Observed differences between paddy and upland croplands in soil organic carbon (SOC) and soil inorganic carbon (SIC) may reflect environmental and data-provenance imbalances rather than land-use effects. We reconstructed independent SOC and SIC profile datasets across China, harmonized depths, and separated full-sample comparisons from a prespecified comparable subset. Among all topsoil SOC profiles retained after applying the inclusion criteria (334 paddy, 347 upland), the median Upland-minus-Paddy contrast was −2.12 g kg−1; within the shared subset (97/95), it attenuated to −0.35 g kg−1 (95% interval, −1.74 to 1.55). For 97 paddy soils, changing only the land-use indicator to upland while holding observed soil and environment states fixed yielded a mean SOC contrast of −0.58 g kg−1 (joint 95% interval, −1.02 to −0.15), with 78.4% negative. A layer-resolved Extra Trees S-learner supported this scenario with out-of-fold R2 = 0.72 and mean R2 = 0.72 across ten spatial partitions. The shared topsoil SIC subset retained only 9 paddy and 7 upland profiles, so adjusted SIC could not be estimated. Aridity index (AI) stratification showed the strongest negative SOC contrast in more humid high-AI croplands (−1.08 g kg−1; −1.62 to −0.56), whereas low- and middle-AI strata crossed zero; the high-minus-middle difference was −1.29 g kg−1 (−2.09 to −0.60). Among comparable croplands, observed topsoil SOC differed little between paddy and upland fields, but model predictions indicated lower SOC under upland land use, particularly in humid regions. These results suggest a modest SOC advantage of paddy croplands, while SIC differences remain unresolved.

Soil organic carbon (SOC) sustains ecosystem productivity, soil health, and sequesters atmospheric CO2. Straw return (StrawR) effectively compensates for carbon (C) losses by SOC mineralization in croplands. Quantifying the straw-derived SOC and straw conversion efficiency (SCE; the percentage of straw C converted to SOC) enables a direct assessment of C sequestration potential. This study integrates 13C isotopic tracer data with machine learning approaches to evaluate straw-derived SOC and SCE. A random forest model was further used to identify the key environmental and management drivers controlling straw-derived SOC and SCE, and to extrapolate their spatial patterns at the global scale. Straw-derived SOC content decreased over time, primarily due to the relative accumulation of recalcitrant compounds. Such dynamics are typically mediated by changes in microbial metabolic strategies in response to shifting resource availability. Random forest analysis identified StrawR amount, straw particle size, and soil bulk density (BD) as the key drivers of straw-derived SOC content (IncMSE percentages: 42%, 20%, and 19%, respectively). High soil BD potentially reduces soil aeration and suppresses microbial metabolic capacity, reducing C sequestration. Machine learning predictions indicate a straw C residual ratio of 17 ± 3.4% after 1 year and a global average SCE of 10 ± 1.1% after 5 years of StrawR, which supports our hypothesis that initial StrawR practices elevated C sequestration potential and SCE compared with prolonged StrawR application. Assuming 100% global adoption, StrawR offers a theoretical maximum biophysical potential of 1.7 Pg C yr−1 over five years. This maximum capacity would theoretically offset 52% of agricultural CO2 emissions and 16% of total anthropogenic CO2 emissions. This study addresses critical gaps in straw conversion dynamics and updated estimates of C sequestration capacity, highlighting the contribution of StrawR as a climate change mitigation strategy.

