An overview of the Livestock-Climate Change CRSP RPRA (Risk, perception, resilience and adaptation to climate change in Niger and Tanzania) Project and update on the project's current status. Presentation given by S. McKune (University of Florida) at the Livestock-Climate Change CRSP Annual Meeting, Golden, CO, April 26-27, 2011.

1. This presentation was made possible by the United States Agency for International Development and the generous support of the American people through Grant No. EEM-A-00-10-0001. The opinions expressed herein are those of the authors and do not necessarily reflect the views of the U.S. Agency for International Development or the U.S. Government. EFFECTS OF PERCEIVED RISK OF CLIMATE CHANGE ON PATTERNS OF ADAPTATION AND LIVELIHOOD RESILIENCE IN EASTERN NIGER Sarah L. McKune, MPHPhD Student, Interdisciplinary Ecology University of Florida, School of Natural Resources and the Environment

2. Contents of Presentation Introduction Significance of Research Objectives of Research Methods Key Variables Findings Discussion

3. Introduction This research investigates how pastoral populations with varying degrees of sedentism perceive and respond to climate change in Eastern Niger, and if/how those responses (coping mechanisms and adaptations) affect their vulnerability/resilience.

4. Introduction: Key Concepts Pastoralism and resilience Pastoral reliance on milk and animal products for subsistence and unique social adaptations have historically allowed for a high level of resilience, essential for communities whose marginal environment continually requires adaptation. Climate change and pastoralism Arid and semi-arid regions of the world are projected to be among those most affected by climate change. This poses new challenges to the historic adaptability and resilience of pastoral populations. Overarching goal of this research Climate change – coping strategies – vulnerability/resilience x livelihood

5. Introduction: Niger

6. Introduction: Niger Land area - 1.3 million sq km Population - 13.3 million people Two-thirds of the country desert, with little population Cyclical drought throughout the past century, persistent food insecurity Economy - largely agricultural and pastoral Ethnic groups - Hausa, Djerma, Fulani, Tuareg and Beri Beri. Tuareg and Fulani pastoralists inhabit the northern reaches of the populated southern third of the country, and some live and track herds farther into the heart of the Saharan north. Macro International Inc., 2007

7. Introduction: Study Area Niger Located between Tanout and Agadez, within the administrative departments of Zinder and Agadez, circled in red Includes a southern portion of the pastoral zone (in tan) and a northern portion of the agro-pastoral zone Sparsely populated by sedentary agro-pastoral communities in addition to semi-nomadic communities, and, seasonally, nomadic communities Site of 2005-2007 data collection for UA/BRC FEWS NET, 2005

8. Significance of Research It is essential that global efforts to improve livelihoods determine if/how climate change is differentially affecting pastoral, agropastoral, and agricultural communities, rather than assuming that communities with different means of subsistence will experience, interpret, and be affected equally by climate change and strategies and adaptations used to manage climate related risk.

9. Specific Objectives of Research Describe perceptions of climate change among communities across the nomadism-sedentarism spectrum Determine if perceptions of climate change are a motivating factor for specific livelihood strategies, including sedentarization, among communities Determine how utilized strategies and adaptations are affecting vulnerability/resilience (especially child health) among communities

10. Methods Field Methods Statistical Methods

11. Methods: Field Methods Primary data collection Oct-Jan 2010/11 Focus groups Key-informant interviews Household surveys Child health and growth measures

12. Methods: Statistical Methods Construction of indices for key variables Factor analysis Reliability testing (Chronbach’s alpha) Descriptive analysis of key variables Correlation tests (Spearman’s Rho and Pearson’s r) to assess bivariate association Linear regression to estimate explanatory models

13. Key Variables

14. Key Variables 14 item livelihood index created household survey data including revenue sources, history of agriculture, history of pastoralism, self identification, and use of migration as herding strategy. Created to capture an agricultural-pastoral continuum that positions households along a livelihood spectrum Livelihood

15. Descriptive Statistics: Livelihood Univariate distribution of the livelihood of households in the sample is presented above. Note the lack of households representing the poles.

