1. Local Knowledge Systems – local indicators, connecting to regional forecasts Jere Gilles University of Missouri McKnight Workshop Lima, Perú, 29 April 2008

2. Topics Adaptation and community networks Local and scientific knowledge systems Aymara traditional forecast indicators Local networks and scientific forecasts Building resilience through linking systems

3. Adaptation and knowledge Adaptation is a continual locally based process Adaptation depends upon the pool of knowledge available and the costs and incentives to change Extra community knowledge needed with increased importance of extra- community shocks

4. Linking knowledge Systems to Improve Adaptation and resilience Linking local and scientific is the only way to downscale in order to help decision makers We must understand differences before we can develop strategies for linking them.

5. Local Knowledge Empirical but based in practice It is context specific (a time and place) The core of local knowledge are explanations specific to a particular place and time

6. Scientific Knowledge Empirical Explanations based upon prior observations and on theories The core of scientific knowledge are explanations that are independent of time and place/reductionist

7. Local and Indigenous Knowledge Local knowledge is practitioner knowledge not necessarily “indigenous knowledge” Differences between local and scientific knowledge on climate (Orlove, Chiang and Case, Nature 2000)

8. Pleaides (K’oto) rainfall and potato yield

9. Differences between Knowledge Systems Context: LK: the principal focus, SK : the principal obstacle Perspective: LK: holistic, SK: reductionist Principal Language: LK: Practice, SK: words and symbols

10. Sources of climate forecast information in the Altiplano Two communities— Peru and Bolivia Sources of information– 1999 90% used abiotic indicators and 99% used biotic ones– 3% used scientific sources directly, 13% used media (in Peru the Bristol Almanac was an important source)

11. Traditional Indicators Abiotic indicators Stars Winds Biotic indicators Plants Animals

12. Production Decisions related to climate Few people relied on their own observations of indicators Relied on the knowledge of local experts/nodes– the best potato producers

13. Schematic of a Network

14. Changes observed 1999-2006 Significant decline in use of indicators but the exact degree unclear Participatory methods lower level of use and efficacy than survey/ intensive methods 74% still use in Bolivian community LT 50% in Peruvian one from surveys

15. Reasons for Decline? Local knowledge answer—they don’t work like they used to (expers disagree) Scientific knowledge hypotheses– Environmental change Changes in the production system Disappearance of nodes/experts Never worked

16. Our Challenge for the future Create effective local knowledge systems related to weather and climate Develop linkages between knowledge systems Currently working with farmer groups in Bolivia to monitor and evaluate indicators