IPCC Tier 1 and Tier 2 soil organic carbon (SOC) estimation methods were originally designed for national inventories and involve considerations for accounting convention. Their calculations may affect the results of life cycle assessment (LCA) when SOC balance is included. This study aims to evaluate how the scaling and time-based equilibrium assumptions used in IPCC Tier 1 and Tier 2 methods influence SOC stock estimations from their mathematical logic, and to quantify the impacts in a product-level LCA for Finnish wheat production. We compared the mathematical logic of IPCC Tier 1 and Tier 2 methods against a basic equation that accounts for both initial and newly formed SOC stocks. The comparisons were further parameterized using local data for Finland and integrated into a cradle-to-gate attributional LCA to determine the carbon footprint of wheat production, using 1 kg of wheat grain dry matter yield as the functional unit. The results showed that soils with higher initial SOC storage tended to lose more C when receiving equal C input. Compared with the basic equation, the scaling method with local coefficient constrained the range of SOC loss. For different initial SOC stocks, the net greenhouse gas balance (NGHGB) for SOC balance ranged 0.19–0.75 kg CO2-eq kg− 1 of yield using the basic equation, but the range was narrowed to 0.34–0.56 kg CO2-eq kg− 1 of yield with scaling equation. Both calculations revealed significant C loss from soil compared to the NGHGB for wheat, which was 0.56 kg CO2-eq kg− 1 of yield when SOC was not considered. However, the 20-year time-based steady SOC storage did not account for the NGHGB resulting from the SOC storage changes. The carbon footprint from soil carbon balance is considerable compared with other processes for crop production. The SOC balance is influenced by initial SOC storage, a factor that may be overlooked in time-based steady SOC models, while the scaling method underestimates the variations in SOC loss across different initial SOC stocks.

Integrated nutrient and field management is key to farmland soil health, but evaluation frameworks for improving soil quality index (SQI) through combined organic amendments under reduced nitrogen (N) input are still limited. Hence, we conducted a three-period field experiment to examine the effects of green manure (GM) and its synergy with biochar (GB) on SQI under reduced N input. Results were as follows: (1) GM and GB rapidly and persistently improved the SQI by 66.67–116.67

Autumn freeze-thaw cycles (AFTCs) represent critical transitional periods influencing greenhouse gas emissions in permafrost peatlands, yet field-based evidence regarding how freeze-thaw variability interacts with peatland type to affect carbon flux dynamics remains limited. Here, we conducted a field observational study across three permafrost peatland types in the Great Hinggan Mountains, Northeast China, including Calamagrostis angustifolia peatland (CA), Larix gmelinii-Sphagnum peatland (LG-SP), and Eriophorum vaginatum peatland (EV). Carbon dioxide (CO2) and methane (CH4) fluxes were monitored during AFTCs under different freeze-thaw variability stages to evaluate relative influences of peatland type, freeze-thaw variability, and their interaction on greenhouse gas dynamics. CO2 fluxes ranged from -266.93 to 209.34 mg m-2 h-1, whereas CH4 fluxes ranged from 1.00 to 2.23 mg m-2 h-1 across peatland types. Most peatlands functioned as net CO2 sources during AFTCs; however, the LG-SP peatland exhibited temporary net CO2 uptake under severe freeze-thaw variability, indicating ecosystem-specific differences in carbon exchange responses during AFTCs. General linear model and effect-size analyses revealed contrasting response patterns between the two greenhouse gases. For CO2, the interaction between peatland type and freeze-thaw variability explained a greater proportion of flux variability (η2p = 0.057) than freeze-thaw variability alone (η2p = 0.004). In contrast, CH4 fluxes were primarily associated with peatland type (η2p = 0.557), followed by the interaction effect (η2p = 0.217), whereas freeze-thaw variability alone explained only a small proportion of variation (η2p = 0.018). These contrasting effect-size patterns indicate that CO2 and CH4 responded differently during AFTCs across permafrost peatland ecosystems. The results highlight the importance of considering peatland type and freeze-thaw variability when evaluating greenhouse gas dynamics during AFTCs. This study provides field-based evidence that autumn carbon dynamics in permafrost peatlands are characterized by both ecosystem-specific and gas-specific response patterns during AFTCs.

