GC11J-08
Coupled socioeconomic-crop modelling for the participatory local analysis of climate change impacts on smallholder farmers in Guatemala

Monday, 14 December 2015: 09:45
3005 (Moscone West)
Julien Jean Malard1, Jan F Adamowski1, Ling Yun Wang1, Marcela Rojas1, Jaime Carrera2, Juventino Gálvez2, Héctor Antonio Tuy2 and Hugo Melgar-Quiñonez1, (1)McGill University, Montreal, QC, Canada, (2)Universidad Rafael Landívar, Institute of Agriculture, Nat. Resources and the Environment, Guatemala City, Guatemala
Abstract:
The modelling of the impacts of climate change on agriculture requires the inclusion of socio-economic factors. However, while cropping models and economic models of agricultural systems are common, dynamically coupled socio-economic-biophysical models have not received as much success. A promising methodology for modelling the socioeconomic aspects of coupled natural-human systems is participatory system dynamics modelling, in which stakeholders develop mental maps of the socio-economic system that are then turned into quantified simulation models.

This methodology has been successful in the water resources management field. However, while the stocks and flows of water resources have also been represented within the system dynamics modelling framework and thus coupled to the socioeconomic portion of the model, cropping models are ill-suited for such reformulation. In addition, most of these system dynamics models were developed without stakeholder input, limiting the scope for the adoption and implementation of their results.

We therefore propose a new methodology for the analysis of climate change variability on agroecosystems which uses dynamically coupled system dynamics (socio-economic) and biophysical (cropping) models to represent both physical and socioeconomic aspects of the agricultural system, using two case studies (intensive market-based agricultural development versus subsistence crop-based development) from rural Guatemala. The system dynamics model component is developed with relevant governmental and NGO stakeholders from rural and agricultural development in the case study regions and includes such processes as education, poverty and food security. Common variables with the cropping models (yield and agricultural management choices) are then used to dynamically couple the two models together, allowing for the analysis of the agroeconomic system’s response to and resilience against various climatic and socioeconomic shocks.