A data-driven framework to quantify nature -based carbon removal from historic silvoarable landscapes

Abstract

Accurately quantifying the net climate impact of nature-based carbon removal remains a major challenge, particularly in agricultural landscapes where historic land-use transitions are often overlooked. This study introduces a data-driven framework for evaluating the long-term carbon sequestration potential of traditional agroforestry systems in Northern Italy’s Po-Venetian Plain, one of Europe’s most carbon-impacted rural regions. Drawing from detailed historical land use records (1929–2024), we reconstructed the spatial extent and biophysical characteristics of the Coltura Promiscua silvoarable system (a multifunctional landscape combining trees, vines, and cereals) now nearly extinct due to 20th-century agricultural intensification. Using Monte Carlo simulations, coupled with Sobol sensitivity analysis, we estimate a mean carbon stock of 75.4 t C ha⁻¹ (95% CI: 50.4–101.6) for the historic system, with soil organic carbon beneath trees emerging as the dominant driver of uncertainty. Our scenario-based modeling quantifies the carbon impact of agroforestry abandonment and explores six future management scenarios. Results show that restoring silvoarable systems could increase regional carbon sequestration by 12% matching the carbon gains of converting 25% of farmland to forest—without displacing agricultural production. This research bridges environmental history, remote sensing, and ecosystem service science to inform transparent carbon accounting. It highlights how reviving traditional land-use strategies can complement afforestation, improve regional-scale modeling, and support the development of robust metrics for project-scale climate impact. Our findings have direct implications for climate-smart agriculture policies and carbon markets targeting multifunctional rural landscapes.

Plain-language Summary

Traditional agroforestry systems (the integration of trees and crops on the same plot of land) were once widespread across Europe, but have nearly disappeared due to widespread of industrial agriculture. In this study, we focus on Northern Italy and use historical land records from 1929 to 2024 along with computer simulations to estimate how much carbon these landscapes once stored and how much could be restored through land-use changes today. We examine a system called Coltura Promiscua, which combined mulberry trees, grapevines, and cereals within the same field. Our results show that restoring these historic systems could significantly boost regional carbon storage, achieving climate benefits comparable to afforesting one-quarter of the farmland, but without taking land out of food production. We combined historical data, allometric equations, and statistical modeling to develop a reproducible method for calculating the carbon impacts of land management changes. This research offers a science-based approach for evaluating the climate benefits of restoring traditional farming practices. It demonstrates how historical land-use knowledge can inform modern carbon removal strategies and support nature-based solutions that are both climate-effective and culturally meaningful.