Environmental Research Letters

The integrity of forest-based climate solutions and carbon credits requires persistent carbon storage, but climate change is increasing the risk of natural disturbances that release carbon back into the atmosphere. Using global satellite data, disturbance modeling, and machine learning, we provide the first spatially explicit and scenario-based maps of long-term probability of carbon loss in global forests under different disturbance severities and climate scenarios. We find that North American conifer forests, tropical rainforests, and Asian (sub)tropical dry forests face the greatest risks, and that Eurasian temperate forests, African (sub)tropical dry forests face the lowest. Globally, the likelihood of reversals over 100 years is 31%-42% across all scenarios. Our work helps to maximize the benefits of forest-based climate solutions by informing more strategic project placement and more robust reversal-risk compensation mechanisms, such as buffer pools, and highlights critical additional science to better understand and manage risks of these essential climate solutions. Plain Language SummaryForests can help slow and lessen climate impacts. However, in places this benefit is becoming less reliable as climate change increases natural disturbances such as wildfires, drought, storms, and insect outbreaks, which can release stored carbon back into the atmosphere. In this study, we created the first scenario-based global maps of risks and found that the risk of carbon loss is widespread and highly variable across regions, with especially high vulnerability in North American conifer forests, tropical rainforests, and Asian tropical and subtropical dry forests. Our study highlights the importance of considering disturbance risks when siting forest projects for climate mitigation, and developing protocols for carbon markets, such as in voluntary programs and under the UNFCCC Paris Agreement. Key PointsO_LIA demographic model framework estimates the reversal risk from natural disturbances over 100 years in global forests C_LIO_LISpatially explicit maps under different severity scenarios show variation in the integrated 100-year risk of carbon reversal C_LIO_LISpatially explicit maps estimate the required buffer pool needed to compensate for disturbance-driven reversals in global forests C_LI

Climate change affects food systems through multiple pathways, yet the isolated effects of climate-driven ecosystem productivity changes remain poorly understood. While field studies translate productivity changes to crop yields, at larger scales yield conflates productivity with management and technology, and critically, productivity changes occur across all vegetation types, not just agricultural lands. We isolate ecosystem productivity changes to trace their propagation through food systems across three socioeconomic scenarios (SSP1-2.6, SSP3-7.0, SSP5-8.5) by coupling the CLASSIC land surface model with GCAM integrated assessment model. Productivity changes lead to crops systematically shifting from human consumption to animal feed and bioenergy (up to 15% reallocation), while there is a significant transition of managed agricultural lands to unmanaged lands by up to 6 million km2 as productivity gains enable less intensive land use. These changes drive extreme regional divergence, with food production volume changing from +35% to -28% and substantial portfolio reorganization. Disruptions peak under regional rivalry (SSP3-7.0), revealing how fragmented governance amplifies biophysical feedbacks beyond climate forcing alone. While how much we eat may remain stable, ecosystem productivity fundamentally reshapes what we eat and where to source it.

Monitoring, halting and reversing land conversion is fundamental to meeting international biodiversity and climate targets, and agriculture is the major driver of land conversion. We present an open access set of global data for calculating land use change impacts of agricultural supply chains. These data, originally prepared for the LandGriffon service, include indicators of deforestation, conversion of natural ecosystems, greenhouse gas emissions, and loss of intact or high integrity ecosystems following international standards and guidelines for reporting and target setting in the agriculture, forestry, and land use sector. In order to assign impacts to agricultural production, we prepare data using a spatial adaptation of the statistical Land Use Change (sLUC) accounting approach distributing impact to human activities across the local area using a 50km radius. The results are high resolution global maps of impact per hectare of land occupation. These can then be combined with land footprint data, cropland extent, or productivity maps to calculate land use change related impacts for specific crop volumes sourced from specific regions. Carbon and deforestation results are validated against FAO statistics at the national level.

