Economic Impact of Land Degradation in the Himalayan region & Sub-Saharan Africa & policy

implications

Dr. Ephraim Nkonya1

Dr. Melanie Requier Desjardins2 Dr. Ho Young Kwon1

Professor Raghavan Srinivasan3 1 International Food Policy Research Institute

2 Researcher, Centre of Economics and Ethics for Environment and Development & member of the French Scientific Committee on Desertification (CSFD)

3 Texas A&M University

Bhutan, in Pursuit of Happiness

• Bhutan measures its economic development in terms of Gross Domestic Happiness (GPH)– Enhancing traditional values, improving people’s standard of

living and environmental sustainability• 72% of land area covered with forest

– Deforestation rate in 1990-2010 only 0.03% - mainly conversion to built land

• 51% of land area protected• Ag land area only 1.8%, but employs 67% of population• Hydroelectric power (HEP) accounts for 22% of GDP –

largest sector

The cost of land degradation• Bhutan spends US$9.6 million to repair

turbines damaged by sediment loading, which is 0.53% of country’s GDP– SLM reduces sediment loading by 50%Table 1: Impact of SLM on sediment loading, SWAT results

Area in 000 Km2 Sediment under SLM T/ha

Baseline Sediment T/ha

% Change

Forest 26.31 1.75 3.5 50%Agriculture 1.22 4.58 5.93 23%Citrus orchards 0.039 2.98 5.96 50%

On-farm & off-farm benefits of Sustainable Forest Management (SFM)

10.147.8

Benefit of SFM (million US$) in Bhutan

On-farm Off-site

The large off-benefit suggestsThe need for PES to farmersPracticing SLM

What can be done to achieve SFM?

• Payment for ecosystem services (PES) with direct tangible benefits to land users– Currently DGPC pays the government 1% of its

revenue for encouraging SFM but land users hardly link the PES to SFM

• Turn publicly managed forests to community forests – this can increase forest density by 25% (Agarwal 2009

• Secure land tenure, access to roads & extension services enhance SLM

Sub-Saharan Africa

Economics of land degradation

• We evaluate losses due to land degrading land management practices on crops. Empirical models used to determine impact of land management on maize yield

• We use past studies and secondary to determine land degradation due to deforestation

Crop loss due to land degrading practices

• Annual yield loss:– Empirical model 2% for two thirds of farmers using

low management practices– Long-term experiment, Kenya 4.6%

• Such loss is enormous and has negative implications on achieving food security and poverty reduction

Cropland area expansion has predominantly replaced intact forest

East Africa Central Africa West Africa0

10

20

30

40

50

60

70

80

Sources of cropland area expansion in SSA, 1980-2000

intact forest Disturbed forest

Sour

ce o

f agr

icul

tura

l lan

d ex

-pa

nsio

n, %

Source: Gibbs et al 2010

Cropland change in SSACountry Baseline, 1973-83 Endline, 1997-2007

% change

Million ha  Countries with declining cropland area

Botswana 0.40 0.24 -41Guinea 3.56 3.12 -12Ethiopia 13.63 12.23 -10Senegal 3.21 3.08 -4Equatorial Guinea 0.23 0.22 -3

SSA countries with >70% increase in cropland areaBenin 1.53 2.73 79Ghana 3.54 6.34 79Sierra Leone 0,51 0.98 93Mauritania 0.22 0.45 106Mali 2.01 5.17 157SSA 103.97 202.36 23

Botswana’s large investment into R&D partly explains the countries decrease in Crop land area

Why farmers replace forests with cropland?

Forest ecosystem value US$/haSustainable timber harvesting 1480Fuelwood 40NTFPs 50Genetic info 1500Recreation 236Watershed benefits 47.5Climate benefit 1280Existence value 7Tangible local benefits 1570Global benefits 2780

Ecosystem value of forest (US$/ha)

Tangible local benefitsGlobal benefits

Tropical forest vs maize production

Tangible local benefits (no timber)

maize proudction Tangible local benefits (with timber)

0200400600800

10001200140016001800

90

573

1570

Benefit (US$/ha)

Maize has greater returns than forest with no timber deforestation Farmer also need food more than forest products

Cost of land Degradation in SSA

The Cost of Desertification in North Africa : % of GDP

0

0,2

0,4

0,6

0,8

1

1,2

1,4

1,6

Algeria Tunisia Morocco Egypt

% of GDP

Cost of desertification in North Africa

Sarraf, 2004

Cost of land degradation in SSA

Country, year

Type of loss

Cost AGDP

Main Elements of Methodology

Rwanda, 2003

Agriculture 3,5% Agr P ; loss of human productivity

Ethiopia 2003

Agr, Livstk, For

4% Depth of soil and loss in productivity

Ethiopia, 1986

Agriculture <1% Modelling of crop WRS

Zimbabwe, 1994

Agriculture <1% Modelling of plants growth, erosion mapping

Zimbabwe, 1992

Agriculture, Livestock

8% Cost of replacement, main soils and farms types

Malawi, 1992 Agriculture 3% Modelling of soil losses and drop in productivity

Berry et al. 2003, Bojo, 1996

Implications

• Direct and tangible local benefits should form basis of decision making

• Incentives Build SLM on solid ground – effective governance

• PES programs can enhance SLM – especially if they are grounded on local buyers and sellers of ecosystem services

• R&D will help increase intensification – lead to saving the forests