Aravindakshan Sreejith, Krupnik Timothy J, Shahrin Sumona, Tittonell Pablo, Siddique Kadambot H M, Ditzler Lenora, Groot Jeroen C J
Farming Systems Ecology Group, Wageningen University & Research, P.O. Box 430, 6700 AK Wageningen, The Netherlands.
International Maize and Wheat Improvement Center (CIMMYT), House 10/B, Road 53, Gulshan-2, Dhaka, 1213 Bangladesh.
Environ Dev Sustain. 2021;23(11):16588-16616. doi: 10.1007/s10668-021-01342-y. Epub 2021 Apr 3.
Appreciating and dealing with the plurality of farmers' perceptions and their contextual knowledge and perspectives of the functioning and performance of their agroecosystems-in other words, their 'mental models'-is central for appropriate and sustainable agricultural development. In this respect, the sustainable development goals (SDGs) aim to eradicate poverty and food insecurity by 2030 by envisioning social inclusivity that incorporates the preferences and knowledge of key stakeholders, including farmers. Agricultural development interventions and policies directed at sustainable intensification (SI), however, do not sufficiently account for farmers' perceptions, beliefs, priorities, or interests. Considering two contrasting agroecological systems in coastal Bangladesh, we used a fuzzy cognitive mapping (FCM)-based simulation and sensitivity analysis of mental models of respondents of different farm types from 240 farm households. The employed FCM mental models were able to (1) capture farmers' perception of farming system concepts and relationships for each farm type and (2) assess the impact of external interventions (drivers) on cropping intensification and food security. We decomposed the FCM models' variance into the first-order sensitivity index (SVI) and total sensitivity index (TSI) using a winding stairs algorithm. Both within and outside polder areas, the highest TSIs (35-68%) were observed for effects of agricultural extension on changes in other concepts in the map, particularly food security and income (SI indicators), indicating the importance of extension programs for SI. Outside polders, drainage and micro-credit were also influential; within polders, the availability of micro-credit appears to affect farmer perceptions of SI indicators more than drainage. This study demonstrated the importance of reflection on the differing perspectives of farmers both within and outside polders to identify entry points for development interventions. In addition, the study underscores the need for micro-farming systems-level research to assess the context-based feasibility of introduced interventions as perceived by farmers of different farm types.
The online version contains supplementary material available at 10.1007/s10668-021-01342-y.
认识并处理农民对其农业生态系统功能和表现的多种认知、他们的情境知识及观点——换句话说，他们的“心智模型”——对于恰当且可持续的农业发展至关重要。在这方面，可持续发展目标（SDGs）旨在到2030年消除贫困和粮食不安全，设想通过纳入包括农民在内的关键利益相关者的偏好和知识来实现社会包容。然而，针对可持续集约化（SI）的农业发展干预措施和政策并未充分考虑农民的认知、信念、优先事项或利益。考虑到孟加拉国沿海两种截然不同的农业生态系统，我们对来自240个农户的不同农场类型的受访者的心智模型进行了基于模糊认知映射（FCM）的模拟和敏感性分析。所采用的FCM心智模型能够：（1）捕捉每种农场类型的农民对耕作系统概念及关系的认知；（2）评估外部干预（驱动因素）对作物集约化和粮食安全的影响。我们使用蜿蜒楼梯算法将FCM模型的方差分解为一阶敏感性指数（SVI）和总敏感性指数（TSI）。在圩区内外，农业推广对地图中其他概念变化的影响观察到最高的TSI（35 - 68%），特别是对粮食安全和收入（SI指标），表明推广项目对SI的重要性。在圩区外，排水和小额信贷也有影响；在圩区内，小额信贷的可得性似乎比排水更能影响农民对SI指标的认知。本研究表明，反思圩区内外农民的不同观点对于确定发展干预的切入点很重要。此外，该研究强调需要进行微观耕作系统层面的研究，以评估不同农场类型的农民所感知的引入干预措施基于情境的可行性。
在线版本包含可在10.1007/s10668 - 021 - 01342 - y获取的补充材料。
