# Projecting spatiotemporal changes in Soil Organic Carbon stocks in Mexico under coupled socioeconomic and climate scenarios

## TL;DR

The study predicts how soil carbon in Mexico will change by 2100 based on different future scenarios involving climate and land use.

## Contribution

The study introduces a new method combining climate and socioeconomic data to project soil carbon changes in Mexico.

## Key findings

- Mexico's soil carbon stocks may decline under fossil-fueled development scenarios.
- Agricultural systems could shift from carbon sinks to sources by 2070 under certain scenarios.
- Sustainable pathways may stabilize or slightly increase soil carbon stocks.

## Abstract

Soil organic carbon (SOC) sequestration is a pivotal strategy for achieving global climate goals, yet current projections often rely on static landscape assumptions that fail to capture the complex interplay between climatic forcing and socioeconomic development. This limitation is particularly acute in Mexico, where rapid agricultural transformation threatens to destabilize historic carbon sinks. To bridge this gap, we projected spatiotemporal SOC dynamics (2021–2100) across Mexico’s diverse ecoregions by coupling a calibrated Random Forest model (R2 = 0.45) with downscaled climate and dynamic land-use data under four Shared Socioeconomic Pathways (SSPs). We identified a current baseline mean SOC stock of 2.96 kg C/m² and revealed stark, pathway-dependent future trajectories. While sustainable and intermediate pathways (SSP126, SSP245, SSP370) stabilize or slightly increase national stocks (~2% gain), the fossil-fueled development scenario (SSP585) drives a continuous decline below baseline levels. Novel analysis of agricultural systems reveals a critical tipping point: under SSP585, the proportion of degrading cropland escalates from 36.7% to 63.2%, transitioning the sector from a net carbon sink to a net source after 2070. These findings provide quantitative evidence that future SOC stability is not merely a climatic outcome but is critically determined by policy-driven land-use choices, offering a data-driven basis for immediate intervention in threatened agricultural zones.