Releasing global forests from human management: How much more carbon could be stored?

Assessing biochar's impact on greenhouse gas emissions, microbial biomass, and enzyme activities in agricultural soils through meta-analysis and machine learning

The role of biochar in reducing greenhouse gas (GHG) emissions and improving soil health is a topic of extensive research, yet its effects remain debated. Conflicting evidence exists regarding biochar's impact on soil microbial-mediated emissions with respect to different GHGs. This study systematically examines these divergent perspectives, aiming to investigate biochar's influence on GHG emissions and soil health in agricultural soils. The meta-analysis includes 2594 paired observations from 157 studies conducted between 2000 and 2024. It was found that biochar increased the presence of amoA and nosZ genes by 39.4 % and 41.7 %, respectively, while reducing the abundance of the nirS gene by 17.8 %. This led to a 13.1 % decrease in N2O emissions. Nitrous emissions were positively associated with mean annual temperature and biochar's pyrolysis temperature and dosage while inversely related to soil pH, nitrogen fertilisation rate, and biochar pH and carbon content. Biochar also regulated enzyme activity related to the nutrient cycle and increased microbial biomass carbon, nitrogen, and phosphorus by 16.6 %, 23.9 %, and 50.2 %, respectively, leading to changes in microbial community diversity. These changes contributed to a reduction in CO2 and CH4 emissions, particularly when biochar and nitrogen fertiliser were applied at doses below 21.4 t ha-1 and 242.5 kg ha-1, as predicted by machine learning models. This study offers an overview of the positive impact of biochar amendments on soil GHG emissions mitigation. The key predictive factors identified could help optimise biochar production and targeted amendments, potentially improving soil health and achieving carbon neutrality in agroecosystems.

Integrating high-resolution data and species-level traits for enhanced ecosystem projections using a dynamic vegetation model: Case study in Wallonia, Belgium

Accurate quantification of carbon dynamics is critical for developing effective climate mitigation strategies. In this study, we employed the CARAIB dynamic vegetation model (DVM) to analyze carbon fluxes and stocks (biomass and total soil carbon) in Wallonia, Belgium (1980-2070), integrating species-level traits, high-resolution land use/land cover (LULC) data, climate data, and type-1 fuzzy logic for uncertainty quantification. We provide insights into ecosystem resilience and carbon sequestration under Representative Concentration Pathways (RCPs) 2.6 and 8.5. Historical results (1980-2020) demonstrated strong model performance, with gross primary production (GPP) validation achieving R2 > 0.85 against MODIS and GOSIF datasets, and aboveground biomass correlating well with GEDI (R2 = 0.77) and ESA-CCI (R2 = 0.91) datasets. Grasslands emerged as critical carbon sinks, exhibiting the highest mean GPP (2480 g C m-2 yr-1), surpassing forests due to rapid growth and belowground carbon storage. Future projections (2021-2070) identified afforestation as a robust mitigation strategy, increasing forest GPP by 18% and total biomass by 60-110 Mt C under RCP 8.5. Under RCP 2.6, total biomass was more stable due to the milder emissions trajectory, emphasizing its potential for long-term ecosystem resilience. Interestingly, total soil carbon showed similar levels across both RCPs, indicating belowground carbon resilience despite emissions differences. Sensitivity analyses of LULC scenarios highlighted grassland resilience, with grasslands sustaining a high GPP (2604-2728 g C m-2 yr-1) and contributing significantly to soil carbon storage, while deforestation caused substantial carbon losses. These findings underscore the need for nuanced land management, integrating afforestation and grassland conservation, to enhance resilience and sustainable carbon sequestration under climate change.

