Agroecological assessment of maize suitability in the Polissia and Forest-Steppe of Ukraine under future climate projections

Climate change is profoundly altering the spatial structure of agricultural land use, particularly in regions such as Polissia and the Forest-Steppe of Ukraine. These areas, characterised by distinct climatic and edaphic conditions, are increasingly vulnerable to shifts in temperature, precipitation patterns, and the frequency of extreme weather events. This study presents a comprehensive spatial modelling approach to assess the historical and projected suitability of maize cultivation in these agroecological zones under four Shared Socioeconomic Pathways (SSP126, SSP245, SSP370, SSP585) across three time horizons (2021–2040, 2041–2060, and 2061–2080). Using a combination of 19 bioclimatic variables from the WorldClim and CMIP6 datasets and 9 soil predictors derived from SoilGrids, the analysis integrates historical yield data from the CROPGRIDS database to construct a multivariate linear regression model with Box-Cox transformation. The results indicate that in the historical period, maize distribution was primarily constrained by low winter temperatures, excessive annual precipitation, and high soil nitrogen levels, while optimal temperature and moisture conditions during the growing season significantly enhanced suitability. Soil compaction was found to be a critical limiting factor, underscoring the importance of soil physical properties for root development. Under future climate scenarios, short-term warming is projected to facilitate a northward expansion of suitable areas. However, in the medium and long term, a consistent reduction in the spatial extent of favourable zones is observed, particularly in the northern Polissia region. The SSP585 scenario, representing high emissions and rapid socioeconomic development, results in the most substantial decline in maize suitability, whereas SSP126 maintains relative stability in central Forest-Steppe areas. Analysis of variance (ANOVA) and non-parametric tests confirm that time (period) is the dominant driver of variability in projected maize areas, while SSP scenarios and their interaction play secondary roles. Delta maps of projected change relative to historical baselines reveal pronounced spatial and temporal heterogeneity. While early periods may exhibit local gains, especially under mild scenarios, losses increasingly dominate in subsequent decades, with more intense warming accelerating the contraction of suitable areas. The generated spatial maps and scenario-specific forecasts provide valuable insights for adaptive agricultural planning. These tools enable the identification of stable, transitional, and vulnerable zones and support the development of region-specific strategies such as adjusting crop rotations, investing in irrigation, and selecting climate-resilient varieties. The study highlights the need for integrated approaches that consider both climatic and edaphic variability in the context of global change. Future research should expand on these findings by incorporating socioeconomic variables, land use practices, and farmer-level adaptation strategies. Overall, this work establishes a scientific foundation for enhancing the climate resilience of maize production systems and informs evidence-based policy development for sustainable agriculture in Ukraine.