Organic matter plays an important role in the health and productivity of soils, but its depletion is a common problem in households in low-income countries. This is due to lack of and competing uses for organic resources, and limited information on recycling methods. Therefore, here we review low-cost and labour-efficient innovations to improve recycling of organic wastes, stabilising residues so that soil organic matter can be increased with less inputs and enhancing nutrient content to produce a more effective organic fertiliser. Composting, anaerobic digestion and pyrolysis are all processes that stabilise organic matter. Innovations in treatments are needed to improve stabilization and control the release of nutrients so that they are available to crops in the right amounts and at the right time. This can be achieved by maintaining appropriate treatment conditions: for composting, carbon to nitrogen ratio 25–35, carbon to phosphorus ratio ∼50, pH 5.5–8.5 and 50%–60% moisture content; for anaerobic digestion, carbon to nitrogen ratio 20–35, bulk density 0.6–0.8 g cm ^−3 , lignin content < 7.5%, pH 6.8–7.4 and moisture content 85%–95%; and for pyrolysis, carbon to nitrogen > 40 and moisture content < 20%. Different methods to achieve these ideal conditions are discussed, including appropriate choice of treatment method, co-composting/co-digestion for ideal nutrient content, enhancing nutrients using collected urine, nitrogen-fixing plants, bioslurry or by inoculating with bacterial communities, absorbing excess nutrients on biochar, adjusting pH using wood ash or biochar, pre-treatment to break down lignin and cellulose, and designs to achieve ideal moisture and temperature. Innovations should also ensure that treatment processes do not overuse or compete with other important household resources, such as finances, water or labour. We draw together findings to identify methods with most potential to improve soils in low-income countries, providing decision tables to guide selection of approaches for different contexts.

ABSTRACT The concept of soil is increasingly being examined within a planetary context, prompting renewed attention to the physical conditions that enable surface materials to support life. In parallel, planetary habitability has emerged as a framework for defining the minimum resources and conditions required for biological activity, independent of whether life is currently present. Here, we apply habitability principles to soils not to assert the presence of life, but to distinguish clearly between soil formation, biological viability, and functional performance. Habitability formalises a binary set of physical and chemical requirements—including accessible energy, liquid water, essential elements, and viable environmental conditions—that define whether an environment can support life in principle. By treating habitability as a state that applies to already formed soils, rather than as a defining criterion for soil existence, we resolve long‐standing ambiguity around the role of biology in soil definition. This separation leads to a tightened planetary definition of soil as ‘an organised planetary surface system, comprising generally loose mineral and/or organic material, formed through sustained genesis via water‐mediated surface coupling that produces internal physical, chemical, and/or biological organisation and enables system evolution through time, irrespective of the presence of extant life.’ Within this framework, soil health, soil quality, and soil security operate as continuous descriptors of function only within habitable or potentially habitable soils, while degradation is conceptualised as a contraction of habitable state space. Habitability thus provides a physically grounded foundation for interpreting soil function, selecting indicators, and differentiating soils from sediments and regolith across Earth and other planetary environments.

Rice production underpins food security but relies heavily on nitrogen (N) fertilization, much of which is lost as gaseous emissions. Dinitrogen (N2) represents the largest N loss, yet its sources remain poorly constrained because biological dinitrogen (N2) fluxes are difficult to quantify against the atmospheric background. Here, we apply an in situ 15N tracing-membrane inlet mass spectrometry (15N-MIMS) technique to simultaneously measure N2, ammonia (NH3), and nitrous oxide (N2O) emissions and partition their soil- versus fertilizer-derived origins across the growing season in conventional japonica rice and hybrid rice. We find that soil organic N (SON) accounts for most N2 emissions (72 to 75%), overturning the prevailing assumption that fertilizer dominates this loss pathway, which is independently confirmed by a 14-y fertilization experiment. In contrast, NH3 originates mainly from fertilizer (71 to 77%) and N2O derives from both sources in near-equal proportions. We identify a previously unrecognized "microbial N pump", in which rapid microbial assimilation of fertilizer-derived ammonium (NH4+) induces stoichiometric imbalance and stimulates SON mineralization, mobilizing soil-derived NH4+ that ultimately fuels N2 emissions, with depleted SON partially replenished through microbial N turnover. Neglecting SON contributions causes systematic overestimation of fertilizer-derived N2 and NH3 losses by ~35%. Hybrid rice increases yield by 59% and reduces yield-scaled gaseous N losses by 43% through enhanced fertilizer uptake and microbial N use efficiency. Together, these findings reveal an underappreciated pathway of fertilization-driven soil N losses, revise N budgets for flooded rice systems, and demonstrate that cultivar-informed management can simultaneously enhance rice productivity and environmental sustainability.