Drivers of forest productivity in two regions of the United States: Relative impacts of management and environmental variables

Climate, environmental conditions, and management strategies are key factors affecting forest net ecosystem production (NEP). However, little is known about the relationship between management approaches and regional to continental-scale forest productivity. In this study, we utilized forests of the U.S. Southeast (SEUS) and Pacific Northwest (PNW), two ecologically and socio-politically distinct regions, to answer the question: Does management exert a stronger influence on NEP than environmental factors? We estimated Geographically Weighted Regression models of NEP derived from the Ecosystem Demography Model as a function of soil, topography, climate, and forest management practices for the period 2000-2015 using 383 and 407 10 × 10 km2 landscapes in SEUS and PNW, respectively. Results showed that forest management practices were important in predicting NEP only in mountainous northeastern areas of the SEUS; in the PNW, NEP had a more complex relationship with management and was positively related to ecological, preservation, and passive management. Management, topography, and soil were more strongly correlated with NEP in the PNW than in the SEUS, in which 81%, 83%, and 83% of PNW locations showed significant relationships with at least one management, topography, or soil variable, repectively. In contrast, seasonal precipitation and temperature were stronger predictors of NEP in the SEUS than other drivers, with 99% and 84% of the locations influenced by at least one seasonal temperature or precipitation variable, respectively. The findings of this study may provide a valuable framework for forest management - climate change strategies that could be extended across regional scales.

Global Greenhouse Gas Emissions From Agriculture: Pathways to Sustainable Reductions

Agriculture serves as both a source and a sink of global greenhouse gases (GHGs), with agricultural intensification continuing to contribute to GHG emissions. Climate-smart agriculture, encompassing both nature- and technology-based actions, offers promising solutions to mitigate GHG emissions. We synthesized global data, between 1990 and 2021, from the Food and Agriculture Organization (FAO) of the United Nations to analyze the impacts of agricultural activities on global GHG emissions from agricultural land, using structural equation modeling. We then obtained predictive estimates of agricultural GHG emissions for the future period of 2022-2050 using deep-learning models. The FAO data show that, from 1990 to 2021, global livestock numbers, inorganic nitrogen (N) fertilizer use, crop residue, and irrigation area increased by 27%, 47%, 49%, and 37%, respectively. The increased livestock numbers contributed to the increases in CH4 and N2O emissions, while inorganic N fertilizer, crop residue, and irrigation mainly contributed to the increases in N2O emissions. Emissions of CO2 decreased because of a 29% reduction in net forest loss. As a result of the reduced deforestation emissions, the overall agricultural GHG emissions declined from 11.50 to 10.89 GtCO2eq from 1990 to 2021 despite the increases in livestock numbers, inorganic N fertilizer, crop residue, and irrigation. Looking ahead, our model predicts that if current agricultural trends persist, GHG emissions will rise to 11.82 ± 0.07 GtCO2eq in 2050. However, maintaining agricultural GHG emissions at the 2021 level through 2050 is possible if the rate of reduction in net forest loss is doubled. Furthermore, if the rate is tripled, agricultural GHG emissions can be limited to 9.85 ± 0.07 GtCO2eq in 2050. Our findings suggest that reductions in agricultural GHG emissions, alongside sustainable agricultural intensification and climate-smart agricultural practices, can be achieved through parallel efforts emphasizing accelerated forest conservation.

Contrasting forest management strategies: Impacts on biodiversity and ecosystem services under changing climate and disturbance regimes

Natural disturbances may compromise the past and ongoing efforts to increase carbon sequestration and halt biodiversity loss in boreal forests. Measures to minimize the effects of forest disturbances i.e., adaptive management, offer solutions to secure future timber yields. However, the consequences of adaptive management on biodiversity, the climate change mitigation potential of forests, and other ecosystem services are not well understood. In addition, the impact of climate change and disturbances on future forest-based mitigation potential is not well known. We compared the effects of forest management options emphasizing climate change mitigation or adaptation on boreal forests in changing climate and disturbance regimes in southern Finland. We used the process-based forest landscape and disturbance model iLand to dynamically model interactions between climate change and disturbances together with forest management and protection options, and examined the consequent effects on forest carbon storage, berry yields, recreation, and structural attributes important for biodiversity. Mitigation managements resulted in up to one-fifth higher carbon stocks, even after accounting for disturbances by wind and bark beetles, but halved annual harvests over the 80-year simulation period. Adaptive managements reduced bark beetle disturbances, but in some cases the disturbed volumes were even higher than under business-as-usual management due to increased wind damage. The effects of proactive risk management depended on the time horizon considered, the adaptive management option chosen and the climate change scenario. In general, the mitigation managements had positive effects on the biodiversity indicators studied, while the effects of adaptive management were mixed. Our results highlight the complex interactions between disturbance risk prevention, biodiversity, carbon sequestration and storage, and other ecosystem services. The results guide forest managers and policymakers to plan mitigation and adaptation strategies optimizing multiple benefits, and strengthening forest resilience in a changing climate.

