A framework to assess fine-resolution land use implications from global and regional human-driven decisions: MIT IGSM-Demeter

Plain Language Summary
The use of land for agricultural and human activities has important effects on the environment. Scientists develop models to represent how land use evolves at global and regional levels due to overall socio-economic and environmental changes, but usually these do not address changes at local levels. 

To overcome this limitation, we combined an economy-wide model with a land use model which can spatialize the projections from broad changes in the societies, markets and nature. This approach helps us to understand how land use might change in the future at global, regional, and local levels, due to various global challenges. Our findings show that in scenarios with rapid economic growth, increasing populations, and significant climate impacts, there's a trend toward converting forests into pastures for grazing. On the other hand, in scenarios with less pressures, land use remains more stable. These changes vary widely depending on the region and specific circumstances of each country and region. 

Our study highlights the importance of considering global factors when looking at local land use changes and demonstrates how combining different models can improve our predictions.

Abstract 

Land use change driven by human activities has significant environmental consequences that can vary significantly at local scales. However, global coupled human-Earth system models usually project land use changes at resolutions that are too coarse to provide insights at finer resolutions that are commensurate to climate models and assessing land-use impacts. To overcome this, we integrate a human-system model with an open-source downscaling model to project land-use changes at a finer spatial resolution and capture their important variations at regional to local scales. We use this framework to investigate future land use transitions at global, regional and local scales under various global stressors, emphasizing the interplay between natural and human systems. 

We find that land-use transitions can intensify toward pasture and grazing land, often at the expense of forests, under scenarios associated with higher economic growth, population increases, and climate impacts. Conversely, low-pressure scenarios reduce overall transitions, favoring stability in land use patterns. Results show large heterogeneity within and across alternative scenarios and geographies, driven by differences in socio-economic responses and land characteristics. While both cropland and pasture increase in Africa, pasture expansion dominates in Europe, US and China. 

Our study demonstrates the relevance of global drivers on land-use projections when evaluating regional and local impacts, which can be achieved by integrating human-system models with a downscaling model. The framework is a step toward more fully incorporating feedback mechanisms between human and natural systems with an aim of improving predictions of socio-economic and climate-driven land use change.