Article
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Exploring the Marginal Effects of Climate Change on Farming System Choice: A Farm-Level Space-for-Time Approach
Version 1
: Received: 20 September 2023 / Approved: 21 September 2023 / Online: 25 September 2023 (10:25:13 CEST)
A peer-reviewed article of this Preprint also exists.
Ribeiro, P.F.; Santos, J.L. Exploring the Effects of Climate Change on Farming System Choice: A Farm-Level Space-for-Time Approach. Land 2023, 12, 2113. Ribeiro, P.F.; Santos, J.L. Exploring the Effects of Climate Change on Farming System Choice: A Farm-Level Space-for-Time Approach. Land 2023, 12, 2113.
Abstract
Climate change is expected to affect the agricultural sector in ways that are often unclear to predict. If in the short- medium-terms farmers may adapt to climate change by adjusting agricultural practices, in the long-term these adjustments may become insufficient, forcing farmers to change their farming systems. The extent and direction in which these farming system transitions will occur is still a subject underexplored in the literature. We propose a new framework to explore the marginal effect of climate change on the choice of the farming system, while controlling the effect of other drivers known to also influence farming system choice. Using a spatial-explicit farming system choice-model developed by a previous study in an extensive agricultural region of southern Portugal, we applied a space-for-time approach to simulate the effect of climate change on the future dynamics of the farming systems in the study area. Results suggest that climate change will force many farmers to change the farming system in a foreseeable future. The extent of the projected changes in farming systems is likely to trigger significant social, economic, or environmental impacts, which should require early attention from policy makers.
Keywords
climate change; farming systems; space-for-time; marginal effect; choice modelling
Subject
Biology and Life Sciences, Agricultural Science and Agronomy
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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