The Economics of Desertification, Land Degradation, and Drought

More documents

Recommendations

Info

Table A.1—Land degradation assessments on the national level Author Region Methods Used APPENDIX A: SUPPLEMENTARY TABLES Meadows and Hoffman 2003 South Africa Modeling of the potential impact of future climate changes on the nature and extent of land degradation in South Africa. The Climate System Model gave information on the interlinking of climate conditions and land degradation. Future climate change is a key challenge for developing economies of countries like South Africa Sonneveld 2003 Ethiopia Uses expert opinion to conduct a nationwide water erosion hazard assessment in Ethiopia. Symeonakis and Drake 2004 Sub-Saharan Africa The desertification monitoring system consists of four indicators: NDVI, rainfall use efficiency (RUE), surface runoff (using the Soil Conservation Service), and soil erosion (using a model parameterized by overland flow, vegetation cover, the digital soil maps, and a digital elevation model), calculated for 1996. Klintenberg and Seely 2004 Namibia Four primary indicators for Land Degradation Monitoring in Namibia: population pressure (population density), livestock pressure (distribution of boreholes and annual numbers of livestock), rainfall (index based on rainfall records), and erosion risk (based on gradient and soil characteristics for agroecological zones); 1971–1997 Foster 2006 Botswana Using main methodologies for assessing land degradation in Botswana: Global Assessment of Human-Induced Land Degradation (GLASOD); remotely sensed images showing bush encroachment from 1997 and vegetation distribution in 1971 and 1994; agricultural productivity trends by region for 1980–1998; participatory studies from two degradation hot spots in Botswana; average annual rainfall for 1986–2000 Prince, Becker-Reshef, and Rishmawi 2009 Wessels et al. 2007 South Africa (and Limpopo) Zimbabwe Local Net Production Scaling information on land cover, precipitation (from the U.S. National Oceanic and Atmospheric Association, or NOAA), soil (Soil and Terrain Digital Database, or SOTER, and Zimbabwe soil map); net primary production (NPP) and Normalized Differenced Vegetation Index (NDVI) data from moderate resolution imaging spectroradiometer (MODIS) Advanced very high resolution radiometer (AVHRR), NDVI, and modeled NPP were used to estimate vegetation production in South Africa. Human-induced signals were separated from natural land degradation by the use of RUE and residual trend (RESTREND). Source: Author’s compilation. Note: Local Net Production Scaling is the estimated potential production in homogeneous land capability classes. It models the actual productivity using remotely sensed observations. 132
Table A.2—Land degradation assessment on the local and subnational levels Author Region Methods Used Hill, Mégier, and Mehl 1995 Mediterranean ecosystems (test sites in the south of France and Greece) Vegetation indexes Normalized Differenced Vegetation Index (NDVI), airborne imaging spectrometry, change detection with Landsat Thematic Mapper (TM) data, soil conditions Hill et al. 1998 Greece, Crete Long-term series of Landsat TM images (between 1984 and 1996), conversion into geographic information system (GIS) layers Collado, Chuvieco, and Camarasa 2000 Diouf and Lambin 2001 Gao, Zha, and Ni 2001 Evans and Geerken 2004 Herrmann, Anyamba, and Tucker 2005 Kiunsi and Meadows 2006 Hein and de Ridder 2006 Argentina—San Luis Province Comparing two Landsat images for 1982 (a more arid period) and 1992 (a humid period) of the area; difference picture of two Landsat images; Monitoring of the following: - enlargement of water bodies - increasing soil degradation because of increased grazing pressure - invasion of alien species while other palatable species disappear - displacement of sand dunes (using albedo monitoring )a - Senegal—Region Ferlo Assess land cover modifications in Ferlo with rainfall data and rainfall use efficiency (RUE), advanced very high resolution radiometer (AVHRR), NDVI, data on soil types, changes in floristic composition, analysis of the resilience after drought China—Yulin, Shaanxi provinces Aerial photographs, one Landsat TM image and GIS; trend of desertification between 1960 and 1987 is modeled from changes in other land covers Syria Distinguish between climate- and human-induced dryland degradation based on evaluations of AVHRR, NDVI data, and rainfall data Africa—Sahel Investigation of temporal and spatial patterns of vegetation greenness and rainfall variability and their interrelationship, based on NDVI time series for 1982–2003 and gridded satellite rainfall estimates. Tanzania—Monduli District, (Northern Tanzania) Three sets of land cover maps synchronized against long-term rainfall data (1960s, 1991, and 1999). The change detection, based on the land cover map set, gives information on changes in vegetation due to rainfall, which could be separated from changes in vegetation that occurred due to human impact. Africa—Sahel Critical assessment of desertification by the use of RUE. Variability of RUE for the analysis of remote sensing imagery of semiarid rangelands with regard to natural and human-induced degradation of Sahelian vegetation cover. Lu et al. 2007 Brazil—Western Brazilian Amazon Mapping and monitoring of land use and land cover changes by the use of remote sensing (Landsat TM/ETM+ images). A surface cover index is developed to evaluate and map potential land degradation risks associated with deforestation and accompanying soil erosion in the rural settlements of the study area. 133
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 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
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
Page 112 and 113: Introduction 6. CASE STUDIES Five c
Page 114 and 115: Salinity The effects of salinity on
Page 116 and 117: Third, to correctly decide which ac
Page 118 and 119: Costs of Action and Inaction We eva
Page 120 and 121: The NGOs and religious organization
Page 122 and 123: have a strong influence on NRM (And
Page 124 and 125: We estimated the cost of action (de
Page 126 and 127: Figure 6.15—Costs of action and i
Page 128 and 129: Of interest to us is the strategy t
Page 130 and 131: 7. PARTNERSHIP CONCEPT The review o
Page 132 and 133: degradation. All this should be don
Page 134 and 135: Finally, the global assessment of D
Page 136 and 137: the experience of and lessons learn
Page 138 and 139: Table 7.3—Example of E-DLDD resea
Page 140 and 141: 8. CONCLUSIONS Since the publicatio
Page 142 and 143: lowest in the region. From a socioe
Page 146 and 147: Table A.2—Continued Author Region
Page 148 and 149: Table A.3—Continued Author Countr
Page 156 and 157: Table A.5—Costs of land degradati
Page 158 and 159: Figure B.1—Land use systems of th
Page 160 and 161: REFERENCES Abelson, P. 1979. Cost B
Page 162 and 163: Benin S., E. Nkonya, G. Okecho, J.
Page 164 and 165: Clark, E. H. 1985. The Off-Site Cos
Page 166 and 167: De Jager a., D. Onduru and C. Walag
Page 168 and 169: Foster, V., and C. Briceño-Garmend
Page 170 and 171: Holden, S. and H. Lofgren. 2005. As
Page 172 and 173: Lapar, M. L., and S. Pandey. 1999.
Page 174 and 175: Nachtergaele, F., M. Petri, R. Bian
Page 176 and 177: Pender, J. L. 2009. “Food Crisis
Page 178 and 179: Sauer, J., and H. Tchale. 2006. Alt
Page 180 and 181: Tan, Z. X., R. Lal, and K. D. Wiebe
Page 182 and 183: ———. 2010. “Assessment of L
Page 187 and 188: RECENT IFPRI DISCUSSION PAPERS For
show all

The Economics of Desertification, Land Degradation, and Drought

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?