The Impact of Climate Change on the Sustainability of PGI Legume Cultivation: A Case Study from Spain

Legume crops are sensitive to shifting environmental conditions, as they depend on a narrow range of climatic stability for growth and nitrogen fixation. This research sought to assess the sustainability of Faba Asturiana (FA) cultivation under current and future climatic scenarios by establishing generalized linear mixed models (GLMMs). Specifically, it aimed to (1) investigate the effects of significant climatic stressors, including higher nighttime temperatures and extended drought periods, on crop viability, (2) analyze future scenarios based on Representative Concentration Pathways (RCP 4.5 and RCP 8.5), and (3) recommend adaptive measures to mitigate threats. Six spatial GLMMs were developed, incorporating variables such as extreme temperatures, precipitation, and the drought duration. Under present-day conditions (1971–2000), all the models exhibited strong predictive performances (AUC: 0.840–0.887), with warm nights (tasminNa20) consistently showing a negative effect on suitability (coefficients: −0.58 to −1.16). Suitability projections under future climate scenarios revealed considerable variation among the developed models. Under RCP 4.5, Far Future, Model 1 projected a 7.9% increase in the mean suitability, while under RCP 8.5, Far Future, the same model showed a 78% decline. Models using extreme cold, drought, or precipitation as climatic stressors (e.g., Models 2–4) revealed the most significant suitability losses under RCP 8.5, with the reductions exceeding 90%. In contrast, comprising variables less affected by severe fluctuations, Model 6 showed relative stability in most of the developed scenarios. The model also produced the highest mean suitability (0.130 ± 0.207) in an extreme projective scenario. The results highlight that high night temperatures and prolonged drought periods are the most limiting factors for FA cultivation. ecological niche models (ENMs) performed well, with a mean AUC value of 0.991 (SD = 0.006) and a mean TSS of 0.963 (SD = 0.024). According to the modeling results, among the variables affecting the current distribution of Protected Geographical Indication-registered AF, prspellb1 (max consecutive dry days) had the highest effect of 28.3%. Applying advanced statistical analyses, this study provides important insights for policymakers and farmers, contributing to the long-term sustainability of PGI agroecosystems in a warming world.