Paradigm of engineering recalcitrant non-model microorganism with dominant metabolic pathway as a biorefinery chassis

The development and implementation of microbial chassis cells have profound impacts on circular economy. Non-model bacterium Zymomonas mobilis is an excellent chassis owing to its extraordinary industrial characteristics. Here, the genome-scale metabolic model iZM516 is improved and updated by integrating enzyme constraints to simulate the dynamics of flux distribution and guide pathway design. We show that the innate dominant ethanol pathway of Z. mobilis restricts the titer and rate of these biochemicals. A dominant-metabolism compromised intermediate-chassis (DMCI) strategy is then developed through introducing low toxicity but cofactor imbalanced 2,3-butanediol pathway, and a recombinant D-lactate producer is constructed to produce more than 140.92 g/L and 104.6 g/L D-lactate (yield > 0.97 g/g) from glucose and corncob residue hydrolysate, respectively. Additionally, techno-economic analysis (TEA) and life cycle assessment (LCA) demonstrate the commercialization feasibility and greenhouse gas reduction capability of lignocellulosic D-lactate. This work thus establishes a paradigm for engineering recalcitrant microorganisms as biorefinery chassis.

Reconciling the EU forest, biodiversity, and climate strategies

Forests provide important ecosystem services (ESs), including climate change mitigation, local climate regulation, habitat for biodiversity, wood and non-wood products, energy, and recreation. Simultaneously, forests are increasingly affected by climate change and need to be adapted to future environmental conditions. Current legislation, including the European Union (EU) Biodiversity Strategy, EU Forest Strategy, and national laws, aims to protect forest landscapes, enhance ESs, adapt forests to climate change, and leverage forest products for climate change mitigation and the bioeconomy. However, reconciling all these competing demands poses a tremendous task for policymakers, forest managers, conservation agencies, and other stakeholders, especially given the uncertainty associated with future climate impacts. Here, we used process-based ecosystem modeling and robust multi-criteria optimization to develop forest management portfolios that provide multiple ESs across a wide range of climate scenarios. We included constraints to strictly protect 10% of Europe's land area and to provide stable harvest levels under every climate scenario. The optimization showed only limited options to improve ES provision within these constraints. Consequently, management portfolios suffered from low diversity, which contradicts the goal of multi-functionality and exposes regions to significant risk due to a lack of risk diversification. Additionally, certain regions, especially those in the north, would need to prioritize timber provision to compensate for reduced harvests elsewhere. This conflicts with EU LULUCF targets for increased forest carbon sinks in all member states and prevents an equal distribution of strictly protected areas, introducing a bias as to which forest ecosystems are more protected than others. Thus, coordinated strategies at the European level are imperative to address these challenges effectively. We suggest that the implementation of the EU Biodiversity Strategy, EU Forest Strategy, and targets for forest carbon sinks require complementary measures to alleviate the conflicting demands on forests.