Soils underpin many ecosystem services, including food production, through functions such as organic matter decomposition. These functions are increasingly threatened by soil degradation, especially in climate-vulnerable regions, such as sub-Saharan Africa, where unstable soils are prone to severe erosion. As soils continue to degrade, farmers face multiple challenges; they cannot afford accurate tests to assess soil, their livelihoods are constrained by demand for food, fuel and water, and competition for valuable resources hampers farming. Hence, there is a pressing need for accessible tools to assess soil health and methods to provide tailored advice on resilient, climate-smart agricultural management and optimal use of resources. This narrative review offers a comprehensive overview of key issues and potential solutions. We highlight tools and approaches that can support farmers to improve soil and secure livelihoods. Practical indicators and field-ready tests are evaluated, with examples from Ethiopia, but tailored to support farmers and advisors across sub-Saharan Africa and other developing countries. A wide range of tests are reviewed, including physical, biological, chemical, function and service-related tests, drawing on scientific and farmers knowledge. Science-based tests require expertise, equipment and incur costs, while locally-derived tests are affordable and seamlessly applicable. We also review Nature-based Solutions for improving soil quality, and assess them against factors such as labour, costs, and crop production. There is no single universally applicable practice; suitability depends on farmers’ priorities and circumstances. Therefore, we explore predictive methods—mechanistic, process-based soil models, data- and knowledge-driven Artificial Intelligence and systems models—to simulate the impact of practices on soil and farm dynamics. Promising approaches include hybrid approaches assimilating data, physics and knowledge through digital soil mapping. Overall, this review emphasizes the need to empower farmers with accessible tools and methods to harness Nature-based Solutions, build climate resilience and secure sustainable futures for generations ahead.

Stabilized soil organic carbon is the most persistent fraction of soil carbon and plays a key role in long-term climate mitigation, yet its global distribution remains poorly constrained. Here we integrate georeferenced soil profiles with a machine learning model to map stabilized soil carbon in the upper one meter of soils worldwide. Global stabilized soil carbon is estimated at 1304 petagrams of carbon, representing about half of total soil carbon and concentrated in wetlands and cold-temperate regions. Soil properties explain most of the spatial variation, whereas climate and management effects show threshold responses. We further define soil negative carbon potential, the proportion of stabilized carbon in total soil carbon, as an indicator of stabilization efficiency and mitigation potential. Increasing this metric is associated with lower greenhouse gas emissions and improved economic outcomes with minimal yield trade-offs. These results provide benchmarks for Earth system models and inform soil-based climate mitigation strategies. Stabilized soil organic carbon totals 1304 pentagrams carbon globally about half of total soil carbon concentrated in wetlands and cold regions shown by mapping upper one-meter soils using georeferenced soil profiles and high precision machine learning models.

Abstract Grasslands support the majority of global livestock production systems while providing vital ecosystem services. Expansion of the livestock sector over recent decades has however placed enormous pressure on grasslands, with increasing greenhouse gas emissions that challenge the aspirations of climate mitigation. Here, we reviewed (a) climate policies pertaining to livestock and grasslands underpinning the Nationally Determined Contributions (NDCs) of 16 countries or regions, and (b) representation of grassland and livestock sectors in five contemporary integrated assessment models (IAMs). We find that mitigation policies reported in NDCs and Biennial Update/Transparency Reports (BURs/BTRs) remain limited in their specification of clearly defined forward‐looking quantitative mitigation targets for ruminant livestock and grassland systems, despite their substantial contribution to agricultural emissions. At the same time, many reported policies are articulated in ways that support inventory‐compatible, retrospective accounting. Contemporary IAMs, however, employ a highly simplified and aggregated representation of grassland–livestock interactions, with limited consideration of management intensity, degradation, restoration, and management‐induced carbon dynamics. Taken together, these features reveal an information imbalance at the interface between policy articulation and model‐based quantitative assessment, which may limit the transparency and cross‐country comparability of evaluations of mitigation pathways in grassland and ruminant livestock systems.

