Natural Resource Management Indicators for the Least Developed Countries
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1 Natural Resource Management Indicators for the Least Developed Countries Alex de Sherbinin CIESIN, Columbia University 24 June 2005 Millennium Challenge Corporation workshop Brookings Institution Washington, DC
2 Acknowledgements Wildlife Conservation Society Water Systems Analysis Group, University of New Hampshire Center for Tropical Agriculture, The Earth Institute, Columbia University Yale Center for Environmental Law and Policy
3 Sustainable NRM: A Three Legged Stool 1. Biodiversity Conservation 2. Agricultural Sustainability 3. Water Use a focus on outcomes that are affected by policies. Theory: For poor countries, if you get these three right, you are on the route to sustainable natural resource management.
4 Indicator #1: Biodiversity Conservation Indicator: Percentage of wilderness protected per country Input data: Human Footprint Wildness Map World Database of Protected Areas Map Method: Overlay the WPDA on the Human Footprint Wildness Measure the areas protected and unprotected Calculate the percentage of wilderness protected Rationale: There is a large and growing list of biodiversity indicators, but few have any direct connection to policy. Concentrating PAs in the most wild areas maximizes conservation effectiveness.
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8 FY04 Eligible and Threshold Nations CNTRY_NAME %10 > WILDperCNTRY Percent Most Wild in PAs FY2004 ELIGIBLE Mongolia Georgia Armenia Mali Cape Verde Honduras Senegal Nicaragua Benin Ghana Sri Lanka Mozambique Bolivia Madagascar Vanuatu Lesotho THRESHOLD Albania Yemen Uganda Kenya Sao Tome & Principe Tanzania
9 FY05 Eligible and Threshold Nations CNTRY_NAME %10 > WILDperCNTRY Percent Most Wild in PAs FY2005 ELIGIBLE Mongolia Georgia Armenia Morocco Mali Honduras Senegal Nicaragua Benin Ghana Sri Lanka Mozambique Bolivia Madagascar Vanuatu Lesotho THRESHOLD Philippines Yemen Burkina Faso Guyana Uganda Kenya Sao Tome & Princip Tanzania Zambia Malawi Paraguay
10 Indicator #2: Agricultural Sustainability Indicator: Yield changes for subsistence crops Input data: FAO s FAOSTAT Method: Create an index based on changes in the five-year moving average of yields for a basket of subsistence crops such as millet, sorghum, and maize Rationale: Agricultural experts agree that what matters most for small holder agriculturalists is yield changes. A fiveyear moving average smooths some of the effect of rainfall and can help to identify a secular trend in soil fertility.
11 Hg/Ha Maize Yields, (five-year averages) Angola Bangladesh Benin Bhutan Burkina Faso Burundi Cambodia Cape Verde Central African Republic Chad Comoros Congo, Dem Republic of Maize: Cambodia and Bangladesh have dramatically improved; Benin, Burundi and Chad have declined slightly Millet Yields, (five-year averages) Millet: Ethiopia and Chad have improved; Burundi and Bhutan have declined Hg/Ha Angola Bangladesh Benin Bhutan Burkina Faso Burundi Central African Republic Chad Congo, Dem Republic of Eritrea Ethiopia Gambia
12 Indicator #3: Water Use Indicator: Percent of irrigation based on non-renewable water resources Input data: University of New Hampshire discharge fields (Q) FAO irrigation withdrawals (AG)
13 Indicator #3: Water Use Method: Country-level irrigation withdrawals are geospatiallydistributed over irrigated areas (Siebert and Döll, 2001) based on irrigation need Irrigation need = Potential ET (representing crop water demand) actual ET (limited by available soil moisture) Non-sustainable Irrigation Use = Mean annual discharge (Q) minus irrigation water withdrawals (Ag) Rationale: The agricultural sector is the single largest water user. Non-renewable irrigation undermines the future ability to meet water needs for all sectors.
14 Non-renewable Irrigation (km 3 ) Sustainable Unsustainable Percent unsustainable irrigation Percent of irrigation that is from non-renewable water resources
15 Country Percent Saudi Arabia Yemen Oman Libyan Arab Jamahiriya Morocco China Canada Mexico Mongolia Peru Pakistan South Africa Egypt Kazakhstan Ukraine Mauritania United States of America Sudan India Gaza Strip (Palestine) Uzbekistan Jordan Turkmenistan Argentina Kyrgyzstan Mali Niger Japan Iran, Islamic Rep of Iraq Georgia Algeria Tunisia Spain Sri Lanka Malaysia Italy Chad Syrian Arab Republic Afghanistan Turkey Azerbaijan, Republic of Botswana Russian Federation Poland Somalia Namibia Australia Angola Bolivia Cuba Romania Kenya Hungary Madagascar Bulgaria Korea, Dem People's Rep 9.60 Brazil 8.13 Venezuela, Boliv Rep of 7.07 Belarus 5.27 Chile 4.93 Ecuador 4.58 Germany 4.41 Mozambique 4.14 Dominican Republic 4.12 Ethiopia 4.12 Greece 3.29 Tanzania, United Rep of 2.57 Burkina Faso 2.51 Zimbabwe 1.64 Uganda 1.07 Nigeria 0.67 Moldova, Republic of 0.49 Countries below zero not included in this table.
16 Conclusions Data availability on NRM for the least developed countries is a real challenge Geospatial data sets based on simple models are perhaps the best bet for getting broader country coverage All proposed indicators have time series data though the non-renewable irrigation data are under development All the measures proposed here are policy mutable and highly relevant to the NRM issues confronting the least developed countries
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