Carbon storage through China's planted forest expansion

China's extensive planted forests play a crucial role in carbon storage, vital for climate change mitigation. However, the complex spatiotemporal dynamics of China's planted forest area and its carbon storage remain uncaptured. Here we reveal such changes in China's planted forests from 1990 to 2020 using satellite and field data. Results show a doubling of planted forest area, a trend that intensified post-2000. These changes lead to China's planted forest carbon storage increasing from 675.6 ± 12.5 Tg C in 1990 to 1,873.1 ± 16.2 Tg C in 2020, with an average rate of ~ 40 Tg C yr-1. The area expansion of planted forests contributed ~ 53% (637.2 ± 5.4 Tg C) of the total above increased carbon storage in planted forests compared with planted forest growth. This proactive policy-driven expansion of planted forests has catalyzed a swift increase in carbon storage, aligning with China's Carbon Neutrality Target for 2060.

Making the biochemical conversion of lignocellulose more robust

Lignocellulose is an alternative to fossil resources, but its biochemical conversion is not economically competitive. While decentralized processing can reduce logistical cost for this feedstock, sugar platforms need to be developed with energy-saving pretreatment technologies and cost-effective cellulases, and products must be selected correctly. Anaerobic fermentation with less energy consumption and lower contamination risk is preferred, particularly for producing biofuels. Great effort has been devoted to producing cellulosic ethanol, but CO2 released with large quantities during ethanol fermentation must be utilized in situ for credit. Unless titer and yield are improved substantially, butanol cannot be produced as an advanced biofuel. Microbial lipids produced through aerobic fermentation with low yield and intensive energy consumption are not affordable as feedstocks for biodiesel production.

Accounting for albedo change to identify climate-positive tree cover restoration

Restoring tree cover changes albedo, which is the fraction of sunlight reflected from the Earth's surface. In most locations, these changes in albedo offset or even negate the carbon removal benefits with the latter leading to global warming. Previous efforts to quantify the global climate mitigation benefit of restoring tree cover have not accounted robustly for albedo given a lack of spatially explicit data. Here we produce maps that show that carbon-only estimates may be up to 81% too high. While dryland and boreal settings have especially severe albedo offsets, it is possible to find places that provide net-positive climate mitigation benefits in all biomes. We further find that on-the-ground projects are concentrated in these more climate-positive locations, but that the majority still face at least a 20% albedo offset. Thus, strategically deploying restoration of tree cover for maximum climate benefit requires accounting for albedo change and we provide the tools to do so.

Land potential assessment and trend-analysis using 2000-2021 FAPAR monthly time-series at 250 m spatial resolution

The article presents results of using remote sensing images and machine learning to map and assess land potential based on time-series of potential Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) composites. Land potential here refers to the potential vegetation productivity in the hypothetical absence of short-term anthropogenic influence, such as intensive agriculture and urbanization. Knowledge on this ecological land potential could support the assessment of levels of land degradation as well as restoration potentials. Monthly aggregated FAPAR time-series of three percentiles (0.05, 0.50 and 0.95 probability) at 250 m spatial resolution were derived from the 8-day GLASS FAPAR V6 product for 2000-2021 and used to determine long-term trends in FAPAR, as well as to model potential FAPAR in the absence of human pressure. CCa 3 million training points sampled from 12,500 locations across the globe were overlaid with 68 bio-physical variables representing climate, terrain, landform, and vegetation cover, as well as several variables representing human pressure including: population count, cropland intensity, nightlights and a human footprint index. The training points were used in an ensemble machine learning model that stacks three base learners (extremely randomized trees, gradient descended trees and artificial neural network) using a linear regressor as meta-learner. The potential FAPAR was then projected by removing the impact of urbanization and intensive agriculture in the covariate layers. The results of strict cross-validation show that the global distribution of FAPAR can be explained with an R2 of 0.89, with the most important covariates being growing season length, forest cover indicator and annual precipitation. From this model, a global map of potential monthly FAPAR for the recent year (2021) was produced, and used to predict gaps in actual vs. potential FAPAR. The produced global maps of actual vs. potential FAPAR and long-term trends were each spatially matched with stable and transitional land cover classes. The assessment showed large negative FAPAR gaps (actual lower than potential) for classes: urban, needle-leave deciduous trees, and flooded shrub or herbaceous cover, while strong negative FAPAR trends were found for classes: urban, sparse vegetation and rainfed cropland. On the other hand, classes: irrigated or post-flooded cropland, tree cover mixed leaf type, and broad-leave deciduous showed largely positive trends. The framework allows land managers to assess potential land degradation from two aspects: as an actual declining trend in observed FAPAR and as a difference between actual and potential vegetation FAPAR.

