4.5 Article

Participatory scenario planning for developing innovation in community adaptation responses: three contrasting examples from Latin America

Journal

REGIONAL ENVIRONMENTAL CHANGE
Volume 16, Issue 6, Pages 1685-1700

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s10113-015-0898-7

Keywords

Socio-ecological systems; Community-based adaptation; Scenarios; Triple-loop learning; Social learning; Latin America

Funding

  1. EU [282845]
  2. Scottish Government

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Environmental change requires adaptive responses that are innovative, forward-looking and anticipatory, in order to meet goals for sustainability in socio-ecological systems. This implies transformative shifts in understanding as conceptualised by the idea of 'double'- or 'triple-loop learning'. Achieving this can be difficult as communities often rely on shorter-term coping mechanisms that purport to maintain the status quo. The use of participatory scenario planning to stimulate forward-looking social learning for adaptation was investigated through three contrasting community case studies on natural resource management in Latin America (in Mexico, Argentina and Colombia). Exploratory scenario narratives that synthesised local knowledge and future perceptions were used iteratively to define response options considered robust across multiple futures. Despite its intensive format, participants in each case agreed that scenario planning enabled a more systematic appraisal of the future. Scenarios facilitated innovation by providing scope to propose new types of responses and associated actions. Differences in local context meant that learning about future change developed in diverse ways, showing a need for a reflexive process. Reframing of key issues characteristic of double-loop learning did occur, albeit through different forms of interaction in each location. However, a shift towards transformative actions characteristic of triple-loop learning was less evident. Achieving this would appear to require ongoing use of scenarios to challenge social norms in light of changing drivers. Use of learning loops as a diagnostic to evaluate adaptive responses provided a useful reference framework although in practice both innovation and consolidative approaches can develop concurrently for responses to different issues.

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