Process-based cropping systems models (CSMs) are key components of measurement, monitoring, reporting, and verification (MMRV) frameworks of carbon markets, but their application suffers from model-specific differences that keep any one model from working well across all combinations of soils, climates, crops, and agronomic practices at varying scales. Multi-model ensemble (MME), successfully used to quantify soil, management and climate impact on crop productivity, provide an opportunity to better estimate changes in soil organic carbon (SOC) outcomes for agronomic practices that have the potential to mitigate SOC loss at scale. We used an MME across 46 million hectares of US Midwest cropland at a resolution of 4- km2 to assess the aggregate ability of different regenerative practices to sequester SOC at this scale compared to their dynamic baselines. MME was validated with long-term experimental data and compared to its constituent CSMs, showing greater accuracy and lower uncertainty. The results show that adopting no-till combined with cover crops increased SOC stocks by 0.36 {+/-} 0.12 Mg ha-1 yr-1 aggregated across the entire U.S. Midwest cropland. At the regional scale, this corresponds to a net SOC gain of 16.4 Tg C yr-1 compared to business-as-usual baselines. These benefits are approximately halved when each management change is practiced individually, and the modest gains are only fully realized when continued over the long-term in soils with low initial carbon stock. Results demonstrate the power of MMEs run at high resolution for providing robust estimates of environmental outcomes following agricultural practice change, and for pinpointing locations for most effective intervention. This approach can alleviate many producer carbon market participation barriers and help address market issues while ultimately supporting large-scale regenerative agriculture initiatives.

We believe the carbon removal potential of 205 Gt C reported by Bastin et al. (2019) to be overestimated. The authors did not consider the carbon already stored on the land with identified tree restoration potential. For instance, grasslands and degraded forests have similar soil carbon stocks as old-growth forests. Accounting for these inconsistencies in the calculation, we estimate a carbon removal potential of 81 Gt C, i.e. only 39% of the Bastin et al. estimate. In addition, some of the assumptions about potential restoration area seem questionable and an essential question remains unanswered: why do areas identified as suitable for tree growth currently lack tree cover?

It remains challenging to quantify recent changes in forest carbon due to lags in forest inventory measurements. The national U.S. forest inventory remeasures plots every five to ten years, so quantifying current carbon stocks using inventory data requires extrapolating from the last time plots were measured. We address this extrapolation challenge by fusing spatially explicit fire disturbance and canopy cover data from Landsat with forest inventory data using a statistical model. We produce annual estimates of live forest carbon across the Western U.S. from 2005 to 2022, and find that live forest biomass increased from 2005 to 2015, and then declined by 5% from 2015 to 2022 -- a signal missed by both official U.S. reporting and Earth system models. The trend reversal was driven primarily by increasing tree mortality from wildfire, and secondarily by slowing rates of carbon accumulation in undisturbed areas. Our results highlight the importance of accounting for rapidly changing disturbance regimes, and can help to improve jurisdictional carbon accounting and inform the extent to which federal and state climate mitigation strategies can rely on land to achieve net-zero emissions targets. Significance statementPolicy makers need to accurately and rapidly assess the status of the land carbon sink in order to make land management decisions and to assess progress towards climate commitments. However, lags in on-the-ground measurements make it challenging to do so, and it remains an open question whether Western U.S. forests are a net sink or a source of carbon. We fuse on-the-ground forest measurements with remote sensing data to show that live biomass is net declining in Western U.S. forests, and that this trend is driven primarily by increasing wildfire activity. This result challenges the idea that jurisdictions can rely on the land to offset fossil emissions, and supports tracking land carbon trends separately from fossil emissions inventories.

Extreme temperatures threaten agriculture and exacerbate global food insecurity, yet their direct impact on dietary choices remains poorly understood. We provide novel evidence of how short-term exposures to extreme temperatures affect macronutrient intake in China. We show that both hot and cold weather elevate high-fat diet risks. In particular, hot weather reduces carbohydrate and protein consumption but not fat intake, while cold weather increases all nutrient intake, particularly fats. Temperature-induced dietary changes are shaped primarily by physiological responses to thermal stress, whereas physical activities demonstrate little effect. Technologies that improve indoor thermal comfort (via fans, air conditioners, and heating systems) substantially mitigate high-fat diet risks. Socioeconomic disparities are evident, with rural and poor individuals more likely to adopt high-fat diets under hot or cold weather. Projections indicate that more extreme temperatures due to climate change may increase the prevalence of high-fat diets nationally, while substantial regional heterogeneity emerges, with declines in northeast China and increases in southern China. These results highlight a crucial but overlooked pathway linking climate change to dietary health inequality.