A global synthesis and conceptualization of the magnitude and duration of soil carbon losses in response to forest disturbances

Aim

Forest disturbances are increasing around the globe due to changes in climate and management, deteriorating forests' carbon sink strength. Estimates of global forest carbon budgets account for losses of plant biomass but often neglect the effects of disturbances on soil organic carbon (SOC). Here, we aimed to quantify and conceptualize SOC losses in response to different disturbance agents on a global scale.

Location

Global.

Time Period

1983-2022.

Major Taxa Studied

Forest soils.

Methods

We conducted a comprehensive global analysis of the effects of harvesting, wildfires, windstorms and insect infestations on forest SOC stocks in the surface organic layer and top mineral soil, synthesizing 927 paired observations from 151 existing field studies worldwide. We further used global mapping to assess potential SOC losses upon disturbance.

Results

We found that both natural and anthropogenic forest disturbances can cause large SOC losses up to 60 Mg ha-1. On average, the largest SOC losses were found after wildfires, followed by disturbances from windstorms, harvests and insects. However, initial carbon stock size, rather than disturbance agent, had the strongest influence on the magnitude of SOC losses. SOC losses were greatest in cold-climate forests (boreal and mountainous regions) with large accumulations of organic matter on or near the soil surface. Negative effects are present for at least four decades post-disturbance. In contrast, forests with small initial SOC stocks experienced quantitatively lower carbon losses, and their stocks returned to pre-disturbance levels more quickly.

Main Conclusions

Our results indicate that the more carbon is stored in the forest's organic layers and top mineral soils, the more carbon will be lost after disturbance. Robust estimates of forest carbon budgets must therefore consider disturbance-induced SOC losses, which strongly depend on site-specific stocks. Particularly in cold-climate forests, these disturbance-related losses may challenge forest management efforts to sequester CO2.

Integrated global assessment of the natural forest carbon potential

Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system1. Remote-sensing estimates to quantify carbon losses from global forests2-5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced6 and satellite-derived approaches2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151-363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

The role of forests in the EU climate policy: are we on the right track?

BACKGROUND

The European Union (EU) has committed to achieve climate neutrality by 2050. This requires a rapid reduction of greenhouse gas (GHG) emissions and ensuring that any remaining emissions are balanced through CO₂ removals. Forests play a crucial role in this plan: they are currently the main option for removing CO₂ from the atmosphere and additionally, wood use can store carbon durably and help reduce fossil emissions. To stop and reverse the decline of the forest carbon sink, the EU has recently revised the regulation on land use, land-use change and forestry (LULUCF), and set a target of - 310 Mt CO₂e net removals for the LULUCF sector in 2030.

RESULTS

In this study, we clarify the role of common concepts in forest management - net annual increment, harvest and mortality - in determining the forest sink. We then evaluate to what extent the forest sink is on track to meet the climate goals of the EU. For this assessment we use data from the latest national GHG inventories and a forest model (Carbon Budget Model). Our findings indicate that on the EU level, the recent decrease in increment and the increase in harvest and mortality are causing a rapid drop in the forest sink. Furthermore, continuing the past forest management practices is projected to further decrease the sink. Finally, we discuss options for enhancing the sinks through forest management while taking into account adaptation and resilience.

CONCLUSIONS

Our findings show that the EU forest sink is quickly developing away from the EU climate targets. Stopping and reversing this trend requires rapid implementation of climate-smart forest management, with improved and more timely monitoring of GHG fluxes. This enhancement is crucial for tracking progress towards the EU's climate targets, where the role of forests has become - and is expected to remain - more prominent than ever before.