Comparing trends of crop and pasture in future land-use scenarios for climate change mitigation

Abstract

Revegetation of former agricultural land is a key option for climate change mitigation and nature conservation. Expansion and abandonment of agricultural land is typically influenced by trends in diets and agricultural intensification, which are two key parameters in the Shared Socioeconomic Pathways (SSPs). Datasets mapping future land dynamics under different SSPs and climate change mitigation targets stem from different scenario assumptions, land data and modelling frameworks. This study aims to determine the role that these three factors play in the estimates of the evolution of cropland and pastureland in future SSPs under different climate scenarios from four main datasets largely used in the climate and land surface studies. The datasets largely agree with the representation of cropland at present-day conditions, but the identification of pastureland is ambiguous and shows large discrepancies due to the lack of a unique land-use category. Differences occur with future projections, even for the same SSP and climate target. Accounting for CO₂ sequestration from revegetation of abandoned agricultural land and CO₂ emissions from forest clearance due to agricultural expansion shows a net reduction in vegetation carbon stock for most SSPs considered, except SSP1. However, different datasets give differences in estimates, even when representative of the same scenario. With SSP1, the cumulative increase in carbon stock until 2050 is 3.3 GtC for one dataset, and more than double for another. Our study calls for a common classification system with improved detection of pastureland to harmonize projections and reduce variability of outcomes in environmental studies.

Keywords

Natural forest regrowth / Scenarios / Agriculture / Climate change mitigation

CRediT authorship contribution statement

Maxime Malbranque: Data curation, Formal analysis, Software, Validation, Visualization, Writing – original draft. Xiangping Hu: Data curation, Methodology, Software, Writing – original draft, Writing – review & editing, Validation. Francesco Cherubini: Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Writing – review & editing.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This research was funded by the Norwegian Research Council through the project MitiStress (Grant No. 286773).

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.geosus.2024.05.003.

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