Globally, forests play an important role in climate change mitigation. However, land-use impacts the ability of forests to sequester and store carbon. Here we quantify the impacts of five divergent future land-use scenarios on aboveground forest carbon stocks and fluxes throughout New England. These scenarios, four co-designed with stakeholders from throughout the region and the fifth a continuation of recent trends in land use, were simulated by coupling a land cover change model with a mechanistic forest growth model to produce estimates of aboveground carbon over 50 years. Future carbon removed through harvesting and development was tracked using a standard carbon accounting methodology, modified to fit our modeling framework. Of the simulated changes in land use, changes in harvesting had the most profound and immediate impacts on carbon stocks and fluxes. In one of the future land-use scenarios including a rapid expansion of harvesting for biomass energy, this changed New Englands forests from a net carbon sink to a net carbon source in 2060. Also in these simulations, relatively small reductions in harvest intensities (e.g., 10% reduction), coupled with an increased percent of wood going into longer-term storage, led to substantial reductions in net carbon emissions (909 MMtCO2eq) as compared to a continuation of recent trends in land use. However, these projected gains in carbon storage and reduction in emissions from less intense harvesting regimes can only be realized if it is paired with a reduction in the consumption of the timber products, and their replacements, that otherwise would result in additional emissions from leakage and substitution.

Droughts severely affect our environments, biodiversity, production systems and communities. When assessing droughts, we generally consider deficits in rainfall, subsurface water, water for crops and water for societies, economies and the environment. Due to climate change, increasing temperatures and more frequent and prolonged drought events are occurring in Australia and globally. When droughts and extreme temperatures occur together in the same space and time, it results in hot droughts, a phenomenon that can be devastating for flora, fauna and society. Here, we map hot drought events across Western Australia since 1889. Our results indicate that significant hot droughts have become more frequent, with the most severe hot droughts on record occurring within the last five years. Additionally, hot droughts within the last four decades, and particularly within the last two decades, affected a significantly larger area than the average for the historical record. With 2024 already on track to be the driest and hottest year on record in southwest Western Australia, natural resource managers must prepare for the increasing frequency and severity of hot droughts. Implication for ManagersO_LIAustralia and the world are experiencing more frequent and intense droughts and heatwaves. Hot droughts, characterised by simultaneous extreme water scarcity and extreme high temperatures, are particularly devastating. C_LIO_LIWe mapped hot drought events in Western Australia since 1889, revealing a recent surge in occurrence concentrated in the most recent five years. Statistical testing indicates that hot droughts within the most recent 20 and 40 years were significantly larger in extent compared to the historical average. C_LIO_LIWith the first half of 2024 exceptionally dry and hot, proactive strategies are imperative for natural resource managers. C_LI

Renewable energy is crucial to achieve climate neutrality, but its rapid expansion can threaten biodiversity through habitat loss or fragmentation and ecological disruption. We present a spatially explicit assessment framework that quantifies biodiversity impacts from land use change associated with renewable energy infrastructure across a broad range of species groups, and identifies siting configurations that balance energy provision and conservation goals. Drawing on metrics from life cycle assessment, combined with species distribution models and siting strategies, we evaluate alternative deployment strategies. Using Switzerland as a case study, we compare three siting strategies (maximizing energy output, minimizing biodiversity impact, and a trade-off approach) for photovoltaic systems, run-of-river hydropower, and wind turbines. For solar and hydropower installations, prioritizing energy efficiency yields the highest cumulative biodiversity losses. However, these impacts can be substantially reduced with only a slight increase in land use by favouring biodiversity protection. For wind installations, strict avoidance of sensitive ecosystems may increase total impacts, as less efficient and therefore additional sites are required to achieve the same annual energy yield. Overall, our results show that trade-off-based siting strategies can effectively balance performance and biodiversity protection, highlighting that renewable energy can be provided without sacrificing sensitive ecosystems.

Reforestation is an important strategy for nature-based climate solutions and identifying carbon storage potential of different locations is critical to its success. Applying average carbon values from forest inventories ignores the spatial heterogeneity in forest carbon and the effects of forest edges on carbon storage degradation. Here we show how spatially-explicit, predictive carbon modeling, that leverages satellite, social and biogeophysical datasets, can be used to identify more efficient restoration opportunities for climate mitigation than area-based carbon stock averages. Accounting for regeneration of forest edges, in addition to reforestation, boosts estimates of potential carbon gains by more than 20%. The total potential carbon gain that could be achieved through reforestation at the level indicated by the Bonn Challenge (350Mha) is 51 Gt CO2-eq, but the "missing carbon" in our current forests accounts for 64.6 Gt CO2-eq globally; the greatest potential carbon gains are found in areas of high fragmentation.

