combining national and subnational data, taking into account different periods of the different inputs; lumping of many indicators loses focus and attribution Identifying hot spots of degrading and improving areas Global GIS database for 62% of all drylands and hyperarid areas of the world Global Land Degradation Information System; Provision of general data and analysis on LD due to a WebGIS Sources: Oldeman, Hakkeling, and Sombroek 1991b; Oldeman 1998; Thomas and Middleton 1994; Van Lynden, Liniger, and Schwilch 2002; MA 2005; Bai et al. 2008b; Nachtergaele et al. 2010. Notes: LD = land degradation; SLM = sustainable land management; GIMMS = Global Inventory Modeling and Mapping Studies; CBD = Convention on Biological Diversity; BIP = Biodiversity Indicators Partnership.
Drought Drought episodes have been increasing over time in the drier areas of the world. Kemp (1994) stated that drought is a rather imprecise term dealing with moisture deficiency in terms of its impact on human activities. Drought describes a naturally occurring phenomenon in which precipitation is significantly below normal recorded levels, which have been established through long-term observations. Droughts are generally considered a temporary event (Kemp 1994). From an agricultural and economic viewpoint, a drought is characterized as adversely affecting land resource production systems (Akhtar-Schuster, Bigas, and Thomas 2010) by leading to reduced crop yields or even crop failure. In accordance with that characterization, UNCCD defines drought as “the naturally occurring phenomenon that exists when precipitation has been significantly below normal recorded levels, causing serious hydrological imbalances that adversely affect land resource production systems” (UNCCD, 1996, Part1, Article 1c). From a natural science point of view, drought is defined as a period of duration D (months) with a soil moisture quantile value q(θ) less than an arbitrary threshold level q0(θ) that is preceded and followed by a value above this level. The departure below this level at any particular time is the drought magnitude: M = q0(θ) – q(θ). The mean magnitude over the drought duration is the intensity. A recent study showed that there is increasing wetness globally but with contrasting regional differences (Table 2.4). From 1950 to 2000, North America showed increased wetness, whereas Europe and southern and southeastern Asia did not experience significant changes. On the other hand, drought spatial extent has increased in the drier areas of western Africa. However, other studies have shown that the regreening of the Sahelian region was due to the recovery from the great Sahelian droughts that affected the region in the 1970s and 1980s (Herrmann, Anyamba, and Tucker 2005). The general circulation models (GCMs) have generally predicted that wet areas and those in high latitudes will experience wetter conditions, whereas drier areas will experience drier and more frequent droughts (Cline 2007; Christensen et al. 2007). The severity and frequency of droughts, heat waves, and floods in most Sub-Saharan African countries are also expected to increase, resulting in significant impacts on natural resources (Christensen et al. 2007). The Hadley Center predicts an increase in the global area expected to experience severe drought at any point in time from 10 percent of the world’s land surface in 2005 to 40 percent in the future, for a given global warming of 3–4 degrees Celsius (Stern 2006). Frequencies of droughts are also expected to increase. Table 2.5 shows the change in four regions in which drought frequency is expected to increase in the year 2030, with a 0.2 degree Celsius increase each decade from 2009 to 2030. Assuming low-, medium-, and high-impact scenarios, Webster et al. (2008) predicted that drought frequency will increase by 10 percent in southeastern and southern Asia and by 20 percent in East Africa and Central America from their levels during the baseline period of 1992–2008. As noted earlier, drought will be more frequent in drier areas. Table 2.4—Trends in the spatial extent of drought for various baseline values Location 10 20 30 40 50 World -0.021 - 0.032 - 0.035 - 0.027 - 0.021 Europe Northern Europe - 0.102 - 0.143 - 0.139 - 0.139 -0.140 Mediterranean 0.014 0.022 0.022 0.026 0.022 Africa West Africa 0.068 0.179 0.319 0.435 0.527 East Africa 0.029 0.064 0.088 0.117 0.154 Southern Africa 0.038 0.09 0.15 0.203 0.234 North Asia Northern Asia 0.055 0.102 0.129 0.139 0.14 Central Asia -0.049 -0.098 - 0.151 - 0.176 - 0.203 37
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 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 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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RECENT IFPRI DISCUSSION PAPERS For
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