The neglected role of abandoned cropland in supporting both food security and climate change mitigation

The study addresses how abandoned cropland can contribute to food security and climate change mitigation amid growing land scarcity due to population growth and increasing food demand. While cropland expansion is projected (25–226 Mha in the next three decades under SSPs), it risks high-biodiversity areas. The food system contributes about one-third of anthropogenic GHG emissions, and land-based mitigation (e.g., reforestation) requires vast areas, potentially conflicting with agricultural needs. Cropland abandonment is widespread due to biophysical, socioeconomic, institutional, and conflict-related drivers. However, systematic, spatially explicit assessments of the potentials, trade-offs, and synergies of recultivating versus reforesting abandoned cropland have been lacking. The authors pose three research questions: (1) How much abandoned cropland is suitable for recultivation and for reforestation via natural regrowth, and what are their respective food and climate mitigation potentials? (2) How can trade-offs between these purposes be balanced? (3) How can synergies and achievable potentials be maximized through spatial prioritization and management strategies.

Prior work documents extensive cropland abandonment alongside continued cropland expansion, with hotspots in Europe, Russia, Central and East Asia, and the Americas. Studies link abandonment to institutional transitions (e.g., post-Soviet changes), conflicts, land degradation, and biophysical constraints, and note its potential ephemerality. Past assessments often focus on a single objective (e.g., recultivation only), insufficiently considering alternative uses like reforestation. Remote sensing estimates show substantial gross abandonment (e.g., 79 Mha from 2003–2019) and predict continued abandonment in hotspots. Land-based climate solutions, including reforestation, are central to many NDCs but compete with agricultural land demands. Emerging work highlights the feasibility of recultivation and natural regeneration for carbon sequestration, but comprehensive, spatially explicit global analyses of trade-offs and synergies across these aims have been limited.

Study period: 1992–2020 for mapping; potentials assessed for 2020–2050. - Mapping abandoned cropland: Used ESA-CCI annual land-cover (300 m) and FAO’s definition (cropland not used for at least five consecutive years, excluding built-up). Steps: (1) aggregate six cropland classes; (2) apply a 5-year moving-window temporal filter to improve consistency; (3) consider only historically stable cropland (cropland during 1992–1997); (4) exclude pixels converted to settlement/wetland and pixels re-cultivated later. Accuracy assessed via disproportionate stratified sampling (1,656 samples), visually interpreted with very high-resolution imagery and Landsat; reported overall accuracy 83%, user’s 95%, producer’s 77%, F1 0.85; derive error-adjusted area estimate (101 ± 35 Mha). - Suitability for recultivation: Identified historically recultivated pixels (abandoned then returned to cropland) to train a MaxEnt model (v3.4.4) using normalized biophysical and socioeconomic predictors: integrated agroecological suitability, market accessibility, travel time to settlements, population density, adjacent cropland density, distance to stable cropland, abandoned cropland density, INFORM risk index, and annual economic loss due to natural hazards. Pixels with recultivatability > 0.2 deemed suitable; protected areas (UNEP/IUCN) masked out. - Food production potential: Considered 15 major crops (barley, cassava, groundnut, maize, millet, oil palm, potato, rapeseed, rice, sorghum, soybean, sugarbeet, sugarcane, sunflower, wheat). Used GAEZ v4 present-day harvested areas and actual yields (2009–2011, rain-fed) downscaled to 5 arc-min. Converted harvest-weight yields to dry-weight calorie yields using FAO/GAEZ factors; integrated pixel productivity as area-weighted average across crops; deducted food loss (FAO Food Loss Index, crop- and region-specific) and a uniform 17% food waste (UNEP). Estimated consumer-level calorie production potential assuming recultivated areas achieve current active-cropland productivity in the same pixel. Also calculated immediate emissions from clearing accumulated aboveground biomass if recultivated (assuming immediate oxidation) and 30-year averaged equivalent. - Suitability for reforestation via natural regrowth: Overlapped abandoned cropland with Potential Natural Vegetation (PNV) map classes ‘forest’ and ‘woodland’ to identify suitability. - Climate mitigation potential: Computed net annual mitigation for next 30 years as carbon accumulation from natural regrowth (above- and belowground biomass; aboveground rates from global machine-learning map based on 13,112 measurements; belowground via IPCC root-to-shoot ratios) minus emissions from clearing accumulated aboveground biomass on areas allocated to recultivation (natural regrowth areas used Cook-Patton et al. accumulation; grass/shrub/bareland used carbon stock map by Spawn et al.). Soil organic carbon changes excluded due to limited, inconsistent evidence. Uncertainty propagated using the sequestration map’s error layer (1 SD across model ensemble). - Scenario simulations (trade-offs and synergies): Allocated each 300-m abandoned cropland pixel to either recultivation or reforestation under multiple scenarios, varying total area used, allocation shares, and allocation strategies (randomized vs spatially prioritized by highest productivity/sequestration). Four representative scenarios showcased: maximizing food production; maximizing climate mitigation; equal allocation; maximizing combined potential (assign by comparative advantage of productivity vs sequestration). Metrics include achieved potentials and combined potential (sum of achieved food and climate potentials relative to their respective maxima). - Spatial prioritization analysis: Compared outcomes with vs without prioritization across different percentages of area used; examined distributions of allocated cropland productivity and sequestration rates. - Improvement levers: Explored hypothetical enhancements: shift rain-fed to irrigated yields; close yield gaps to attainable yields (high-input, market-oriented); halve food waste and loss; optimize crop spatial allocation; future climate effects (RCP4.5/RCP8.5 ensemble). For reforestation, assessed active reforestation (outside protected areas) vs natural regrowth. Quantified freed-up land effects on the alternate objective. Data and code shared via Zenodo.