Nature-based climate solutions in Earths forests could strengthen the land carbon sink and contribute to climate mitigation, but must adequately account for climate risks to the durability of carbon storage. Forest carbon offset protocols use a buffer pool to insure against disturbance risks that may compromise durability. However, current buffer pool tools and allocations are not based on existing scientific data or models. Here, we use a tropical forest stand biomass model and an extensive set of long-term tropical forest plots to test whether current buffer pools are adequate to insure against observed disturbance regimes. We find that forest age and disturbance regime both influence necessary buffer pool sizes. In the vast majority of disturbance scenarios, current buffer pools are substantially smaller than required by carbon cycle science. Buffer pool estimates urgently need to be updated based on rigorous, open scientific datasets for nature-based climate solutions to succeed. Plain Language SummaryForests could contribute to climate mitigation through conservation and restoration activities. Carbon offsets are a widespread pathway to fund these nature-based climate solutions in forests, but must account for the risks to durability that forests face in a changing climate. Current carbon offset protocols have a buffer pool to insure against risk in different disturbance regimes, but the buffer pool contributions have not been tested with observed disturbance regimes and rigorous models. We tested these contributions using widespread tropical forest plot data and a carbon cycle model and find that the current buffer pool contributions are generally not adequate for most disturbance regimes. Our results highlight that better datasets, models, and tools are urgently needed in forest carbon offset protocols. Key pointsO_LINature-based climate solutions in forests face substantial and rising climate risks to durability C_LIO_LICarbon offsets use a buffer pool to insure against disturbance, which is not currently based on rigorous evidence C_LIO_LIOur results reveal current carbon offset protocols do not have an adequate buffer pool for most tropical forest disturbance regimes C_LI

Vegetation plays a crucial role in the Earths system, and its characteristics are strongly influenced by climate. Previous studies have investigated the climate-vegetation relationship, often attempting to predict vegetation types based on climate data. Many of them have utilized biome types as proxies for different vegetation forms. Biomes, although widely used, are not always optimal for this task. They are broadly defined, a priori linked to climate, and subject to change over time. This study proposes a novel approach by using the local composition of land cover (LC) categories as descriptors of vegetation types and examines the feasibility of modeling such compositions based on climate data. The investigation focuses on the Sahel region of Africa, which is tessellated into 5 x 5 km square tiles, serving as the basic units of analysis. The independent variable comprises a set of bioclimatic variables assigned to each tile, while the dependent variable consists of shares of each LC category within the tile. The modeling framework involves a set of n regressions, one for each LC category. The K-nearest neighbors (KNN) algorithm is employed to ensure that interdependently predicted shares sum up to 100%. The models performance is validated using 2010 data, where both climate and LC information are available. The mean absolute value of residuals ranges from 1% to 11%, depending on the LC category. Subsequently, future predictions of LC patterns are made for 2040, 2070, and 2100 using climate projections under IPCC scenarios 370 and 585. A novel visualization technique called synthetic landscape is introduced to visually compare the temporal sequence of predicted LC maps from 2010 to 2100 with similar sequences of biome maps and Koppen-Geiger climate type maps. This comparison highlights overall similarities across all sequences but also reveals some significant differences.

