Payments to promote biodiversity conservation and implications for poverty reduction among pastoral communities in East Africa

Payments to promote biodiversity conservation and implications for poverty reduction among

pastoral communities in East Africa

Philip Osano (PhD Candidate)Geography Department, McGill University, Canada

Graduate Fellow, ILRI (PLE)August 16, 2011

Outline of Presentation

1. Problem Statements

2. Conceptual Framework of the study

3. Study Objectives and Questions

4. Study Design and Preliminary Results

Problem Statements

1. Severe declines in large mammal wildlife population in Kenyan rangelands

Western et al. 2009; Ottichilo et al. 2000; Norton-Griffith, 2007; Norton-Griffith & Said, 2007

Source: Norton-Griffith, 2007

1. Habitat loss/fragmentation (pop. increase; agricultural expansion etc)2. Poaching (e.g. illegal trade, local consumption etc)3. Recurrent drought (and climate change)

2. Pastoralists are becoming more poorer in rangelands

Homewood et al. 2009; Reid et al. 2008; Okwi et al., 2007; UNDP, 2006; WRI, 2007; Norton-Griffith, 2007; Ferraro & Kiss, 2002; Pagiola et al. 2005; Grieg-Gran et al., 2005; Zilbermann et al., 2006; Barret & Arcese 1995; Horan et al., 2008;

Pastoralists are diversifying income sources due to increase in poverty

Wildlife payments (PES) can potentially provide stable, predictable and reliable income to pastoral landholders – future of wildlife conservation in private land (mostly pastoral)

Past approaches (e.g. ICDPs, CBC, CBWM etc) insufficient: only 5% of wildlife tourism revenue accrue to local landowners in Kenya yet they bear heaviest costs of conservation

Direct payments or (PES) can contribute to wildlife conservation and poverty reduction among pastoral communities e.g. Maasai in Amboseli (Bulte et al., 2008)

Conceptual Framework of the study

Wunder, 2008:287

Study Objectives, Hypothesis and Questions

Questions

1. What are the financial and non-financial benefits of PES on households?

• What is the annual income benefit to provider households from PES• What is the income from PES to provider households used for?• What are the perceived social and cultural impacts of PES?• How are non-participants and potential providers affected by PES?• What are the potential drawbacks and obstacles of PES?

2. What are the motivating factors driving household participation in PES?

• How does household poverty status affect the intensity of participation in PES?

• What are providers recommendations on PES design and features?• What are the reasons why potential providers want to participate in

PES?

Questions3. How does formal and non-formal institutions contribute to PES

implementation?

• What are the roles of provider groups (e.g. landowners and wildlife associations), users, intermediaries and other stakeholders?

• How does normative institutions (e.g. laws and policies on property rights) affect PES implementation?

• How does PES fit with traditional non-formal institutions of Maasai community?

4. What are the perceived risks and how are these mitigated in PES design?

• What are the major perceived risks and threat to PES implementation?• What are stakeholders perceived future scenarios for household and

wildlife conditions with and without PES?

Study Design and Preliminary Results

Data sources

1. Household surveys in 2 sites: ES providers, potential providers and non-providers

2. Interviews with Users, Intermediaries and Key Informants

3. Secondary data: past surveys, PES program database (contract/lease agreements, payment records, compliance /monitoring of conditionalities etc)

4. Review of legal, policy and development planning documents

5. GIS and spatial databases (ILRI)

Olare-Orok Conservancy (OOC)

• 130 HHs surveyed- Participants = 73- Non-participants = 57

• Partnership between tourism private sector and pastoral landowners

• Current payment rate of $ 43/ha/yr:

- Controlled livestock grazing- No settlements in core

conservation area

Maasai Mara National Reserve

50 0 50 100 Kilometers

N

Maasai Mara National Reserve

Proportion Below Poverty Line among Members and Non-Members of Olare Orok Conservancy (OOC)

Ref: Osano et al. (in prep.)

Year 2008 2009Proportion below Poverty Line (US$ 1/capita/day

OOC+PWC 24/72 22/7333 % 30%

OOC-PWC 26/52 22/5150% 43 %

OOC+PWC (Ex-Providers)

2/6 2/633% 33%

• 164 HHs surveyed- Participants = 86- Non-participants = 78

• PES funding from KWS, World Bank (GEF) and TNC (USA)

• Current payment rate of $ 10/ha/yr:

- No plot fencing- No land sub-

division

Thank You for Listening!

Add a trend line showing area of Nairobi National Park (ha) and area of Athi Kapiti Plains

Study Design

Question Data Requirements Data Analysis

1. Financial and non-financial benefits (profitability of land use)

Household Income data (poor vs. non-poor)Household Socio-economic condition dataLand prices/valuesData on use of PES incomeNon-income benefitsLand use dataAccess to social services

PES payments vs. household income/expenditure Cost analysis:- Start-up costs - PES payments vs. Opportunity costs of land use (GIS maps)- PES payments vs. transaction costsQualitative analysis of interviews

2. Motivating factors for HH participation

Total land area of householdLand area allocated to PES (in conservation)Household characteristicsPES program characteristics

Regression Analysis (dependent variable = proxy indicator intensity of HH participation)Independent variables: factors likely to affect participation of poor in PESContingency TablesQualitative analysis of interviews

Data and Data Analysis

Ferraro & Pattanayak, 2006; Pagiola et al. 2008

Study Design

Question Data Requirements Data Analysis

3. Influence of Institutions

Membership in local resource associations (e.g. land, wildlife)Implementation of laws and policies (e.g. land, wildlife, environment, etc)

Qualitative analysis of household survey responses, users, intermediaries and key informantsPES program reportsPolicy and Institutional Analysis (e.g. review of published /grey literature on local/national policy development planning)Policy screening

4. PES risks mitigation and future scenarios

PES financing (short and long term)Data on use of PES income (displacement/leakage effect)Data on withdrawals/reasonsLocal drivers of change (land sales)National drivers of change (policy)

Qualitative analysisScenario analysis

Data and Data Analysis