Gil-Clavel Sofia, Wagenblast Thorid, Filatova Tatiana
Department of Multi-Actor Systems, Faculty of Technology, Policy, and Management, Delft University of Technology, Jaffalaan, Delft, The Netherlands.
PLoS One. 2025 Mar 19;20(3):e0318784. doi: 10.1371/journal.pone.0318784. eCollection 2025.
Climate change is projected to adversely affect agriculture worldwide. This requires farmers to adapt incrementally already early in the twenty-first century, and to pursue transformational adaptation to endure future climate-induced damages. Many articles discuss the underlying mechanisms of farmers' adaptation to climate change using quantitative, qualitative, and mixed methods. However, only the former is typically included in quantitative metanalysis of empirical evidence on adaptation. This omits the vast body of knowledge from qualitative research. We address this gap by performing a comparative analysis of factors associated with farmers' climate change adaptation in both quantitative and qualitative literature using Natural Language Processing and generalized linear models. By retrieving publications from Scopus, we derive a database with metadata and associations from both quantitative and qualitative findings, focusing on climate change adaptation of farmers. We use the derived data as input for generalized linear models to analyze whether reported factors behind farmers' decisions differ by type of adaptation (incremental vs. transformational) and across different global regions. Our results show that factors related to adaptive capacity and access to information and technology are more likely to be associated with transformational adaptation than with incremental adaptation. Regarding world regions, access to finance/income and infrastructure are uneven, with farmers in high-income countries having an advantage, whereas farmers in low- and middle-income countries require these the most for effective adaptation to climate change.
预计气候变化将对全球农业产生不利影响。这就要求农民在21世纪初就开始逐步适应，并进行转型适应，以承受未来气候造成的损害。许多文章使用定量、定性和混合方法讨论了农民适应气候变化的潜在机制。然而，在关于适应的实证证据的定量荟萃分析中，通常只包括前者。这忽略了定性研究中的大量知识。我们通过使用自然语言处理和广义线性模型，对定量和定性文献中与农民气候变化适应相关的因素进行比较分析，来填补这一空白。通过从Scopus检索出版物，我们得出一个包含元数据以及定量和定性研究结果关联的数据库，重点关注农民的气候变化适应。我们将所得数据用作广义线性模型的输入，以分析农民决策背后报告的因素是否因适应类型（渐进式与转型式）以及不同全球区域而有所不同。我们的结果表明，与适应能力以及获取信息和技术相关的因素更有可能与转型适应相关，而不是渐进式适应。在世界区域方面，获得资金/收入和基础设施的情况不均衡，高收入国家的农民具有优势，而低收入和中等收入国家的农民为有效适应气候变化最需要这些。