16. Key Variables 14 item perceived risk of climate change (PRCC) index Seven areas of potential climate change (hazards) identified through literature review and focus group discussion Each head of household indicated 1) the degree of locally observed change and 2) the magnitude of potential harm for each of the seven hazards Those products were then summed for the seven hazards and broken into tertiles, categorizing household perception of climate change as low (38%), medium ( 32.5%), or high (29.4%; n=126). Perceived Risk of Climate Change (PRCC)

17. Key Variables Complications Lack of internal reliability (CA = .425) Options: Accept lower Chronbach’s alpha Eliminate items and statistically increase internal reliability (3 item index, CA = .557) Look at each hazard individually Implications on applicability in other research sites All three options employed Perceived Risk of Climate Change (PRCC)

18. Descriptive Statistics: PRCC (full index) Univariate distribution of the PRCC among households in the sample is presented above. Note, this is for the 14 item index (seven hazards included: land degradation, vegetation cover, soil and crop productivity, rainfall, desertification, heat/temperature, and loss of indigenous species).

19. Key Variables 8 item vulnerability/resilience index (adapted from Elasha et al., 2005) Generic indicators of resilience presented to key informants, who then established locally appropriate indicators These indicators validated through focus group discussions, and 8 items used in the final survey Heads of household asked to compare their current situation for each indicator (e.g., wealth, health, soil productivity, etc.) to the situation immediately following the 2005 food crisis A summary index was created based on household response to these eight items, and tertile data are presented as univariate distribution of decreasing, stable, or increasing resilience Vulnerability/Resilience

20. Key Variables Complications Lack of internal reliability (CA = .438) Options: Eliminate items and statistically increase internal reliability (5 item index, CA = .540) Look at each item individually Implications on applicability in other research sites Perceived Risk of Climate Change (PRCC)

21. Findings Preliminary findings indicate that despite no significant correlation between livelihood and perceived risk of climate change, livelihood is significantly correlated with certain coping strategies, many of which, are significantly correlated with increasing vulnerability, or a loss of resilience.

22. Findings Correlation tests were used to assess bivariate association (Spearman’s Rho and Pearson’s r) and linear regression was used to estimate explanatory models

23. Findings Describe perceptions of climate change among communities across the nomadism-sedentarism spectrum No statistical correlation between livelihood and PRCC No significance when resilience and/or sedentarization added to the model. No significant correlation between individual items (risk of each hazard) and livelihood. Objective 1:

24. Findings Determine if perceptions of climate change are a motivating factor for specific livelihood strategies, including sedentarization, among communities PRCC is positively correlated with strategies to accept familial loans and is negatively correlated with consumption of one’s own harvest and seasonal migration Pastoral populations have a PRCC that positively correlates with nomadic transhumance and reduced mobility and negatively correlates with sending family members to live with others and regular migration Agricultural populations have a PRCC that positively correlates with a day of fasting and accepting commercial loans and negatively correlates with the sale of personal belongings Objective 2:

25. Findings Determine how utilized strategies and adaptations are affecting vulnerability/resilience (especially child health) among communities Reduction of number of meals, reduction in amount of food per meal, use of fasting days, and consumption of one’s own milk/meat are each correlated with ]self-reported increasing household vulnerability (decreased resilience). Accessing grain banks and sending children to work are both correlated with self-reported decreasing household vulnerability (increased resilience) Reduction in the amount of food per meal is correlated with higher weight for height z-scores (lower rates of malnutrition) Controlling for livelihood does not change the relationship between coping strategies and child nutrition outcomes Objective 3:

26. Discussion

27. Discussion No significant difference in the perception of climate change across the agro-pastoral livelihood continuum Implications of finding for development practice Next steps: elaborate regression model to include other potential interactions and confounding factors

28. Discussion Correlation between certain coping strategies and vulnerability Implications for development Limitation: vulnerability/resilience thus far measured based on self-reported index Next step: triangulate self-reported items within the vulnerability index (health, wealth, land cover, etc.) with qualitative data and data measuring change between 2005 and 2010 (data from household surveys and Landsat images)

29. Discussion Inverse relationship between resilience and livelihood found in sample Why? Timing of data collection? Self-reported v. measured? Lack of correlation between PRCC and livelihood Qualitative data to confirm/refute this? Establish role of vulnerability/resilience in relationship between PRCC, coping strategies/adaptations, and livelihood Estimate multiple regression models to predict livelihood; vulnerability/resilience Additional points for discussion

30. Thank you. Questions?