- Extent and distribution: Identified 101 Mha (95% CI: 66–136 Mha) of abandoned cropland (1992–2020), averaging 3.6 Mha yr−1; equals 7.0% of 1992 active cropland and 6.4% of 2020 active cropland. Concentrated in Asia (33 Mha), Europe (22 Mha), Africa (19 Mha), with Russia (12.4 Mha), China (8.7 Mha), Brazil (8.4 Mha) prominent. - Suitability: 61 Mha suitable for recultivation (unrecultivated to date) and 83 Mha suitable for natural reforestation; 50 Mha suitable for both. - Food potential: Recultivating all suitable areas could produce 363 Peta-calories yr−1 (consumer level), feeding an estimated 292–476 million people per year depending on diet and intake. Clearing accumulated biomass for recultivation would emit about 4.7 GtCO2 instantly, equivalent to 156 MtCO2 yr−1 averaged over 30 years. - Climate mitigation: Reforesting all suitable abandoned cropland via natural regrowth could sequester about 1,080 MtCO2 yr−1. This could meet on average 17% of unconditional NDC reduction targets across 120 countries (e.g., USA 0.4%, Indonesia 19%, Ethiopia 49%) and corresponds to 3–7% of global reductions needed for a 2°C pathway (SSP2-2.6, 2020–2050). - Trade-offs across scenarios: Achievable food production ranges from 29 to 363 Pcal yr−1 and climate mitigation from 290 to 1,066 MtCO2 yr−1 across scenarios. The maximizing food scenario allocates 61 Mha to recultivation and 33 Mha to reforestation (127% combined potential), while maximizing climate allocates 83 Mha to reforestation and 11 Mha to recultivation (107% combined). Equal allocation yields 121% combined. The maximizing combined potential scenario achieves the highest integrated outcome (143% combined), concurrently reaching 79% of max food (295 Pcal yr−1) and 72% of max climate (667 MtCO2 yr−1) by assigning pixels by comparative advantage. - Benefits of spatial prioritization: Prioritization increases achievable food and climate outcomes by up to 59% and 43%, respectively, relative to randomized allocation, with strongest gains when only a fraction of area is used. Using 30% of abandoned cropland, prioritization yields +29% food (max food scenario) and +19% food (max combined) and +31% carbon (max climate) and +27% carbon (max combined), versus no prioritization. To achieve the same outcomes, prioritized scenarios use on average 14% less area for recultivation and 10% less for reforestation; example: 200 Pcal yr−1 requires 19 Mha with prioritization vs 33 Mha randomized. Priority regions include Central/Eastern Europe, East/Southeast Asia, Central Africa, and South America (top countries: Russia, Brazil, China). - Potential improvements: Relative to baseline estimates, converting rain-fed to irrigated increases food potential by 62%; closing yield gaps to attainable yields by 40%; halving food waste/loss by 16%; optimized crop allocation by 74%; combined, food potential could double from 363 to 791 Pcal yr−1, or hold at 363 Pcal while freeing 27 Mha for reforestation, enabling up to 439 MtCO2 yr−1 additional sequestration (+98%). Future climate change yields marginal additional 3–12% food potential depending on forcing and water. Active reforestation (outside protected areas) raises mitigation by 53±18% and frees 17 Mha for recultivation, generating about 45 Pcal yr−1. Agricultural nature-based solutions on recultivated land can add 1.1–1.6 MgCO2e ha−1 yr−1, compared to average 11.5 MgCO2 ha−1 yr−1 for regrowing forests.

