Perceptions, Networks, Knowledge and Climate
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Perceptions, Networks, Knowledge and Climate Jere L. Gilles Department of Rural Sociology, University of Missouri. Segundo Seminario Internacional de Investigación SANREM CRSP: Cambios globales y su efecto sobre los sistemas agropecuarios de la zona andina. La Paz, 28-29 junio, 2007. Goals.

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Perceptions, Networks, Knowledge and ClimateJere L. GillesDepartment of Rural Sociology, University of Missouri

Segundo Seminario Internacional de Investigación SANREM CRSP: Cambios globales y su efecto sobre los sistemas agropecuarios de la zona andina. La Paz, 28-29 junio, 2007


  • Perceptions and the scientific enterprise

  • The relationship between networks, perceptions, action and forecasts

  • The gap between scientific and local knowledge

  • A research plan to for addressing this gap


  • The word perception has a bad reputation in some circles

  • Suggests something that is based more on opinion than fact

  • Science is entirely based on perception

  • The Thomas Theorem—what is believed has real consequences but… what is real may or may not.

Where do the perceptions that influence our decisions come from

  • Empirical experiences of ourselves and others

  • Our networks

    • The connections we have to other people who we trust

    • Can be through publications but the most are through personal contacts


The case of forecast networks

  • Little overlap in networks used by forecasters and those used by producers

    • Ex. Interviews in 3 altiplano communities showed only 12% used mass media forecasts

    • Only 7% used technicians and extension

Factors leading to disconnectHypotheses

  • Effectiveness of scientific forecasts not as apparent as those of local forecasts.

  • Lack of congruence between products of scientific forecasters and producer needs

  • Producers cannot use forecasts in current form

Bridging Knowledge Systems

  • Practitioners organize knowledge differently than scientists

    • This creates barriers to the development of appropriate technology

    • Makes it difficult to adopt appropriate technology

Local and Scientific Knowledge

  • Both are empirical

  • Local knowledge is contextual—what works best in my situation

  • Scientific knowledge views context as problematic (seeks knowledge that is independent of time and space)

Local Climate Forecasting in the Altiplano

  • Forecasting is an important risk management tool (when, where, what to plant)

  • Farmers use a variety of indicators to make predictions –abiotic and biotic

    • Although many understand indicators people rely on a few local experts.


(Cantón San José)


Plantas Thola

Animales Tiqui tiqui, Tiqui tiqui


 Abioticos Q’ana Q’ana

Nevada Vientos


Local forecasts linked to actions


  • Pronóstico Precipitación, Pronóstico Temperatura, Modo de Siembra Alternativa Precipitación alta (lluvia en abundancia Sembrar en partes altas y suelos secos Precipitación baja (poca lluvia o sequía)Sembrar en partes bajas y suelos húmedos. Bajas temperaturas (fuertes heladas)Sembrar en lomas. No sembrar en hoyadas.

Perceptions and Forecasting

  • There may be less confidence in both scientific and local systems

    • Reports about global warning and increased dryness seem to be contradicted by flooding

    • There appears to be less confidence in local indicators even has there is increased evidence of their validity.


  • To build linkages between scientific and local forecast experts

    • This can enhance use of forecasts AND

    • Provide valuable information on local scale that can help scientific forecasts

      Linkages may provide basis for a early warning system

How to meet challenge

  • Validate traditional and scientific methods through participatory research

  • Train locals in the observation and use of indicators

  • Use collaborative learning to improve the development and communication of forecasts

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