High Resolution Global Environmental Stratification to Model Shifting Bioclimatic Conditions and Climate Change Impacts on Terrestrial Ecosystems

Understanding climate-driven ecological change benefits from frameworks capable of translating climate model outputs into ecologically interpretable spatial patterns. This study presents a global application of the Environmental Stratification (EnS) methodology, using Maximum Likelihood Classification, and integrating outputs from 22 CMIP6 Earth System Models (ESMs) across four Shared Socioeconomic Pathways (SSP: 1-2.6; 2-4.5; 3-7.0; 5-8.5), two historical baseline climate datasets (1960–1990; 1970–2000), and two future averaged time periods (2021–2040; 2041–2060). Both “Consensus” and “High-Risk” multimodel majority ensembles were selected and used in the global analysis. The resulting Future_Global_EnS Database ( https://doi.org/10.5281/zenodo.15099763), provides these highresolution EnS projections at 30 arc seconds resolution (~1km ²). The global EnS analysis reveals extensive bioclimatic reorganization by mid-century. Cooler and mesic zones, particularly boreal, temperate, and montane systems, exhibit high zonal turnover, significant poleward latitudinal shifts, upslope migrations, and mountaintop extirpations. Tropical, arid, and extremely hot zones show significant spatial expansion and internal reorganization under high-emissions scenarios, including large-scale growth of drylands and intensification of extremely hot bioclimatic conditions. Results from the global EnS analyses align closely with empirical observations of bioclimatic and ecological shifts, providing spatially explicit, ecologically grounded metrics for anticipating where and how terrestrial ecosystems will change. By delineating statistically based coherent and ecologically meaningful geospatial strata, the EnS methodology provides a powerful tool for translating complex climate projections into interpretable ecological insights and enables rigorous analysis of climate impacts at decision-relevant scales. Both the EnS methodology and Future_Global_EnS Database provide a resource with immediate utility for biodiversity conservation, land-use policy, agricultural sustainability, natural resource management, and adaptation to rapid climate change, at global to regional and local scales.

As the planet warms, natural systems across the globe are shifting, and this study introduces a widely applicable methodology and a new global dataset that helps us understand how climate change is expected to alter the environments where plants and animals live. Using climate projections, the researchers mapped how bioclimatic zones—areas with similar temperature, rainfall, and moisture—are likely to shift over time. This method, called Environmental Stratification (EnS), identifies patterns such as cold, wet forests or hot, dry deserts, and shows how these zones may move, shrink, or expand in the coming decades. For instance, cooler zones in mountains and polar regions are projected to decline, while hotter and drier zones are expected to grow. Many regions may experience climates that differ significantly from the past, with shifts occurring toward the poles or higher elevations. These changes affect agriculture, biodiversity, and water resources, especially in areas already vulnerable to climate extremes. The analysis highlights patterns of bioclimatic displacement, zone turnover, and emerging risk space, offering a global-scale perspective on the pace and direction of ecological change under climate warming.

While the main contribution is the utility of the EnS framework in interpreting future climate conditions, the study also makes available a high-resolution (30 arc-second) global dataset of present and projected EnS classifications. This open-access resource supports research, planning, and decision-making related to conservation, land management, and climate adaptation.The new EnS database stands out for its global coverage, high spatial detail (about 1 km resolution), and public accessibility, making it a useful tool for governments, researchers, land managers, and communities preparing for future conditions. The work reflects a collaboration between European and Chinese institutions, particularly the Center for Mountain Futures at the Kunming Institute of Botany and the CMCC Foundation in Italy, and provides a practical resource for supporting climate adaptation.