Forests are central to the EUs climate neutrality strategy, currently offsetting [~]9% of total greenhouse gas emissions and offering further mitigation potential through harvested wood products and the substitution effect. However, the climate benefit of the forest sector is influenced by multiple interacting factors, including forest management, climate change, wood-use strategies, and assumptions about substitution benefits, as well as the timing and fate of carbon across the forest ecosystem and technosphere. To evaluate these drivers, we used a coupled forest growth and a wood products model to simulate five different silvicultural strategies under three climate change scenarios, four wood use schemes, and five displacement factor decay pathways over a 285-year period (2015-2300), applied to a Pinus nigra forest in Italy, questioning the impact of these factors on climate mitigation potential of the forest sector. We assessed forest sector balance (FSB, net carbon exchange between forest system and atmosphere), radiative forcing from biogenic CO2 (RFbio), and mitigation efficiency (ME) - the proportion of sequestered carbon contributing to net climate benefit. Results showed that FSB and RFbio were "broadly" aligned, but ME varied with the magnitude and duration of biogenic emissions. The scenarios BIOE (bioenergy) and TM (modular cutting) achieved high FSB but showed lower ME due to concentrated or sustained emissions. WOOD (promotion of long-lived wood) and ADAPT (adaptation management) yielded higher ME under SSP1-2.6, while several strategies (WOOD, ADAPT, TRANS) became net sources under SSP5-8.5 after 2200. Substitution benefits declined under degressive assumptions, reducing mitigation by up to 53% especially for high-harvest scenarios. FSB was primarily shaped by climate and management, secondly by substitution, however; wood-use strategies had no significant long-term effect provided they did not impact resource availability. Together, these findings underscore that effective forest-sector mitigation requires not only maximizing cumulative carbon stocks, but also minimizing the magnitude, timing, and atmospheric residence time of emissions while carefully considering the role of substitution benefits. HighlightsO_LIThe long-term forest sector carbon balance is mainly governed by active management, climate conditions, and wood substitution pathways. C_LIO_LIForest Sector Balance as a metric is "broadly" aligned with the radiative forcing from biogenic emissions C_LIO_LIThe mitigation efficiency of forest sector options depends on emissions timing, duration, and amplitude C_LIO_LISubstitution factors also known as displacement factors need to be considered with greater caution C_LI

AbstractThe ability to accurately assess ecosystem C budgets across scales from individual sites to continents is essential for C accounting, management, and ultimately mitigating climate change. State data assimilation (SDA) provides a framework for harmonizing observations with models, while robustly accounting for and reducing multiple sources of uncertainty. In this study, we employed a hybrid SDA framework that combines process-based terrestrial biosphere modeling, hierarchical Bayesian inference, and machine learning to harmonize bottom-up and remotely-sensed data streams for 8,000 pre-selected 1km2 locations across North America within a hybrid structure. Combining bottom-up soils data (SoilGrids) with spectral (MODIS and Landsat) and microwave (SMAP) remote sensing helps constrain the major C and water stocks through space and time. Machine learning is used both to identify and correct systematic errors in the process model (SIPNET) and to interpolate the pre-selected locations onto a 1km grid, making it computationally feasible to generate annual ensemble maps of the North American carbon budget. Furthermore, the uncertainties for each variable were reduced compared to those from observations or models alone. Spatiotemporal analysis showed a slight decrease in aboveground biomass (AGB) across the western US, a loss of leaf area across the boreal, and a slight greening of the Alaskan tundra. The uncertainty trends suggest a significant reduction in the uncertainty about soil organic carbon (SOC), the largest C reservoir. Validation results show that we accurately estimate C pools, compared to the assimilated data streams and held-out observations of AGB from GEDI, ICESat-2, and the US FIA, and SOC from the ISCN network. Our ML-debiasing algorithm further improved the accuracy of major C pools (AGB, SOC). In general, our continental SDA framework will facilitate global C MRV (monitoring, reporting, and verification) by providing accurate and precise C-cycle estimates, along with their corresponding spatiotemporal uncertainties.

Over the last decade, health impact attribution studies have shown that climate change is a present-day public health emergency, with substantial impacts felt through death, disability, and illness, equivalent to financial losses on the order of US$ trillions. However, these studies have so far been biased towards the direct effects of heat and extreme weather in high-income countries, and so capture a small fraction of the total global burden of climate change. Expanding the use of attribution science in public health could help put pressure on policymakers to take action for human health.

The impacts of invasive pests and diseases are routinely estimated and measured in the context of agriculture, but less so in the context of biodiversity and ecosystem services. In this study, we estimate the potential reduction of carbon sequestration in Australia due to exotic strains of myrtle rust (Austropuccinia psidii, also known as Puccinia psidii, guava rust, or [o]hia rust). We model the contribution of susceptible plants to carbon sequestration and use previously known myrtle rust damage estimates to susceptible plant species and the valuation of carbon sequestration in Australia to estimate the potential monetary impact. This method can be systematically extended to other pests impacting plant growth as well as other ecosystem services. In the case of myrtle rust, we estimate that it could cause up to a 1.6% (95% CI: 1.3-2.0%) annual reduction in national carbon sequestration if it were to spread across all climatically suitable areas in Australia, resulting in an estimated value loss of over $340 million AUD (over $220 million USD) per year. Compared with contemporary syntheses of known cost estimates, our results show that the potential consequences of invasive species can be substantially larger than reported, and may be currently undervalued. Our work shows the need to systematically compile the potential impacts and costs to the environment and ecosystem services globally, to support both biosecurity decision-making and climate-change related initiatives such as net-zero emissions targets and reforestation efforts.