The analysis demonstrates that strategically using abandoned cropland can materially advance both food security and climate mitigation goals. Explicitly resolving trade-offs and exploiting spatial heterogeneity enable substantial synergies: allocating land by comparative advantage simultaneously captures large fractions of both maximum food and climate potentials. Spatial prioritization markedly boosts outcomes and land-use efficiency, especially under constrained resource scenarios. Reforestation offers additional co-benefits, including biodiversity, water and air filtration, and soil quality improvements, while recultivation can help offset displacement from new cropland expansion and attendant habitat loss. Improvements in water management, yield gaps, waste reduction, crop allocation, and active reforestation could further amplify achievable benefits and/or free land to support the alternate objective. The estimated climate benefits are significant in the context of national NDCs, though they must complement, not replace, decarbonization in energy and industry. Realizing these potentials will require policy measures to ensure permanence, appropriate incentives, equitable carbon markets, and alignment of increased production with accessibility and nutrition outcomes. Consideration of alternative uses (e.g., bioenergy, grassland restoration, rewilding) and local socio-ecological contexts is necessary to optimize overall land-system outcomes.

The study quantifies global abandoned cropland (101 Mha) and shows large, actionable potentials for both recultivation (up to 363 Pcal yr−1) and natural reforestation (about 1,080 MtCO2 yr−1). A spatially explicit trade-off framework reveals that allocating land by comparative advantage maximizes combined benefits (143% of combined potential), while spatial prioritization substantially increases efficiency and outcomes. The work highlights practical levers—irrigation, closing yield gaps, reducing food waste/loss, optimized crop allocation, and active reforestation—to boost potentials or free land for the alternate objective, and identifies regional priorities. These insights can guide policies and programs aimed at SDG 2, SDG 15, and Paris Agreement goals. Future research should integrate fine-scale socioeconomic costs, governance, tenure, and equity considerations; improve high-resolution monitoring of abandonment and regrowth; include soil carbon and crop life-cycle emissions where data permit; and design policy instruments to ensure permanence, avoid adverse biophysical effects (e.g., water yield, albedo), and support people-centered implementation.

- Mapping constraints: ESA-CCI’s coarse resolution and design not optimized for change detection can introduce mixed-pixel and temporal classification errors, especially in regions with small fields (e.g., Africa); early-period reliability issues (pre-2000) required temporal filtering. Validation sampling exclusions (cloudy/mixed pixels) may inflate accuracy. - Carbon accounting scope: Soil organic carbon dynamics excluded due to inconsistent evidence; belowground biomass inferred via root-to-shoot ratios; life-cycle emissions of crop production not included due to lack of spatially explicit crop-specific data; assumption of immediate oxidation of cleared biomass may overstate near-term emissions if biomass is utilized (e.g., bioenergy). - Suitability and permanence: Recultivation/reforestation suitability can be limited by conflicts, market access, labor, and policy changes; abandonment can be ephemeral without policy support, undermining permanence of benefits. - Scale and transferability: Global analyses may not align with local policy contexts and costs; many socioeconomic datasets are only country-level, limiting integration of spatially explicit costs and constraints; implementing actions requires local tenure security, indigenous/community rights, and context-specific knowledge. - Demand-side uncertainties: Dietary shifts (e.g., toward meat) and allocation of crops to feed vs food can reduce realized food security benefits. - Biophysical side-effects: Large-scale reforestation may reduce water yield in water-stressed regions and cause albedo-driven warming in high latitudes; careful planning is required.