ArticleAgronomy for sustainable development2023
Effects of extreme events on land-use-related decisions of farmers in Eastern Austria: the role of learning.
Article in Agronomy for sustainable development, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Tipping points toward sustainability: The role of industrial ecology.Journal of industrial ecology · 2025Article
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8 authors.
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Abstract
European farm households will face increasingly challenging conditions in the coming decades due to climate change, as the frequency and severity of extreme weather events rise. This study assesses the complex interrelations between external framework conditions such as climate change or adjustments in the agricultural price and subsidy schemes with farmers' decision-making. As social aspects remain understudied drivers for agricultural decisions, we also consider value-based characteristics of farmers as internal factors relevant for decision-making. We integrate individual learning as response to extreme weather events into an agent-based model that simulates farmers' decision-making. We applied the model to a region in Eastern Austria that already experiences water scarcity and increasing drought risk from climate change and simulated three future scenarios to compare the effects of changes in socio-economic and climatic conditions. In a cross-comparison, we then investigated how farmers can navigate these changes through individual adaptation. The agricultural trajectories project a decline of active farms between -27 and -37% accompanied by a reduction of agricultural area between -20 and -30% until 2053. The results show that regardless of the scenario conditions, adaptation through learning moderates the decline in the number of active farms and farmland compared to scenarios without adaptive learning. However, adaptation increases the workload of farmers. This highlights the need for labor support for farms. Supplementary Information: The online version contains supplementary material available at 10.1007/s13593-023-00890-z.
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