Soil carbon sequestration (SCseq) is fundamental to global climate mitigation initiatives; however, growing evidence indicates an expanding disparity between carbon (C) accumulation and its long-term persistence. This article aims to integrate recent advances in microbial ecology, mineral biogeochemistry, and nutrient stoichiometry to examine why increases in soil C (SC) stocks do not necessarily translate into long-term persistence. The article introduces the fragile sink framework, wherein sink durability reflects the balance between internal C throughput and the strength of stabilizing barriers. Global change drivers, including warming, elevated CO2 (eCO2), nutrient enrichment, and anthropogenic disturbance, can accelerate internal C turnover, resulting in soils that are structurally younger, more reactive, and increasingly vulnerable to rapid C loss despite stable or rising stocks. The article shows that destabilization begins at predictable vulnerability frontiers where stoichiometric gating and mineral protection are overridden, while recovery is constrained by kinetic and architectural hysteresis. Thus, it recommends a shift away from stock- and input-centric C farming toward process-centric C defense, emphasizing the protection of slow-cycling, kinetically protected pools under increasing turnover.

Crop diversification plays a vital role in sustainable agriculture by enhancing ecosystem functions and improving resource efficiency. It is a key strategy to ensure food security while optimizing water and nitrogen use, addressing the challenges posed by limited resources, and supporting environmental preservation. This review synthesizes current knowledge regarding the mechanisms and regulatory pathways through which diversified cropping systems enhance water productivity (WP) and agronomic efficiency of nitrogen (AEN), and partial factor productivity of nitrogen (PFPN). It also identifies existing challenges and proposes priority directions for future research. This analysis focuses on studies of diversified cropping systems, such as intercropping, crop rotation, and multiple cropping, that enhance WP, AEN, and PFPN. We elucidate the underlying mechanisms driving these improvements by incorporating recent findings. Diversified cropping systems enhance WP, AEN, and PFPN by reducing water and nitrogen losses, improving soil physicochemical properties, regulating interspecific interactions, enhancing crop physiological performance, and stimulating beneficial microbial activity. These benefits are optimized through strategic crop combinations, integrated water–nitrogen management, improved tillage and mulching practices, and precision monitoring and decision-support systems. Despite these advantages, challenges remain in crop variety selection, mechanization, and the comprehensive evaluation of socio-economic and ecological outcomes. Future research should emphasize system adaptability to climate variability, the molecular mechanisms underlying water and nitrogen use, water–carbon–nitrogen coupling, artificial intelligence (AI)-assisted system design, and implementation-oriented strategies. The efficacy of diversified systems and associated management practices is strongly influenced by local climatic conditions, soil properties, and socio-economic constraints. This review highlights the need for an integrated framework combining agronomic, physiological, and molecular perspectives to better understand and regulate how crop diversification enhances WP, AEN, and PFPN. The findings provide a theoretical and technological foundation for promoting diversified, resource-efficient, and climate-resilient cropping systems, particularly in irrigated regions of Northwest China and similar climatic environments.