Food interventions like industrial fortification and biofortification through crop breeding can help shift towards improved healthy diets, marking a significant stride in public health. Crop breeding contributes to a stable and healthy food supply by boosting agricultural yields and the micronutrient content of staples, which is pivotal for combating chronic and hidden hunger, especially in rural areas. Fortification enhances healthy diets by adding essential vitamins and minerals to commonly consumed foods, helping prevent nutrient deficiencies and support overall well-being. The burden of hunger and its consequences on health are increasingly quantified using the Disability-Adjusted Life Years (DALYs) approach, which merges years of life lost and years lived with disability, offering a comprehensive view of health impacts and aiding in resource allocation. A practical formula for quantifying the health impact of biofortification was introduced by Stein et al. (2005) and Zimmermann and Qaim (2004). This entails calculating the efficacy or relative reduction in hunger burden based on the current and post-intervention nutrient intake against the recommended dietary allowances. As data on consumption and recommended intake levels are variable and not robustly available, this paper proposes relying on relative estimates to bridge the data gaps and uncertainties, thus streamlining the quantification of fortifications and biofortifications impact on diets and overall health.

Agriculture, along with industry and household sector are three major sectors of human consumption. Agriculture has proved to be a major contributor to exceeding planetary boundaries. Here, we have explored the impact of agriculture in the Earth system processes, through eight dimensions of planetary boundaries or safe operating spaces: climate change (10.73%), freshwater use (91.56%), arable land use (37.27%), nitrogen use (95.77%), phosphorus use (87.28%), ecological footprint (19.42%), atmospheric pollution (2.52% - 38.08%) and novel entities. In this work, we have also shown role of agriculture to the socio-economic development dimensions: gender equality, employment and economic growth. We have shown that the safe operating limits for agriculture are going to decline by almost 55% (climate change), 300% (freshwater use), 50-55% (arable land use), 180% (nitrogen use), 265% (phosphorus use) and 20% (ecological footprint) in 2050, if the most inefficient way of consumption is chosen and continued. To alleviate the role of agriculture in transgressing planetary boundaries, it is indispensable to comprehend how many roles of agriculture is playing and where which target should be set to framework the national agricultural policies in coherence with attaining sustainable development goals of UN by 2030.

Peatlands provide one of the largest terrestrial carbon stocks in the UK. However, a large proportion of peatlands are drained for peat extraction, agriculture and other uses, turning them into a major source of the UKs land use greenhouse gas (GHG) emissions. Successful restoration can ultimately return peatlands into carbon sinks. However, rewetting - the primary step in peatland restoration - can reduce CO2 emissions while increasing CH4 emissions. This may result in little overall climate benefit, or even increased warming for several years post peatland restoration, as CH4 is a short-lived but strong GHG, and may overpower the reduction in CO2. Such consequences are rarely explored in detail, since most studies are based on comparing total CO2-equivalent emissions pre- and post-restoration using the 100-year Global Warming Potential (GWP100), which can fail to reveal the full dynamics. We evaluated the emissions and resultant climate impacts from peatland restoration using data from The Wildlife Trusts, a federation of UK-based conservation charities, as a case-study. The total emissions of each restoration stage were estimated by multiplying peatland areas under restoration with up-to-date UK emission factors (EF), then compared under multiple pulse emission metrics (GWP100, GWP20, GTP100) to indicate the impacts over a range of time-horizons, and GWP* to reveal the varying warming impacts over time. We also used Monte-Carlo Simulation to investigate the uncertainties in total emissions drawing from EF ranges. We found that the restoration so far has provided large emission reductions under all metrics, even considering the uncertainties. Increased CH4 is unlikely to cause extra warming in the extremely near-term (<20 years), and if the peatlands are maintained in their rewetted states, they can contribute to net-cooling in the long term. There is less certainty over the climate benefits of further restoration, from rewetted to "near-natural" states, especially in the shorter term, but we argue that any risks are low, while this continued restoration will provide further ecological benefits and support biodiversity. Our study lends further support for peatland restoration in the UK and other regions with similar habitats, and provides insight into the climate roles of peatlands more broadly.