Agroforestry has been promoted as one solution to make agriculture more ecologically sustainable. While research has examined its effects on biodiversity and on climate change mitigation and adaptation separately, comprehensive reviews linking these outcomes remain lacking. This review fills that gap. We searched six academic databases in June 2025, retrieving 12,175 unique records. Screening against pre-defined criteria yielded 258 studies reporting at least one biodiversity and one climate outcome. Findings reveal a strong concentration of studies on soil biota and plants in agrosilviculture systems with short-term, observational designs. When biodiversity is studied alongside climate change adaptation, outcomes cluster around soil nutrients and chemical properties, with very few studies addressing ecosystem process, such as nutrient cycling and ecosystem regulation. Studies on biodiversity and mitigation are centred around soil carbon. Overall, fruit trees are more common than timber trees, though, continental differences in system characteristics exist. There is a significant knowledge gap for studies on vertebrates and long-term studies. Further, the evidence comes from a few countries leaving significant geographical gaps. The review underlines how current research falls short on capturing the complexity and ecological resilience of agroforestry systems. Cross-taxa, system-level perspectives offer valuable insights into the synergies between biodiversity and climate mitigation and can help to identify win-win situations for managing production landscapes. We provide the findings as an interactive database enabling stakeholders to explore the evidence by outcome and context, and discuss how to improve the global relevance of agroforestry research and help avoid overly narrow development pathways.

ABSTRACT Perennial energy crops (PECs) are increasingly being recommended for cultivation on marginal lands to support the bioeconomy and promote soil restoration, owing to their low input requirements and large potential for soil organic carbon sequestration. However, the effects of the cultivation of PECs on the trade‐offs or synergies among soil functions, and consequently on ecosystem multifunctionality (EMF), remain unclear, hindering large‐scale adoption. We conducted our measurements in a long‐term field experiment that was established a decade ago, where Miscanthus and switchgrass were cultivated alongside a native C3 grass mixture (Cyperus rotundus L. and Setaria viridis L.) as reference to assess the effects of PECs on soil multifunctionality. We assessed 10 ecosystem functions grouped into provisioning, supporting, and regulating services. The results demonstrate that Miscanthus and switchgrass cultivation elevated the overall EMF by an average of 5.29‐fold over the C3 native grass control, with supporting, regulating, and provisioning services increasing by 2.08, 7.27, and 43.98‐fold, respectively. Specifically, the two PECs improved all 10 measured soil functions, with the exception of abiotic stress regulation under switchgrass cultivation. Miscanthus outperformed switchgrass by 41.54% in supporting services and 81.09% in provisioning services, resulting in higher EMF. Moreover, strong positive relationships were observed among the three service categories, indicating that the cultivation of PECs improves EMF consistently without significant trade‐offs. These findings suggest that cultivating PECs on marginal land can simultaneously provide sustainable biomass feedstock and enhance soil health, supporting the feasibility for larger‐scale deployment.

Active (seeding native grasses) and passive (natural recovery via degradation factor removal) restoration practices regulate soil organic carbon (SOC) recovery in degraded grasslands through distinct mechanisms. We quantified microbial- (amino sugars) and plant-derived (lignin phenols) C contributions to SOC after a 10-year restoration of degraded grasslands on the Qinghai-Tibetan Plateau. Active restoration increased SOC to 17.8 and 18.1 g·kg-1 in the topsoil and subsoil, respectively, whereas passive restoration maintained SOC at degraded levels (9.3 and 3.5 g·kg-1). Microbial-derived C contributed 31-37%, while plant-derived C contributed only 1-2% of the SOC pool under active restoration. Active restoration accelerated lignin oxidation while driving an influx of plant-derived phenols into the subsoil, which stimulated microbial turnover and fueled the microbial carbon pump. Microbial necromass accumulation outpaced the direct preservation of recalcitrant plant residues, with fungal necromass dominating the stable microbial-derived C pool. This disproportionate accumulation of biochemically persistent fungal necromass drives long-term SOC sequestration. Land managers should prioritize active grass seeding to maximize root inputs, stimulate fungal dominance, and secure long-term grassland carbon sinks.

Flooded arable fields are considered to emit large amounts of N2O and CH4, but their regional-scale measurements are missing. Here, we measured N2O and CH4 concentrations and calculated their emissions from the flooded maize fields (FMFs) across North China Plain, one of the most important arable regions in China, after the heaviest rainfall in 2023 since 1960s. Our results revealed that both the concentrations and fluxes of N2O and CH4 were high (50.83 +/- 45.41 nmol l(-1) and 1.91 +/- 2.38 mu mol m(-2) h(-1) for N2O, 14.49 +/- 19.71 mu mol l(-1) and 0.69 +/- 0.92 mmol m(-2) h(-1) for CH4). The mean emission factor (EF) of N2O (0.0043) was slightly higher than that of the IPCC default value for paddy fields (0.004), while that of CH4 was about eight-folds larger. Cumulatively, the N2O and CH4 emissions from the completely flooded maize fields were estimated to be 23.3 +/- 18.6 Gg CO2-eq, with CH4 contributing over 90%, and accounted for similar to 0.91% of the regional budget, although the flooding areas were only 0.2% of the entire fields. This emission estimate should be significantly larger if the partly flooded maize fields were included. These findings highlight that flooded arable fields are significant sources of N2O and CH4 at regional scales, and should be included in future estimations.

Zero Hunger (Sustainable Development Goal 2, SDG 2) serves as a cornerstone for achieving global sustainable development, and is intricately linked with other SDGs exhibiting complex and multifaceted synergies and trade-offs. While the interconnections among indicators referring to food system within environmental domain have been widely investigated, interactions among indicators of all three pillars (social, economic, and environmental) remain under-researched. This study leverages the 2020 Sustainable Development Solutions Network (SDSN) assessment data to construct a global SDG 2-related network comprising 38 targets and 61 indicators, and examine how this network’s structure varies across income levels. The results reveal high-income countries (HICs) have achieved notable advancements in eradicating hunger and improving agricultural productivity, while facing unique challenges of overnutrition. Low-income countries (LICs), by contrast, face persistent constraints in agricultural productivity, infrastructure, and resource access. Across the global SDG 2-related network, SDG 2 targets show direct synergies with 31 targets in other SDGs, covering all studied economic targets, whereas 10 targets exhibit direct trade-offs, all of which are related to the environment. The share of trade-offs declines as income rises, from 28 % in LICs to 13 % in HICs. Synergies mainly occur between economic targets in LICs, while they often occur between economic and social targets in HICs. Trade-offs linked to environmental targets indicate LICs rely more on natural resources, whereas HICs face environmental spillovers. These findings underscore the need for tailored strategies, with LICs prioritizing agricultural productivity and infrastructure, while HICs addressing social equity, social distribution, and environmental sustainability.

Because peatlands store vast amounts of carbon and are highly sensitive to climate warming, an accurate estimation of the size of their global carbon pools is essential for understanding the terrestrial carbon cycle and future climate feedback. Yet current estimates remain highly uncertain due to inconsistent definitions, different estimation methods, incomplete field sampling, and limited information on peatland extent and depth. Here we synthesize recent advances in peatland carbon accounting, including peatland definitions, carbon sink function, and carbon pool components. We compile estimates globally, and for northern and tropical peatlands, and evaluate the main drivers of uncertainty across methods. Current estimates of global peatland extent range from ~3.8 to 4.9 × 106 km2, and corresponding carbon pool estimates span 238-612 Gt C, reflecting a two- to three-fold spread. Although intact peatlands continue to sequester ~0.1-0.3 Gt C year-1, degraded peatlands emit ~1.9 Gt CO2-eq year-1 (~4% of anthropogenic greenhouse gas emissions), highlighting their dual role as both a carbon sink and a rapidly mobilizable carbon source. We show that peatland area and peat depth are the dominant sources of global uncertainty, while bulk density and soil organic carbon content become critical at regional scales. We propose a pathway toward reducing this uncertainty, based on harmonized peatland definitions, improved depth mapping, and integration of remote sensing, process-based models, and machine learning. These advances are essential for producing policy-relevant, climate-relevant peatland carbon assessments.